INDEX Teaming Profiles
Thank you for showing an interest in ARPA-H’s ImagiNg Data EXchange (INDEX) program. This page is designed to help facilitate connections between prospective proposers. If either you or your organization are interested in teaming, please submit your information via the portal linked below. Your details will then be added to the list below, which is publicly available.
INDEX anticipates that teaming will be necessary to achieve the goals of the program. Prospective performers are encouraged (but not required) to form teams with varied technical expertise to submit a proposal to the INDEX solicitation.
Please note that by publishing the teaming profiles list, ARPA-H is not endorsing, sponsoring, or otherwise evaluating the qualifications of the individuals or organizations included here. Submissions to the teaming profiles list are reviewed and updated periodically.
Interested in learning more about the INDEX program?
INDEX Teaming Profiles
To narrow the results in the Teaming Profiles List, please use the input below to filter results based on your search term. The list will filter as you type.
| Contact | Organization Name | Location | Description of Research Focus Area | Description of Teaming Partner | Technical Areas | |
| Dmitri Krylov, PhD | Advantex Consulting, LLC/DXComposer.ai | dmkrylov@gmail.com | Potomac, MD | DXComposer.ai is a medical informatics company. We are a team of biomedical PhDs, Software engineers and Data scientists located in Potomac, MD. Since 2009 we have been developing large scale medical applications for government and private clients. We currently are designing a medical diagnostic AI platform. We have strong capabilities in medical data processing, annotation, Federated Learning, API development, UI/UX and automation. | We are interested in teaming with a academic institution or a business with access to data and/or complimentary technical and business capabilities. Let's talk before January 23 and make it happen together. | TA2: System architecture design and implementation, TA1: Business model and business plan |
| Lit-Hsin Loo | Agency for Science, Technology, and Research (A*STAR) | loolh@bii.a-star.edu.sg | Singapore | We develop large-scale image data management and visualization methods and tools, such as cellXpress (https://cellXpress.org) and HistoPath Analytics (HPA) Platform, a fully online image data management (upload and download) and visualization platform for huge whole-slide H&E and multiplex tissue images. These tools power ImmunoAtlas (https://immunoatlas.org), an online public image repository for immuno-oncology markers. Our tools and platforms are directly usable for the INDEX program. | We are looking for collaborators from hospitals or other open-source databases that can contribute more diverse data; and/or research groups/companies that develop federated learning models, curation/annotation models, or other AI/ML applications using these image data. | TA1: Business model and business plan |
| Abhe Rajagopal | Allen Institute | abhe.rajagopal@alleninstitute.org | Seattle, WA | Multi-scale deep learning, explainable AI, distributed computing system design. We specialize in multi-omic and image data analysis, and federated learning capabilities. | We are looking for clinical data and system design collaborators. We are happy to work with you. | TA1: Business model and business plan |
| Nameeta Shah | Amaranth Medical Analytics | nameeta@amaranthmedicalanalytics.com | Bangalore, India | We have built a SaaS platform for digital pathology where you can build your own AI models and deploy them with a click of a button. Our current area of focus is on building spatial transcriptomics derived H&E based AI models, brain cancer models, and vasculature characterization. | Business model, customer base with interest in building their own medical AI | TA3: Enrollment |
| Laszlo Kokai | American Chemical Society | koki.ce890601@gmail.com | 3529 Hungary, Miskolc, Kozepszer srt. 64. | A New Era in Medicine: It’s Not the Patient Who Travels, but the Data! Our newly established experimental medical research institute has developed a revolutionary medical technology that enables diagnostic and examination results to travel in place of the patient’s physical presence. This innovation leverages artificial intelligence and advanced data integration to enhance the efficiency and accessibility of healthcare services. | Who is the program for? Initially, we are inviting a pilot group to participate in the testing phase: Those engaged in public-interest work and their family members, whose daily activities contribute significantly to society. | TA2: System architecture design and implementation |
| Mark Newburger | Apollo Enterprise Imaging Corp | mnewburger@apolloei.com | Tysons, VA | Apollo Enterprise Imaging transforms medical imaging by enabling seamless integration and secure sharing across healthcare systems. Our ARCC(r) platform connects providers and patients with comprehensive imaging records, improving care coordination and outcomes. While current sharing focuses on radiology, we are expanding to include pathology and other areas of healthcare, enhancing interoperability, simplifying access, and empowering both patients and providers with greater control. | Apollo Enterprise Imaging seeks teaming partners with cybersecurity and networking expertise to support secure, scalable medical image exchange and sharing. We value collaborators who can enhance the security, interoperability, and performance of our ARCC(r) platform as we expand its use across radiology, pathology, and the broader healthcare system. Ideal partners share our commitment to empowering providers and patients with seamless access and control over imaging data. | TA2: System architecture design and implementation |
| Adil Ahmad | Arizona State University | adil.ahmad@asu.edu | Tempe, AZ, AZ | The ASU-Mayo Center for Innovative Imaging (AMCII) was created to promote the collaborative and multidisciplinary effort to bridge engineering research with clinical practices. Our mission is to improve patient care by developing innovative therapeutic technologies, imaging acquisitions, imaging analytic tools, machine learning and artificial intelligence algorithms, taking a patient-inspired approach. | Performers with expertise on research related to pathology and surgical videos, and ones with business expertise on the sale, acquisition, and augmentation of medical images and videos. | TA3: Enrollment |
| John Kalafut | Asher Orion Group | John.kalafut@asheroriongroup.com | Pittsburgh, PA, PA | Asher Orion Group (AOG) is a global, independent, strategic product management firm for digital health and medical AI solutions. AOG provides cutting-edge solutions and consulting services that incorporate AI, clinical pathway optimization, regulatory strategy, and more. We are actively developing technologies for our clients and for our own platforms that focus on data and algorithm fairness and robustness, performance drift, and distributed compute. | We are looking to support teams with SME insights and knowledge concerning medical imaging data, workflows, ontologies, and experiences gained by working for and with data brokers and consumers of their services whom built regulated, AI products. | TA2: System architecture design and implementation, TA1: Business model and business plan |
| Michelle Churchman | Aster Insights | Michelle.Churchman@AsterInsights.com | Tampa, FL | Our mission is to accelerate the discovery and development of cures for cancer. Our vision is to revolutionize cancer research by providing exceptional data, insights and technology to solve the hardest problems in oncology. | We partner with 19 academic cancer centers comprising the Oncology Research Information Exchange Network (ORIEN) and would be interested in partnering with teams that have strengths in developing analytic tools. | TA1: Business model and business plan, TA2: System architecture design and implementation, TA3: Enrollment |
| Stephanie Randall | Axle | stephanie.randall@axleinfo.com | North Bethesda, MD | Axle specializes in accelerating organizational outcomes through a fusion of research, technology, and healthcare expertise. We focus on data analysis, modeling, and AI/ML algorithms across scientific domains (real-world data, biomedical imaging, -omics, molecular modeling, etc.) as well novel LLM implementations and integrations. For INDEX, we can adapt and reuse the tools we’ve built for data catalogs, visualization, data analysis platforms and distributed computing across different hardware. | We are looking for data provider partners with access to large networks of healthcare providers, academic institutions, and/or research centers especially for rural or underrepresented minority communities as well as partners with strong business and legal/regulatory experience with healthcare and EHR data. | TA2: System architecture design and implementation |
| Guido Mathews | Bayer AG | guido.mathews@bayer.com | Berlin, Germany, Muellerstrasse 178, 13353 Berlin | Bayer's Radiology business unit is focused on advancing medical imaging, including digital pathology to improve patient outcomes. The company is investing in AI to enhance medical imaging analysis, aiding radiologists in disease detection while reducing interpretation times. Big data analytics is harnessed to derive insights from imaging data for personalized medicine. Bayer prioritizes interoperability for seamless data integration, enhancing care coordination. | Looking for complementary expertise, innovative problem-solving capabilities, and a commitment and passion to collaboration. Track record of technical excellence, mission alignment, and adaptability to evolving project requirements. Partners who can fill critical gaps, especially on TA3, contribute resources, and foster a culture of transparency and shared goals. | TA2: System architecture design and implementation |
| Timothy Chou | BevelCloud | tim@bevelcloud.io | Palo Alto, CA | Engineered a global distributed privacy-preserving, real-time distributed AI infrastructure to allow access to real-time imaging data in hospitals, clinics and ambulances | Appication developers who would like to use the infra to accomplish the INDEX mission | TA1: Business model and business plan |
| Rajeev Malhotra | Bioconvergence Pioneering | rmalhotra@veryverse.ai | Boston, MA | Next gen compute enabled imaging analytics, licensing, and venture development that leverages advanced AI, digital twin, and blockchain technologies. | Enrollment and distribution experience and capabilities | TA2: System architecture design and implementation |
| Tapan Khan | BioImaginix LLC | khantapan67@gmail.com | Morgantown, WV | Development of AI-ML-based Imaging Technology: BioImaginix is developing a low-cost diagnostic tool for brain imaging using a generative AI-based algorithm. The algorithm tested in the classification of Alzheimer’s vs mild cognitive impairment with accuracies of 81.41% and autopsy-confirmed AD vs. MCI 92.75%. Proof-of-concept has been published in a peer-reviewed journal. Neurologists/Gerontologists will use it for diagnostic and patient stratification in clinical trials. | Potential teaming partners are neurodegenerative disease clinicians, data scientists, and regulatory advisors. | TA2: System architecture design and implementation, TA1: Business model and business plan |
| Mahdi Moqri | Biomarkers of Aging Consortium | mmoqri@bwh.harvard.edu | Boston, MA | Centralized and federated training, testing, and validation of machine learning algorithms | Expertise in imaging data modality | TA2: System architecture design and implementation |
| Rudolph Pienaar | Boston Children's Hospital | rudolph.pienaar@childrens.harvard.edu | Boston, MA | My specific team research focus is on developing large-scale cloud and HPC infrastructure specifically for AI analysis of large sets of clinical and other data, with a focus on privacy and collaboration/sharing of data. In particular our focus is to build systems to allow collaborators to analyze data "in place" on the cloud infrastructure sharing the data. We focus on not just "AI" but the supporting applications, data conversions, reporting, and powerful web-based visualizations. | Expertise in MLops, containerization, kubernetes and related technologies, CI/CD for pipelines of analysis where AI is only a part. We understand that end-to-end systems need a lot more than just an AI app, but a whole supporting structure of data conversion tools, Q/A, reporting, visualization, etc etc. | TA1: Business model and business plan |
| Yangming Ou | Boston Children's Hospital; Harvard Medical School | yangming.ou@childrens.harvard.edu | Boston, MA | We are developing AI tools on brain MRI and associated data on clinical, treatment, nutrition, socioeconomic status, environment and other factors. One topic is to quantify normal brain development across the lifespan. For this, we have accumulated 70,000+ healthy brain MRIs and associated data. A second topic is to understand how various factors contribute to brain development especially in the early life. For this, we are in the process of accumulating birth cohort datasets around the world. | 1. Harmonizing multi-site and multi-omic data from 100+ datasets, especially given thousands of non-imaging variables. 2. Data host -- the harmonized and preprocessed data should be valuable resources for the community. 3. Business plan -- we are planning consortia efforts to mine the data. | TA3: Enrollment |
| Bryan Ranger | Boston College | bryan.ranger@bc.edu | Boston, MA | Ultrasound imaging for global health applications | Clinical data collection, AI-based medical image analysis, mobile deployment of algorithms | TA3: Enrollment |
| Kayhan Batmanghelich | Boston University | batman@bu.edu | Boston, MA | We have developed a highly accurate, customizable, and controllable generative model for medical images that can be used to share medical images with customers, eliminating the concern about data privacy. | - Businesses interested in partnering with us to commercialize our software - Data vending business interested in partnering with us | TA2: System architecture design and implementation |
| Fleming Lure | Caddie Technology Inc (https://caddieai.io/) | fleming.lure@caddieai.io | Potomac, MD | Develop fully automatic SIFT annotation system to provide tool/data/service for researcher to train AI, clinical trial & accurate medical coding: generative-AI (LLM); fusing DL/LLM for multi-modality multi-lesion to create hybrid annotated data & comorbidity; uncertainty measure to quantify/stratify performance; blockchain for security, cross validation of annotation & IP to create digital asset. Develop FRIENDS exchange platform to license annotated data/SIFT; offer annotation/CRO-4-AI service. | Smart Imagery Framing & Truthing (SIFT) annotates 69&47 lesions on CXR & CT. Offer hi-quality & affordable annotation service to train AI & FDA trial. Develop Federated Resource Integration for Economic and Networked Depositary System (FRIENDS) for medical data exchange. Annotated 500k publicly available CXR/CT from MIDRC, NIAID, CC/NIH, Stanford, Harvard & NLST. Backed 15 MRMC/FDA trials. Seek partners in Ta2 system architecture & implementation; leveraging FRIENDS & revenue models for INDEX. | TA2: System architecture design and implementation |
| Callie Weiant | CaliberMRI | cweiant@qmri.com | Boulder, CO | CaliberMRI develops quantitative MRI phantoms and companion QA/QC software to improve data quality in the age of AI. We currently offer standardization of major quantitative MRI biomarkers (e.g. diffusion and relaxometry) as well as geometric accuracy. Products relevant for data, acceptance testing, clinical trials, longitudinal and cross-site monitoring, R&D and AI/ML validation. Multiple applications: oncology, neurordegenerative, MSK, cardiac etc. | CaliberMRI seeks to support partners aiming to ensure high quality MRI data, standardization, and harmonization. CaliberMRI can develop custom phantoms and/or offer existing products to support R&D, clinical trials, QA/QC, and datasets for AI/ML applications and tools. | TA2: System architecture design and implementation, TA1: Business model and business plan, TA3: Enrollment |
| MAC TAKETANI | CarbGeM Inc | makoto.taketani@gmail.com | 1-5-13 Jinnan, Shibuya-ku, Tokyo 150-0041, JAPAN | CarbGeM Inc. recently introduced CarbConnect®, a cloud-based AI image analysis platform that aligns closely with the goals of the INDEX program. CarbConnect® enables users to upload, share, and analyze images in real time, fostering seamless collaboration among data providers, end-users, and medical software developers. The platform currently integrates a few in-house AI applications and invites data providers and software engineers to join and expand its capabilities. | Since we are already operating CarbConnect, which can serve as a testbed for the platform envisioned by the INDEX program, we are actively seeking data providers—particularly in radiology, pathology, and surgical imaging—as well as medical software developers with extensive experience in medical image analysis. | TA2: System architecture design and implementation, TA1: Business model and business plan |
| Xue Feng | Carina Medical | xfeng@carinaai.com | Ashburn, VA | Our company has developed a web-based data management platform that supports medical image de-identification and annotation (https://carinaai.com/deidentifier.html). The de-identification supports patient-specific date shifting, redundancy checks, AI-based burned-in text removal, LLM-based report de-identification, and mask-based defacing. It has been deployed and validated in multiple top academic hospitals. | Despite the technology and the software platform, we may have the capability to run INDEX as a self-sustaining entity due to the small size of our team. We are looking for partners so that we can contribute to TA 2 leveraging our existing software and algorithms. | TA2: System architecture design and implementation |
| Ajay Joshi | CipherSonic Labs Inc. | ajay@ciphersoniclabs.io | Cambridge, MA | CipherSonic Labs delivers a transformative cloud-based cybersecurity solution tailored for enterprises to securely share and collaboratively process data with other organizations. Our fully homomorphic encryption-based technology ensures that data remains encrypted during its entire lifecycle—while processing, in transit, and at rest—offering unparalleled data privacy and security. | We are looking for healthcare partners who generate patient data, and research labs/organizations that process patient data to develop newer medical technologies for better healthcare outcomes. | TA1: Business model and business plan |
| Shirali Nigam | Cogitamentum Bio | shirali@cogitamentumbio.com | Vienna, VA | Cogitamentum Bio combines healthcare expertise with business acumen, anchored by a Wharton MBA, to develop scalable models for cutting-edge healthcare innovation. With experience in productizing health IT for government clients, our team excels in venture building, operational planning, pricing strategy, growth and revenue forecasting, and advancing accessibility and equity to address critical gaps in data sharing, quality monitoring, and platform monetization. | We seek partners who can support enrollment and help us access and onboard data providers with diverse, high-quality imaging datasets. | TA1: Business model and business plan |
| Alexander Sicular | Consortium for Health Data Exchange P.B.C. | Siculars@gmail.com | Dallas, TX | The Consortium for Health Data Exchange PBC is a members based exchange that aims to democratize access to health information by creating a secure and trusted platform for data sharing. In partnership, we will deliver an exchange based solution with a regulatory and legal framework, and market driven price discovery for health data assets. This will promote greater transparency, empower patients, and drive innovation across the healthcare ecosystem while rigorously protecting patient privacy. | The Consortium for Health Data Exchange will respond as Prime in conjunction with various Subs in Technical Areas TA1, TA2, and TA3. Jointly with partners, we will design and build a standards compliant transaction execution and settlement based exchange. We welcome partnership from patient advocacy groups, data producing, data consuming and data facilitating organization who want to join our Consortium based vision of a market driven, transparent exchange. | TA2: System architecture design and implementation |
| Emma Wyllie | Datavant | EmmaWyllie@datavant.com | Phoenix, AZ | Datavant is a leader in privacy-preserving data exchange, connecting health data for 500+ institutions and 300 million patients, across 10 billion records. Their HIPAA-compliant solution combines with our ecosystem of data partners to support 800+ live connections. With advanced medical record retrieval and tokenization, Datavant enables the largest de-identified real-world data exchange, supporting everyone from pharmaceutical companies to large research institutions like the NIH. | We can facilitate data linkage and supplementary real-world data (RWD) inclusion to any project, and so would be seeking partners to provide the broader platform and toolkit required for this initiative. | TA3: Enrollment |
| Miklós Gyöngy | Dermus Kft | miklos.gyongy@dermusvision.com | Budapest, Hungary | Multimodal dermatology imaging (dermoscopy, ultrasound, clinical images) | Organizations interested in exchanging dermatological images for telemedicine and collaborative/federated AI | TA3: Enrollment |
| JOSEPH BOYSTAK | DrX | joeboystak@gmail.com | Los Angeles, CA | Health data exchange and ecosystem | Ecosystem partners and health care providers | TA2: System architecture design and implementation |
| Todd McCollough | Ellumen Inc. | tmccollough@ellumen.com | Silver Spring, VA | Helping to facilitate the secure sharing of medical images and related data among organizations and community healthcare providers. | Experts in whole slide pathology imaging or surgical video. | TA1: Business model and business plan |
| John Groth | Endeavor Health | jgroth@northshore.org | Evanston, IL, IL | We focus on advancing precision care by driving standards-based interoperability and integrating digital pathology, AI, multimodal imaging, clinical and other data. We aim to optimize the entire patient care process by addressing preanalytic, analytic and post analytic phases. Our areas of focus spans prostate, breast, colorectal and ovarian cancer, in addition to head and neck and other organ systems, enhancing patient engagement and interdisciplinary collaboration. | We seek teaming partners who share our commitment to innovation, precision care, and patient centered solutions, driven by standard-based interoperability. Ideal partners bring expertise in AI, multimodal imaging, digital pathology and enterprise imaging, along with a collaborative spirit to advance interoperable healthcare innovations. We value partners who contribute diverse perspectives, robust technical capabilities, and a shared vision to transform diagnostics and improve patient outcomes | TA3: Enrollment, TA2: System architecture design and implementation |
| Kristy Stengl | Enlitic, Inc. | kstengl@enlitic.com | Fort Collins, CO | Enlitic empowers healthcare providers to enhance the quality of medical imaging data through AI-driven solutions. The ENDEX module, designed to address the inconsistency and variability of medical images across different systems and institutions, leverages Computer Vision and Natural Language Processing to automatically standardize study and series descriptions, ensuring consistency and interoperability. Similarly, the ENCOG module uses AI to deidentify PHI efficiently and securely. | Enlitic seeks partners with expertise in medical imaging, AI/ML development, and interoperability. Ideal collaborators should excel in data annotation, curation, and federated learning. We value experience in informatics, standardizing imaging, and standards for interoperability. Partners should demonstrate strong regulatory compliance and commit to advancing AI-driven healthcare delivery. We prioritize those aligned with our mission to enhance data quality and operational efficiency. | TA3: Enrollment |
| Elias Lozano | Esvyda! Inc | elozano@esvyda.com | Campbell, CA | Telemedicine Platform that offers ALL reimbursable Virtual Care Services including Imaging for a number of CPT codes evaluation | AI LAC models | TA1: Business model and business plan |
| Dwayne Washington | ExpediteInfoTech, Inc. | dwashington@expediteinfotech.com | Rockville, MD | Our research focuses on AI & ML and the connection between the medical arena and the technology arena. By bridging these two communities of interest, will allow us the opportunity to deliver a more robust and patient first centric solution that addresses the needs of our community in the 21st Century and beyond. | We are seeking teaming partners who share our approach and want to build a better delivery of care that offers the best of both worlds. | TA1: Business model and business plan |
| Tyona Pike | F&I Foresight Initiatives | Pikesforesightinitiatives@gmail.com | Cookeville, TN | Our focus includes supporting patients, caregivers, families, and medical teams by addressing unmet needs, enhancing awareness, and fostering partnerships to advance diagnosis, treatment, and care. We aim to work with organizations to reduce diagnostic delays, improve patient outcomes, and develop patient-centric approaches that prioritize the unique challenges posed by rare diseases | seeking a partner to handle the technical and research aspects of our efforts in the rare disease space. While we focus on growing and maintaining support for patients, caregivers, friends and family, medical teams, and those aiding individuals along the diagnostic odyssey, we aim to collaborate with an organization that can enhance our research capabilities and drive innovative solutions. Together, we can create a comprehensive support system that addresses the unique challenges faced by those | TA3: Enrollment |
| Jeffrey Carson | Flywheel Exchange, Inc | jeffcarson@flywheel.io | Minneapolis, MN | Flywheel is a research imaging data platform that streamlines data capture from multiple sources, curates it to common standards, and automates processing and machine learning pipelines. It enables secure collaboration with internal and external partners, ensuring data security and regulatory compliance. Key features include automated data capture, configurable de-identification, data curation, image annotation, automated pipelines, and tools for efficient imaging research. | Current ARPA-H collaborators looking to improve medical image & data ingestion, curation and advanced processing. | TA3: Enrollment |
| Madeline Diep | Fraunhofer USA | mdiep@fraunhofer.org | Riverdale, MD | We are a nonprofit organization consisting of an interdisciplinary team with extensive expertise in system and software engineering, AI-based tool development, and T&E. We are well-positioned to contribute in TA2 by providing: links to the WHO and World Intellectual Property Organization "AI for Health" initiative co-led by Fraunhofer Institute, RSTKs integration, and data users capabilities such as matching AI algorithms with cohorts and datasets most likely to improve AI model performance. | We are interested in collaborating with partners with ties to data providers and data users. | TA2: System architecture design and implementation |
| Farhad Imam | Gates Ventures | farhad.imam@gatesventures.com | Seattle, WA | Gates Ventures supports secure data sharing and analysis environments, tools, and workflows via support of public, nonprofit software platforms such as the Alzheimer's Disease Data Initiative and Global Imaging Research Platform. | Gates Ventures is open to supporting data analysis and compute environments for multicenter, multimodal data collaborations. | TA1: Business model and business plan |
| Daniel Huff | GE HealthCare | daniel.huff@gehealthcare.com | Tacoma, WA | GE HealthCare has research interest in radiological image sharing for training and validation of ML models supporting image enhancement, quantitation, clinical decision support, and other areas. In particular, we have interest in molecular imaging data of patients undergoing radioligand therapies ("theranostics"). | We would be interested in teaming partners with expertise in legal/contracting with healthcare systems, infrastructure for data hosting, and data governance, and clinical partners with expertise in radiotheranostics. | TA1: Business model and business plan |
| Adonis Bovell | Georgia Tech Research Institute | adonis.bovell@gtri.gatech.edu | Atlanta, GA | GTRI is a UARC for the DoD. Our group focuses on ML model development and evaluation for AI security. Our research goes past traditional static correctness, as we develop trustworthy AI pipelines for high-risk scenarios. This includes interpretable and explainable AI, quantifiable robustness metrics, and ensuring resilience from real-world data drift, bias and intentionally adversarial attacks. Our research readily applies to health data models with similar high-impact, high-risk profiles. | GTRI is seeking teammates with strong network of health provider partners. Our teammates can unlock essential data agreements, and ensure this platform becomes self-sustaining over the long term. This will complement our focus on system architecture and model development. | TA2: System architecture design and implementation |
| Julia Komissarchik | Glendor, Inc | julia@glendor.com | Draper, UT | Glendor built software for fully automatic out-of-the-box at-source removal of PHI from multimodal medical data (images, reports, videos, photos, voice) to empower medical data sharing and monetization, while protecting patient's privacy. • Fully Automatic (unlike templates-based solutions that require customization and tweaking) • At Source (unlike APIs and 3rd party services that require sensitive data to be shared) • Easy to Integrate and Use (1 min to install and run) | We provide PHI deidentification software solution. We are looking for partners who would like to deidentify their and their contributors' data on their sites (on premises or in the cloud). Use Case 1: deidentification of data before it is shared, to ensure that there are no HIPAA violations Use Case 2: deidentification of data before it enters the exchange or partner site, to ensure that there are no HIPAA violations Can be used as standalone or to augment existing workflow. | TA3: Enrollment |
| Matthew Doxey | Google Public Sector | mdoxey@google.com | Seattle, WA | Our research focuses on secure data exchange in medical imaging. We use federated learning for privacy and blockchain for consent. AI and machine learning improve image analysis accuracy and efficiency, automating tasks and enhancing diagnostics. We aim to increase data velocity, improve price discovery, strengthen legal frameworks, and enhance collaboration in medical imaging and AI. | We are looking for potential partners that can help scale, expand, and improve the end-to-end medical imaging process | TA1: Business model and business plan |
| Alex Pchelnikov | HistAI | alex@hist.ai | San Francisco, CA | At HistAI, we leverage one of the largest fully digital datasets in pathology (2M+ WSIs, 500+ stains/assays, all organ/tissue types) to develop SOTA AI models. As pioneers in open-sourcing pathology foundation models (Hibou family, 1.2M+ downloads in 6 months), we also provide a HIPAA-compliant platform for viewing, annotation, and AI analysis. Supported by an extensive network of pathologists, we drive innovation in digital pathology. | We're looking for industry and academia partners to make the best INDEX platform together. | TA2: System architecture design and implementation, TA3: Enrollment, TA1: Business model and business plan |
| Melanie Traughber | HOPPR | melanie@hoppr.ai | Chicago, IL | We have developed a medical-grade Imaging AI platform for data de-identification, data curation, annotation, bias detection, and QA for multimodal AI model development. Our ISO 13485–compliant QMS supports regulatory readiness. We build and fine-tune foundation models that seamlessly integrate AI into clinical workflows. Our platform and tools enable large scale data curation and labeling on a multi-cloud infrastructure to train models without requiring data to leave the platform. | Access to additional data providers, AI expertise to develop regional AI solutions, opportunity to deploy and test with a diverse set of stakeholders, partners to support pathway to clinical implementation and regulatory submissions, expertise in Intelligent Process Automation (IPA) and Workflow Orchestration (WFO) in medical imaging, experts to develop standards in performance of AI tools, integrated data, and interrogation tools to detect and correct identified problems. | TA1: Business model and business plan |
| Trudy Malone | ICA | tmalone@ica.ai | Arlington, VA | Proven track record in the regulated medical device environment and deep understanding of regulatory processes. ICA also brings substantial expertise in sourcing RWD for research purposes. Expert in the application of advanced NLP and ML techniques to extract data from structured and unstructured documents. Additional experience in data annotation. Multidisciplinary teams with extensive experience applying agile project management to lead large, complex federal research programs. | We are looking for teaming partners with proven experience in developing business models around affordable access to medical imaging. We are also interested in those with expertise in design and implementation of system architecture to support INDEX TA2 requirements. | TA3: Enrollment |
| Ratima Kataria | ICF | ratima.kataria@icf.com | Reston, VA | www.icf.com | To be detailed after the proposers day | TA1: Business model and business plan |
| Maksym Krutko | imec USA | max.krutko@imec-int.com | Boston, MA | Imec, the world's leading independent nanoelectronics R&D hub. Imec offers an extensive selection of IP covering a wide range of imaging modules and concepts. This includes areas such as hyperspectral and time domain / line scan imaging, photonics enabled sensors and imagers, acoustic wave imaging and tomography and a wide range of sensors extending beyond imaging. Additionally, imec has AI/ML image analysis capabilities. | Looking to partner with all technical areas. | TA1: Business model and business plan |
| Sina Bari | iMerit | sina@imerit.net | US & India, CA | iMerit is the leader in large scale healthcare data operations for AI applications. We bring together the tools, expertise, and best practices necessary to train, tune, and validate medical models in computer vision, NLP, and generative AI. Today we are data partners to manufacturers and technologic innovators for use cases such as radiology, pathology, endoscopy, robotic surgery, and ambient scribes. | We're interested in talking to software developer partners and enrollment specialist. | TA2: System architecture design and implementation |
| Tony O'Sullivan | Impact Business Information Solutions Inc | tosullivan@ibisworks.com | Princeton, NJ | 1. EICON REACH, platform for solutions requiring Cloud control with execution at the Edge, including automated rad/path de-id at the Edge, data processing pipelines orchestration from Cloud to Edge and/or vice versa. 2. EICON Search Fabric, search-optimized index database for radiology and pathology metadata. Working on extensible multimodal solution for rad/path/++ using parallel search indices.3. EICON EXPLORER, rich Search UI for creating WSI, DICOM data cohorts with export to AI dev. | 3rd party complementary solutions:1. Tokenization, rad/path correlation2. Path and Rad data curation solutions3. Surgical Video solutions providers/consultants4. LLMs or other solutions for metadata extraction, with mapping to standard ontology(ies), for Rad/Path Reports, also EHR/EMR, Epic, Cerner, RIS, etc.5. Advanced Search solutions – vectorization, agentic, RAG approaches, etc.6. Senior executive level Business Plan development/review | TA2: System architecture design and implementation |
| Patricia Saavedra | Inen | pjsaavedras@gmail.com | PERU | NUCLEAR MEDICINE, PET | IMPROVE REPORTS | TA2: System architecture design and implementation |
| Micah Sheller | Intel Corporation | micah.j.sheller@intel.com | Hillsboro, OR | Confidential and secure federated AI, trusted execution, governance for data and AI consortia, governance for multi-party compute using secure processors, trusted execution (our lab invented Intel SGX). | TA3, TA1 (though we do have some bizdev resources), Data System (2.2.2.5) excluding Federated Learning Capabilities (2.2.2.5.9.6) | TA2: System architecture design and implementation |
| Prashant Shah | Intel Corporation | prashant.shah@Intel.com | Portland, OR | Confidential and secure federated AI, trusted execution, governance for data and AI consortia, governance for multi-party compute using secure processors, trusted execution (our lab invented Intel SGX). | TA3, TA1 (though we do have some bizdev resources), Data System (2.2.2.5) EXCLUDING Federated Learning Capabilities (2.2.2.5.9.6) | TA2: System architecture design and implementation |
| Maria Gaboury | InterSystems | Maria.Gaboury@intersystems.com | Vienna, VA | Data Integration and Interoperability, AI | Implementation partner | TA2: System architecture design and implementation |
| Preetham Bachina | Johns Hopkins University | pbachin1@jh.edu | Baltimore, MD | Our interdisciplinary team at Johns Hopkins University operates at the nexus of advanced clinical practice and engineering innovation. We focus on leveraging machine learning to tackle key diagnostic and clinical challenges in neurology, radiology, pathology, and surgery. With expertise in image data analysis, data encryption, and federated learning, we utilize JHU’s extensive datasets to drive advancements in these critical areas. | We are seeking industry partners with expertise in platform commercialization and integration to support the deployment and scalability of our solutions. While we bring a strong foundation in machine learning and decentralized systems, we aim to collaborate with partners who bring practical experience in data management and deployment strategies. Additionally, we are looking for academic partners with access to diverse datasets to enhance the robustness and generalizability of the platform. | TA3: Enrollment, TA2: System architecture design and implementation, TA1: Business model and business plan |
| Muyinatu Bell | Johns Hopkins University | mledijubell@jhu.edu | Baltimore, MD | Ultrasound and photoacoustic imaging | Deployment of rapid overfitting assessment methods for deep neural networks; regulatory strategies; business models | TA3: Enrollment |
| Shaun Kahler | KBI Data | shaun.kahler@gmail.com | Knoxville, TN | KBI Data specializes in Python and SQL-based data analytics for healthcare applications. Our work primarily involves the ETL, data architecture, optimization, and visualization of healthcare data, as well as creating optimal baseline data models for AI-based solutions. | We are looking for partners who seek expertise in the fields of data management and analytics. | TA2: System architecture design and implementation, TA1: Business model and business plan |
| Jeffrey Baumes | Kitware Inc. | jeff.baumes@kitware.com | Clifton Park, NY | Kitware is a software company with experience in WSI, radiology, and surgical video analysis and visualization, as well as deidentification, AI workflows, cloud systems, and MLOps. HistomicsTK, our open-source WSI solution, is used in labs and pharma companies. Our open-source video viewer and annotator DIVE has been utilized in surgical applications. We also pioneered solutions in radiology image analysis and visualization with tools like 3D Slicer, VolView, and ITK. | Ideally we would partner with a team that would organize the overall business model and requires additional software expertise for analyzing and visualizing WSI, radiology, and video, and/or running ML pipelines. | TA2: System architecture design and implementation |
| C.S. Park, PhD/MS | Kyral Health | 4pplic4t10n5+ARPAH@kyralhealth.com | Chicago/ New York/ SF/ Seattle, IL | Kyral Health provides patient-centered interoperability architecture where patients serve as the system-of-record or EHR system - critical for future-facing, real-time continuous wearable data and transfer or sharing of large imaging and personal health data. Our privacy-preserving decentralized system provides self-sovereign data ownership and control, data portability, and chain of custody. It also enables differential privacy and federated learning across siloed databases and IT systems. | We are primarily seeking TA3 partners or stakeholders who are already engaged with or who have access to the medical imaging community and imaging data as described in the TA3 Enrollment description. Working with partners and with real imaging data from data providers and service providers is essential to build any architecture for the an entirely new imaging data exchange platform as envisioned by INDEX - it is fundamental to Design Thinking principles. | TA2: System architecture design and implementation |
| Bijal Mehta | LA County Harbor-UCLA Medical Center and the Lundquist Institute | bmehta@lundquist.org | Los Angeles, CA | Execution of a MRI dice based cryptocurrency/NFT exchange platform with blockchain based reverse tracking | 1. Able to execute Dicom to NFT/crytocurrency platform 2. Able to formulate an independent invite only based cryptocurrency based exchange 3. AI/ML based knowledge of computer vision to analyze imaging data and blockchain/hash function to encryption models 4. | TA1: Business model and business plan, TA2: System architecture design and implementation, TA3: Enrollment |
| Bryan Rushton | LHP Analytics & IoT | bryan.rushton@lhpes.com | Columbus, IN | We research, partner, and deliver on advanced digital solutions to optimize medical data management, improve patient care, and enhance healthcare operations. Specializing in data analytics, secure data integration, and predictive analytics, we create custom, scalable, user-ready solutions for measurable outcomes in the medical field. | -Medical/Industry SMEs -Business/Managerial Partnerships -SAAS or packaged solution providers needing integration/customization as it relates to the scope. -Academic Partners needing practical implementation and integration and/or production-capable architecture design. | TA1: Business model and business plan |
| Rajiv Gupta | Massachusetts General Hospital and Harvard Medical School | rgupta1@mgh.harvard.edu | Boston, MA | Mass General Brigham (MGB) – consists of 16 institutions that include world-renowned medical centers and top-ranked specialty hospitals – it is an integrated academic healthcare system founded by Massachusetts General Hospital and Brigham and Women's Hospital—two of America's leading academic medical centers and Harvard Medical School's largest teaching hospitals. The MGB Dept of Radiology is developing a cohort creation and distributed learning system. | Potential partnerships are sought with teams specializing in business plans for distributed use of data and with other hospital systems interested in contributing radiology data. | TA3: Enrollment |
| Eugene Koay | MD Anderson Cancer Center | ekoay@mdanderson.org | Houston, TX | We lead a national consortium to develop a pre-diagnostic imaging repository for pancreatic cancer. This involves multiple high volume and well recognized academic centers from around the USA. Our institution also has a large imaging archive of annotated patient datasets for pancreatic cancer as well as many other cancer types. | We would hope to contribute to an imaging archive effort and have access to the larger dataset to develop, train, and validate new imaging algorithms. | TA3: Enrollment |
| Shawn Vanseth | MedAcuity | svanseth@medacuity.com | Westford, MA, MA | Software engineering solutions for the medical device industry. Supporting countless architectural designs and implementations for complex AI/ML driven medical imaging solutions. | We have formal partnerships with companies such as Real Time Innovation (RTI) and Sima AI but we are a software company. Potential need for imaging companies with data sets for proof of concept. Potential need for hardware/electrical partnerships may be needed. | TA1: Business model and business plan |
| Nathan Opitz | Medicom | nopitz@medicom.us | Raleigh, NC | Facilitate Medical image exchange between organizations and bridge the gap in RWD by curating large scale de-identification data cohorts for data consumers. | Will know more at a later time | TA2: System architecture design and implementation |
| Kyle Kearney | Medicom Technologies, Inc. | kkearney@medicom.us | Raleigh, NC | Medicom created the first federated health information network: a powerful platform that connects disparate data silos through a single interface. The value of a HIN is dependent on the willing participation of providers, hospitals, and imaging centers in a community. Utilizing similar technology building blocks to our HIN tool, the Medicom Intellect platform enables the ability to collect and de-identify longitudinal health information related to patient imaging data. | Healthcare entities, including academia sites, not on the Medicom network, to participate and provide appropriate patient imaging/health information datasets to further real-world purposes. | TA1: Business model and business plan |
| Madhu Nair | Mendon Group | mrnrochester@yahoo.com | Rochester, NY | Small Business Innovations Research - Medical Software for coordinated care and surveillance systems | Technical expertise related to imagining and AI | TA1: Business model and business plan |
| Paul Kinahan | MIDRC | kinahan@uw.edu | Chicago (Prime site), IL | The Medical Imaging & Data Resource Center (MIDRC) Data Commons supports the management, analysis and sharing of medical imaging data for the development of algorithms to improve workflows and patient outcomes. The data in MIDRC are open access to foster machine learning innovation through tool and data sharing. In addition to imaging files, there are patient demographic data, test results and other clinical data, harmonized study descriptions utilizing the LOINC playbook, and image DICOM tags. | MIDRC is looking for partners in several areas, including TA1 (business model and plan), methods for annotations, and others. | TA2: System architecture design and implementation |
| Abhishek Singh | MIT | abhi24@media.mit.edu | Boston, MA | Our lab specializes in decentralized machine learning, enabling access to data and models without centralizing data or computation. We’ve introduced novel ideas like data markets, the Posthoc Privacy Framework, and Split Learning—a resource-efficient alternative to Federated Learning. We published papers, benchmarks, and open-source tools in this domain. | We have a strong background in machine learning, decentralized systems and are looking for partners who have expertise and experience from deployment and data point of view. | TA3: Enrollment |
| Alexandros Karargyris | MLCommons | alex@mlcommons.org | San Francisco, CA | MLCommons is a community-driven and member-funded organization with Members and Affiliates from across the globe. In collaboration with our 125+ global technology providers, academics, and researcher members, we collaboratively build tools for the entire AI industry through benchmarks, benchmark best practices, public datasets, and measurements for AI risk and reliability. We believe that our organization is well positioned to support this ambitious project technically. | As an engineering organization we are looking into collaborating with teams that have complementary expertise such as healthcare data providers, clinical experts, healthcare business experts to help address TA1 and TA3. While our expertise can be utilized in TA2 we expect to work with stakeholders in this space as well. | TA2: System architecture design and implementation, TA1: Business model and business plan, TA3: Enrollment |
| Alonzo Sexton | nCight | asexton@ncight.com | Atlanta, GA | We are focused on business model development and validation of product market fit for the creation of a sustainable model for data sharing across health organizations. | We provide raw resources of Subject Matter Expertise and diverse high quality data sources. We are looking for teammates that can assist on the non clinical side and have expertise in AI/ ML particularly as it relates to computer vision. | TA3: Enrollment |
| Han Liu | Northwestern University | hanliu@northwestern.edu | Evanston, IL | AI, large foundation models, multi-modality language models, universal simulator, universal forecaster | TBD | TA1: Business model and business plan |
| Mitchell Goldburgh | NTT DATA | mitchell.goldburgh@nttdata.com | Plano, Texas, TX | NTT DATA has a program of creating clinical research networks and ML/OPS plaform to develop and validate AI against data sets using imaging in radiology, oncology and pathology. As a systems integrator we have strong background in platform management. | Looking for partners for enrollment, and innovative system architectures where our scale could add benefits | TA2: System architecture design and implementation, TA1: Business model and business plan, TA3: Enrollment |
| Korak Sarkar | Ochsner Medical System, Veterans Affairs | korak.sarkar@ochsner.org | New Orleans, LA | Advanced Visualization of Medical Imaging | Compliance and Regulatory expertise | TA3: Enrollment |
| Brian Santucci | Omni Federal | brian.santucci@omnifederal.com | Atlanta, GA | Metadata management | Clinical expertise | TA1: Business model and business plan |
| Nathan Crilly | Oregon National Primate Research Center | crillyn@ohsu.edu | Portland, OR | The Oregon National Primate Research Center hosts a vast pathology database containing tens of thousands of samples which represent diverse pathologies relevant to human disease. Our veterinary pathology unit employs cutting-edge tools, including whole-slide imaging and HALO image analysis, to enhance diagnostic precision and rigor in animal models of human diseases. We focus on building digital pathology pipelines to improve biomedical research outcomes. | We seek partners with expertise and resources that complement our veterinary pathology capabilities and extensive sample database. We value collaborators skilled in computational techniques, including AI/ML development and data standardization, to enhance our pathology evaluation and interpretation. Additionally, partners with regulatory expertise and experience in data security, particularly in cloud environments, will be essential for ensuring compliance and protecting data privacy. | TA2: System architecture design and implementation |
| Thomas Loehfelm | PANORAD, LLC | thomas.loehfelm@panorad.io | San Diego, CA | We analyze radiology and pathology plain text reports to identify relevant radiology-pathology correlations. Our commercial software product, PATHFINDER, receives and processes HL7 messages, extracting patient and exam metadata and the full-text reports, which are then processed using a variety of open-source and proprietary tools. The resulting data annotations include structured data and SNOMED concept annotations useful for exam indexing and rad-path correlation. | We are looking to be a technical component to a more comprehensive proposal. Our reports processing platform is a necessary but incomplete component of a successful INDEX proposal. With funding from this proposal we can support installing our software at pertinent clinical sites and develop it in to a gateway component to retrieve and meaningfully annotate clinical exams prior to ingestion and submission to a central INDEX repository. | TA2: System architecture design and implementation, TA1: Business model and business plan |
| David Lee | PathCision Medicine, Inc. | david.lee@pathcisionmedicine.com | Watertown, MA | Our main expertise is anatomic pathology, its upstream workflows, and the downstream needs of industry clients. Our multidisciplinary team includes: 1) an anatomic pathologist with pharma experience, skilled in computational pathology for drug discovery and clinical trial; 2) a histopathology expert with experience in staining (H&E, IHC, special stains), digitization, and the impact of processes and hardware on image output; 3) an ML expert with experience training high-dimensional images. | We seek to collaborate with primes in TA1, TA2 (ML-focused), and TA3 who need to bolster their diagnostic pathology expertise, particularly in understanding how images are used in industry settings and managing image variation. Ideal partners have larger ML teams, as our in-house ML and computational pathology experts can bridge pathology with broader INDEX objectives. | TA2: System architecture design and implementation |
| RAJENDRA SINGH | PathPresenter Corporation | raj@pathpresenter.com | na, NJ | digital pathology | surgical video | TA2: System architecture design and implementation |
| Christopher Stice | Philips NA | Christopher.Stice@philips.com | NA, WA | HIE, Data Standardization | Small , large or socioeconomic | TA2: System architecture design and implementation |
| William Kessler | Physical Sciences Inc. | kessler@psicorp.com | Andover, MA | Physical Sciences Inc (PSI) develops medical imaging technologies, including ophthalmic imagers and multimodal microscopy imagers. PSI ophthalmic imagers provide clinicians with advanced tools for imaging human and small animal eyes enabling early detection of glaucoma, macular degeneration and other eye diseases. PSI microscopy instrumentation is used to diagnose cancer and assess patient trauma such as skin burns. PSI imagers classify tissue types supporting clinical translation. | Organizations with expertise in system architecture design and implementation to operate the system architecture and protocols for the INDEX platform. | TA1: Business model and business plan |
| John Sadowski | Planned Systems International | Jsadowski@atlintl.com | Washington, DC | Planned Systems International (PSI) is a global IT solutions provider specializing in Federal Health IT. PSI has developed and enhanced the U.S. Military Health System Data Repository which integrates patient data from DoD hospitals and associated health clinics across the world. PSI is also the enterprise test agent for the VA and supports the refinement of VA Enterprise Architecture on multiple contracts. | We are looking to partner with subject-matter experts from the medical imaging community. | TA1: Business model and business plan |
| Shelley Zhang | PSI | hzhang@psicorp.com | Andover, MA | optical imaging of various disease | potential partner to be in the field of robotic endoscope surgery | TA1: Business model and business plan |
| Ana Blanco | Quibim | anablanco@quibim.com | New York, NY | Quibim offers QP-Insights, a cloud-based platform designed for managing, storing, and analyzing multi-omics data with a radiologic image-centric approach (MRI, CT, PET...). It features automated pseudonymization, quality check, eCRF interoperability, zero footprint DICOM viewer, AI-driven harmonization, organ/lesion segmentation and predictive tools. It supports 9 cancer registries, including EUCAIM, Europe's largest cancer imaging biobank, enabling federated learning across siloed databases. | Quibim is looking for partners with expertise in pathology and surgical video system architecture design and implementation, as well as data providers in these two categories. We value partners who bring strong technical expertise and a shared commitment to advance precision medicine. | TA2: System architecture design and implementation, TA1: Business model and business plan, TA3: Enrollment |
| Todd Hughes | Scientific Systems Company, Inc. | todd.hughes@ssci.com | Burlington, MA | Computer vision at scale, MLOps | Expertise in medical imaging | TA1: Business model and business plan |
| Martin Willemink | Segmed | martin@segmed.ai | Palo Alto, CA | Segmed developed the technology to ingest, de-identify, and standardize radiology imaging data, and make it searchable. All radiology modalities are supported. This technology is currently deployed within a data network that represents all 50 US states. 40 million studies have been processed and made available through our platform. More than 50 entities (med device, pharma, cloud providers, universities) are using this data network for research and FDA approvals (25+ FDA approvals). | We are looking for collaborators with similar technologies and networks in pathology and surgical videos. | TA2: System architecture design and implementation |
| Martin Willemink | Segmed | martin@segmed.ai | Palo Alto, CA | Segmed has developed the technology that allows for medical image data ingestion, de-identification, standardization, and searchability. | We're looking to partner with more health systems | TA1: Business model and business plan |
| Simona Temereanca Ibanescu | Soar Technology, LLC | simona.temereanca@soartech.com | N/A, MI | SoarTech creates AI solutions that collaborate with humans to improve information processing and understanding. Our research focuses on data curation, structuring, analysis, visualization, and dissemination, rooted in our expertise in human information processing and decision-making. Originally applied in defense, we are adapting these capabilities, and our expertise in developing explainable and trustworthy AI/ML solutions, to research solutions to national healthcare challenges. | (1) Expertise in designing and implementing federated systems at scale; (2) Domain expertise in medical imaging modalities, including data standardization, harmonization, and integration (3) Expertise integrating cost-effective storage, compute resources, and cloud solutions to optimize storage and processing of large-scale medical imaging datasets; and, (4) Expertise in creating robust financial management and monetization systems, including transaction processing, pricing models, and account-b | TA2: System architecture design and implementation |
| Esther Abels | SolarisRTC LLC | Esther.abels@solarisrtc.com | Silver Spring, MD | research focuses on integrating AI/ML into E2E solutions using regulatory science and clinical affairs to develop regulatory pathways for SaMD/IVD. Emphasis is on quality assurance and reliable accurate data incl RWE from underserved areas, ensuring regulatory compliance while integrating datasets for training algorithms, identifying drug targets, and predicting treatment responses. Leveraging expertise in regulatory, clinical, quality, reimbursement, IVD, pharma we drive equitable innovation. | ARPA-H INDEX partners should specialize in data generation and advanced AI/ML modeling. Academic institutions or healthcare providers in underserved areas can provide diverse datasets aligned with regulatory needs. AI/ML developers should focus on algorithm optimization using compliant datasets. A tech firm with federated data management capabilities can ensure secure integration. Together, this synergy will drive impactful and equitable innovation across sectors, fostering advancements | TA2: System architecture design and implementation |
| Milver Valenzuela | Solid Logix LLC | milver.valenzuela@solidlogix.com | Atlanta, GA | Solid Logix specializes in scalable system architecture, high-performance computing, secure cloud-native solutions, with extensive experience supporting science-based federal initiatives (e.g., CMS, CDC). | Solid Logix seeks to support teams with strong expertise in TA1 (business models) and TA3 (participant enrollment), while looking to strengthen capabilities in TA2 (system architecture). | TA1: Business model and business plan |
| Daniel Donoho | Surgical Data Science Collective | dan@surgicalvideo.io | Washington, DC, DC | The Surgical Data Science Collective operates a secure platform for medical imaging data exchange, machine learning operations, and extraction of clinically relevant insights. Our focus is surgical video - all data types are supported. Our infrastructure allows machine learning model training, deployment, post-deployment model monitoring, and automated model improvement across the largest central repository of video data. We are trusted by over 200 surgeons and institutions on 5 continents. | As a key trusted partner of data holders, we offer a mature technical infrastructure optimized for video and the ability to assemble data at scale. We are looking for teaming parters to help lead TA1, collaborate on TA2, and advise on TA3. The ideal teaming partner will have demonstrated track record of a high-trust, mature approach to this area. | TA2: System architecture design and implementation |
| Sameer Peesapati | Synthesize | sameer@synthesize.health | Boston, MA | We are a medical technology and health AI commercialization firm that focuses on increase in adoption of clinical AI tools specifically in Imaging and EHR to improve health and treatment outcomes for patient. Our expertise as usability, regulatory, and reimbursement led to several AI-enabled devices to be introduced in the US and contributed towards their reimbursement and revenue generation. | We are looking to partner with teams performing system architecture design and implementation to offer our expertise in business planning, enrollment and also contribute towards system architecture design. We are connected with multiple large health systems i.e. data providers, and hundreds of startups and innovation organizations - data consumers developing AI algorithms to integrate RSTks into their design process effectively. Our team has regulatory and quality experts in devices and AI DSTs. | TA3: Enrollment |
| Raghu Machiraju | The Ohio State University | machiraju.1@osu.edu | Columbus, Ohio, OH | AI foundation models, data workflows, and large data repositories. | user community, privacy, high-performance computing | TA3: Enrollment |
| Adam Flanders | Thomas Jefferson University (MIDRC) | adam.flanders@jefferson.edu | Philadelphia, PA | MIDRC/RSNA. Federated medical image data discovery, cohort building, de-identification, pre-labeling and annotations. | Capability to support diverse clinical use-cases and unique methods for data discovery and exchange. | TA2: System architecture design and implementation |
| Eric Buckland | Translational Imaging innovations | eric@tiinnovations.com | Hickory, NC | Translational Imaging Innovations (TII) drives precision ocular biomarker discovery with ocuTrack®, a scalable platform for data sharing, workflow management, and modular AI-enabled image and data analysis. By addressing critical gaps in imaging diversity, traceability, and reproducibility, TII aligns with ARPA-H INDEX goals to accelerate AI development, enhance regulatory validation, and support equitable, FAIR-compliant clinical outcomes. | We seek partners to enhance ocuTrack’s capabilities, including data providers (hospitals, biobanks) to ensure diverse, high-quality datasets; AI/ML experts to co-develop modular AI tools and FAIR compliance; and end-user organizations like CROs and pharma to validate usability and drive adoption. Additionally, we prioritize advocacy groups to align with health equity goals, ensuring patient-centered solutions that address ARPA-H’s objectives for robust, transparent AI in medical imaging. | TA1: Business model and business plan |
| Vrad Levering | Triple Ring Technologies | vlevering@tripleringtech.com | Newark, CA | Triple Ring Technologies is a leading partner in developing medical imaging products, driven by AI. Our interdisciplinary team, including PhDs and industry experts, excels at academic collaborations to advance technologies up the TRL scale and to market. We offer software development services with experience working with medical imaging data, including AI pipelines and AWS cloud infrastructure. Additionally, we created simulation tools for generating configurable synthetic X-ray and CT datasets. | We are looking to be a subcontractor to an academic or commercial partner that has experience designing distributed exchange systems. We have a strong track record of proposal writing and program management, and have previously engaged with ARPA-H as a subcontractor. | TA1: Business model and business plan |
| Margaret Wenzlau | Truveta | margaretw@truveta.com | Seattle, WA | Truveta is a collective of 30 health systems providing multi-modal clinical data for over 120M patients. Data are representative of inpatient and outpatient care across the US, and are updated daily from members, cleaned with clinical expert-led AI, and de-identified with industry-leading privacy and security technology. Images are integrated longitudinally with additional clinical data such as EHR data, claims, mortality, clinical notes and reports, and SDoH. | We are looking for teaming partners seeking imaging data providers. Truveta has research ready imaging data from 30 member health systems integrated longitudinally with clinical, claims, mortality data. | TA3: Enrollment, TA3: Enrollment, TA2: System architecture design and implementation |
| Ciprian Ionita | University at Buffalo | cnionita@buffalo.edu | Buffalo, NY | Development and implementation of AI-driven predictive tools for clinical decision support in neurovascular interventions, focusing on real-time guidance, safety, and improved patient outcomes. | Collaborators with expertise in advanced imaging systems, clinical data management, regulatory compliance, and AI deployment in healthcare settings to support end-to-end clinical trial execution. | TA1: Business model and business plan |
| Sheng Xu | University of California San Diego | shengxu@eng.ucsd.edu | San Diego, CA, CA | Develop wearable ultrasound imaging technology. | TA 1 and TA 2. | TA2: System architecture design and implementation |
| Ravi Madduri | University of Chicago and Argonne National Laboratory | madduri@uchicago.edu | Chicago, IL | Privacy Preserving Federated Learning frameworks, services that implement continuous learning to measure model drifts. Additional capabilities include measure AI Readiness of datasets to provide a window to explaining model performance. | TA1, TA3 | TA1: Business model and business plan |
| Kuang Gong | University of Florida | kgong@ufl.edu | Gainesville, FL | My group's expertise is in medical image analysis, synthetic image generation, medical image harmonization, AI algorithm development, and medical physics. | Open | TA3: Enrollment |
| Patrick Mendez, PhD | University of Maryland | Pmendez1@umd.edu | College Park, MD | Open | Open | TA3: Enrollment |
| Sanjay Purushotham | University of Maryland Baltimore County | psanjay@umbc.edu | Baltimore, MD | We specialize in AI, Machine Learning, and Federated Learning, with a particular focus on healthcare and the medical domain. Our current research spans areas such as Multimodal Generative AI (including Multimodal Large Language Models), Medical Image and Video Visual Question Answering, Explainable AI, Interpretable ML, Synthetic Data Generation, privacy-preserving methods, Medical Time Series and Time-to-Event Analysis, and Machine Learning reproducibility and benchmarking. | We are looking to collaborate with clinical experts, healthcare organizations, and health/medical science domain specialists. Specifically, we seek partnerships with clinicians, medical organizations, and health exchange providers who can bring invaluable expertise and resources to help advance our healthcare initiatives. | TA2: System architecture design and implementation, TA1: Business model and business plan, TA3: Enrollment |
| Lin Ma | University of Michigan | linmacse@umich.edu | Ann Arbor, MI | Our team focuses on large-scale data management and data processing. Our primary expertise is in relational (SQL) database management systems. We also have experience in open format and semi-structured data management. Our team has been working on AI/ML-based techniques that enhance the simplicity and efficiency of data management. | Looking to join a team interested in submitting the INDEX proposal, where we can contribute our expertise in data management. | TA1: Business model and business plan |
| Z. Morley Mao | University of Michigan | zmao@umich.edu | Ann Arbor, MI | We are interested in the systems support for such an infrastructure to provide security and privacy guarantees to enable applications in healthcare. | Interested in concrete use cases for using this infrastructure. | TA1: Business model and business plan |
| Mai-Lan Ho | University of Missouri | mailanho@gmail.com | Columbia, MO | Quantitative advanced imaging Imaging genomics and precision theranostics Multicenter informatics infrastructure Multimodal AI for health care | Diverse multimodal datasets Streamlined collaborative network Multicenter use cases | TA3: Enrollment |
| Regent Lee | University of Oxford | Regent.lee@nds.ox.ac.uk | Oxford, United Kingdom | I lead the AICT Consortium (www.aict.ai), which is managed through University of Oxford, UK. The consortium consists of a trandisciplinary partnership of academia, healthcare and industry. We have hospital footprints across three continents and 10 hospitals. AICT Consortium has been established to address the pressing need of high quality CT imaging data to develop and refine AI tool for CT Imaging. We are funded by Horizon Europe and are on track to amass / curate 100 million CT scans in 2025. | clinical organisations to enroll in the expanded consortium. | TA1: Business model and business plan |
| Walter Witschey | University of Pennsylvania | witschey@pennmedicine.upenn.edu | Philadelphia, PA | AI in Medicine | medical imaging, foundational models, artificial intelligence, integration | TA2: System architecture design and implementation |
| Bob Nishikawa | University of Pittsburgh | rmn29@pitt.edu | Pittsburgh., PA | We are interested in improving breast cancer care for patients. Our approach is to leverage the vast amounts of data that clinics and hospitals have in the form electronic records. Our breast cancer data mart contains medical records from radiology (including all images related to breast cancer care), pathology, medical and radiation oncology, surgery, and genetics, all coupled to the hospital's cancer registry. We have data from more than 500,000 women; se are still collecting the images. | We are looking for other organizations that have a breast cancer data mart and would like to form a consortium. | TA2: System architecture design and implementation |
| Valerio Pascucci | University of Utah | pascucci@sci.utah.edu | Salt Lake City, UT | Development of scalable (parallel and distributed) computing solution for training on large models across cloud federations | Primarily looking for data providers for TA1 and TA3. For TA2 we are also looking for groups with solutions for solutions/produts on data harmonization (color of the images) and data deduplication. | TA2: System architecture design and implementation |
| Beatrice Knudsen | University of Utah | Beatrice.Knudsen@path.utah.edu | Multiple sites including Tampan, Salt Lake City and Columbus/Ohio, UT | We are a network of academic investigators from 19 Medical Centers across the US that was founded in 2006. The network, under the name of Aster Insights is expanding its procurement of pathology and radiology images under a unified consent and data sharing agreement. | The main strengths of the network is in TA1 and TA3. We are looking for partners across TA1, TA2 and TA3 to complement our approach. | TA1: Business model and business plan |
| Kevin Matthew Byrd | Virginia Commonwealth University | byrdk6@vcu.edu | Richmond, VA | Our organization focuses on understanding the cellular and molecular mechanisms underlying upper airway and craniofacial biology, cancer, and chronic inflammation. We integrate advanced single-cell and spatial multiomics, bioinformatics, and microbiomics to investigate tissue repair, immune regulation, and disease mechanisms. Our goal is to bridge upper airway biology, cancer research, and health disparities to drive innovation in precision medicine and tissue regeneration. | We seek teaming partners with complementary expertise in computational biology, bioinformatics, tissue engineering, and spatial multiomics. Ideal collaborators bring unique technologies, datasets, or clinical expertise to advance our understanding of upper airway and craniofacial biology, cancer, and chronic inflammation. We value partners committed to innovation, precision medicine, and addressing health disparities through collaborative, multidisciplinary approaches. | TA3: Enrollment |
| Mehdi Hedjazi Moghari | West Virginia University | mehdi.hedjazimoghari@hsc.wvu.edu | Morgantown, WV | Artificial Intelligence in Medical Imaging: Automated Analysis and Report Writing for Cardiovascular Magnetic Resonance Imaging in Patients with Congenital Heart Disease for Accurate and Enhanced Clinical Workflow | We are looking for institutions (e.g., children's hospitals in the U.S. and Europe) interested in sharing medical images to help develop an AI-based automatic analysis and report-writing algorithm. | TA3: Enrollment |
| Adam Saunders | xBiologix | adamsaunders.dbq@gmail.com | Corvallis, OR | xBiologix develops patented synthetic biology tools that democratize spatial biology for cancer diagnostics and research. Our technology enables accurate analysis of the tumor microenvironment using standard microscopy equipment, eliminating the need for expensive specialized instruments and complex sample handling. By simplifying the spatial biology workflow, we can help physicians make faster, more precise treatment decisions, reducing time lost on ineffective therapies. | We are seeking to partner with organizations involved with cancer diagnostics, spatial biology, or biomarker detection, including: The National Cancer Institute (NCI) lab network AI companies working on digital pathology Pharmaceutical/Biotech companies Spatial biology platform companies Oncology clinics & hospitals | TA1: Business model and business plan |
| Bijan Tadayon | Z Advanced Computing Inc | bijantadayon@zadvancedcomputing.com | Potomac, MD, USA, MD | Technology: ZAC has developed and demonstrated disruptive technologies for recognizing and searching 3D objects and their details from any view direction in images and videos, with: • higher accuracy (more robust/ reproducible), • using only a few training samples (typically less than 50), instead of 1000s or Millions or Billions & • much less computation resources (CPU/ GPU) & energy to run. We are the only company in the world that can train our AI machine with a few training samples. | As far as we know, we are the only company in the world that can train our AI machine with a few training samples (typically 5 to 50), based on the Concept Learning algorithms. Tractions: • Awarded & successfully completed 3 SBIR Phase II contracts ($ 2.8 M) by US Air Force for Aerial Vision (2019-2024). More funding is coming from USAF, for Phase 3. • ZAC core Cognitive Explainable-AI tech (for Smart Appliances) with BSH/ Bosch. | TA1: Business model and business plan |
| Záda Beasley | ZataData®️ | hello@zatadata.world | Hanover, MD | ZataData's research within the ARPA-H INDEX program focuses on advancing medical imaging through AI. AI-powered image analysis: Developing algorithms for automated image interpretation, including anomaly detection and segmentation. Data standardization: Creating tools to standardize and harmonize diverse medical imaging datasets across institutions. Cloud-based platforms: Developing secure, scalable platforms for image sharing and analysis. Image enhancements and acceleration | An ideal ARPA-H INDEX partner would possess complementary expertise. A leading university with a renowned radiology department (e.g., Johns Hopkins) could provide access to de-identified patient data and clinical expertise. This collaboration would enable ZataData to leverage cutting-edge research and accelerate the development of AI-powered solutions for medical imaging. | TA1: Business model and business plan |