{"id":1437,"date":"2021-01-25T13:52:08","date_gmt":"2021-01-25T18:52:08","guid":{"rendered":"https:\/\/geiselmed.dartmouth.edu\/radiology\/?page_id=1437"},"modified":"2026-06-09T17:06:50","modified_gmt":"2026-06-09T21:06:50","slug":"pressman-fellowship","status":"publish","type":"page","link":"https:\/\/geiselmed.dartmouth.edu\/radiology\/medical-students\/pressman-fellowship\/","title":{"rendered":"Samuel D. Pressman Fellowship"},"content":{"rendered":"

<\/p>\n

Fellowship in Medical Imaging, Precision Health, and Artificial Intelligence<\/h2>\n

Background<\/b>
\nThe Samuel D. Pressman Fellowship in the Department of Radiology at Dartmouth Health (DH), the Geisel School of Medicine, and the Center for Precision Health and Artificial Intelligence (CPHAI) will enable MD, MS, MPH, and PhD students at Geisel to engage in innovative and emerging areas of research at the intersection between medical imaging, artificial intelligence, and precision health.<\/p>\n

Finances<\/b>
\n$6,000.00 funded by the Samuel D. Pressman Fund will be provided to the successful candidate for pursing a research project that meets the criteria set forth above. This project would be expected to span a 10-week period over the Summer of 2026.<\/p>\n

Objectives<\/b>
\nOver the 10 weeks beginning on June 15, 2026 until August 26, 2026, the student will develop skills in performing and presenting research and writing manuscripts involving medical imaging data and artificial intelligence, resulting in one or more publications or presentations.<\/p>\n

Structure<\/b>
\nThe Fellowship consists of a number of components:<\/p>\n

    \n
  1. Mentorship: A successful candidate will have identified faculty mentors from both the Department of Radiology and from CPHAI.\n
  2. Collaboration: Candidates whose research involves application of imaging data to clinical questions outside of radiology will also have a faculty mentor from an appropriate clinical department at DH, thereby promoting research collaboration between the Department of Radiology, CPHAI, and other DH departments.\n
  3. Presentation and publication: The successful candidate will submit a report of their research findings to the Pressman Fellowship committee at the completion of their summer internship on or before August 26, 2026. This candidate will also present their research findings at jointly-hosted Radiology and CPHAI Grand Rounds. Ideally, this candidate will also publish their findings in a peer-reviewed journal.\n<\/ol>\n

    Evaluation:<\/b><\/p>\n

      \n
    1. Formal evaluation by project supervisors\n
    2. Success in presentation and\/or paper submissions\n
    3. Evaluation of research presentation\n<\/ol>\n

      Application<\/b>
      \nThis will be a competitive application. The applications will be assessed and awarded by the Pressman Fellowship Committee.
      \nStudents interested in applying should send the following materials by January 16, 2026 <\/b>to the following email address: pressman.fellowship.radiology@hitchcock.org<\/a>
      \nPlease include the following materials in the application packet:<\/p>\n

        \n
      1. Specific Aims (0.5 page maximum)<\/li>\n
      2. Research proposal (1.5 page maximum)
        The proposal should include a list of the applicant\u2019s CPHAI, radiology, and if applicable, non-radiology DH faculty mentors with their email contact information, which will be used to confirm the faculty member\u2019s support for the proposed research project.<\/li>\n
      3. Current CV<\/li>\n
      4. Current transcript for the applicant\u2019s Geisel degree program.<\/li>\n<\/ol>\n

        Student applicants will be informed of the Fellowship award by March 16, 2026.<\/b>
        \nFor any questions or additional details, please contact         Dr. Jessica Sin<\/a> (jessica.m.sin@hitchcock.org).<\/p>\n

        Pressman Summer Fellow 2026<\/h3>\n

        \"\"<\/p>

        Jillian Melbourne<\/h3>\n

        MS Biomedical Data Science (Expected 2027), Geisel School of Medicine<\/b><\/p>\n

        Project<\/b>
        \nMultimodal Radiology\u2013Pathology Integration for Breast Cancer Recurrence Risk Prediction<\/p>\n

        Mentors<\/b>
        \nDr. Saeed Hassanpour, PhD, Founding Director of Dartmouth Center for Precision Health & Artificial Intelligence, Professor in the Departments of Biomedical Data Science, Computer Science, and Epidemiology
        \nDr. Roberta diFlorio-Alexander, MD, MS, Associate Professor in the Departments of Radiology and Obstetrics and Gynecology
        \nDr. Jonathan Marotti, MD, Associate Professor in the Department of Pathology and Laboratory Medicine<\/p>\n

        Bio<\/b>
        \nShortly after graduating from UCLA with a BS in neuroscience, I became interested in leveraging data for patient-specific care while working as a research assistant at Stanford University on personalized, adaptive deep brain stimulation algorithms for Parkinson's disease. Now as a first-year Health Data Science master's student at Dartmouth College and Program Manager at Stanford University, my research focuses on novel statistical approaches for personalized prediction using medical imaging and wearable sensor data, with a particular emphasis on health equity and understudied populations. Through the Pressman Fellowship, I am excited to develop multi-modal strategies integrating radiology and pathology data for breast cancer recurrence risk prediction. Following my master's degree, I plan to pursue a PhD in biomedical data science to advance computational methods that enable individualized clinical decision-making for underserved populations.<\/p>\n<\/div><\/div>

        <\/div>
        <\/div><\/div>\n

        Pressman Fellows 2025-26<\/h3>\n

        \"\"<\/p>

        Steven Angtuaco<\/h3>\n

        Geisel Class of 2028<\/b><\/p>\n

        Project<\/b>
        \nSeeing is Believing: Understanding Human-AI Interaction Patterns in Prostate Cancer Imaging with Eye-Tracking<\/p>\n

        Mentors<\/b>
        \nIndrani Bhattacharya, PhD, Biomedical Data Science, CPHAI
        \nJessica Sin, MD, PhD, Radiology, CPHAI
        \nMatthew Maeder, MD, Radiology
        \nJames Yu, MD, MHS, Radiation Oncology
        \nMarc Seltzer, MD, Nuclear Medicine
        \nLawrence Dagrosa, MD, Urology
        \nLillian Dominguez Konicki, MD, Radiology<\/p>\n

        Bio<\/b>
        \nBorn, raised, and working in rural Arkansas, I worked as a schoolteacher before rejoining the medical field this past year! If the last few years have taught me anything, it's that my academic interests in metagenomics & psychology could never have fully prepared me to be the only science teacher at an understaffed & underserved high school. Indeed, when our principal abruptly passed away from cancer, it fell to me and my premedical background to take the lead, hugging my students as we worked together to find meaning in chemotherapy and oncogenes. It reminded me of one of my Filipino family's sayings, \"When a good doctor enters a room, everyone should know that things will be okay.\"<\/p>\n

        My goal is to be a physician who cares for patients while teaching them to take care of themselves. Through the Pressman fellowship, I am excited to rekindle my interest in psychology by exploring how artificial intelligence shapes perception, trust, and decision- making in my current favorite field: radiology. If you share my passion for health equity, radiology (or radiation oncology), suicide awareness, or research, I would love to connect and collaborate.<\/p>\n<\/div><\/div>

        <\/div>

        \"\"<\/p>

        Erikson Nichols, MS, MMS<\/h3>\n

        Geisel Class of 2027<\/b><\/p>\n

        Project<\/b>
        \nClinical Reasoning in the Treatment of Pediatric Distal Radius Fractures: A Comparison of Generic vs. Retrieval Augmented Generated Large Language Models<\/p>\n

        Mentors<\/b>
        \nJessica Sin, MD, PhD, Radiology, CPHAI
        \nRameez Qudsi, MD, MPH, Orthopedics<\/p>\n

        Bio<\/b>
        \nAs a Division 1 baseball athlete, pianist and neuroscience major at Duke University, I developed an interest in the relationship between mind and body and completed a thesis within the Duke Human Performance Optimization Laboratory. After participating in several entrepreneurship accelerators to design a diagnostic tool to enhance pre-operative visualization of intracranial electrodes in epilepsy patients by combining 3D printing and augmented reality, I pursued graduate school at the Duke Fuqua School of Business and<\/p>\n

        Johns Hopkins Carey Business School to further understand the integration of health policy, technological innovation and strategic management in optimizing care delivery at the systems level. Prior to medical school, I worked as a research coordinator at the Johns Hopkins Transplant Oncology and Infectious Diseases Clinical Research Center and in the pediatrics department at the Hospital for Special Surgery. Since matriculating at the Geisel School of Medicine, I have been selected to the Albert Schweitzer Fellowship and Swigart Ethics Fellowship, served as the Chief Executive Officer of Medicine in Motion, served as co-president of the Orthopedic Surgery Interest Group and led an innovation project through the DALI engineering lab and Mass Gen MESH bio-design incubator.<\/p>\n<\/div><\/div>

        <\/div>

        \"\"<\/p>

        Jose Romero, MS<\/h3>\n

        Geisel Class of 2028<\/b><\/p>\n

        Project<\/b>
        \nAutomated Surgical Target Volumes for Enhanced Neck Dissection Planning in Head and Neck Squamous Cell Carcinoma<\/p>\n

        Mentors<\/b>
        \nIndrani Bhattacharya, PhD, Biomedical Data Science, CPHAI
        \nDavid Pastel, MD, Radiology
        \nJoseph Paydarfar, MD, Otolaryngology, Audiology, and Maxillofacial Surgery<\/p>\n

        Bio<\/b>
        \nI am a second-year medical student at the Geisel School of Medicine at Dartmouth. I earned a bachelor\u2019s degree in neuroscience from the University of Texas at Austin and a master\u2019s degree in medical science from the University of North Texas Health Science Center. My research focuses on developing artificial intelligence (AI)-enabled tools to generate precise surgical target volumes to guide neck dissections in patients with head and neck cancer, and to assess the clinical utility of these systems. Our team is working to integrate machine learning into clinical workflows to enhance surgical planning for head and neck cancer patients and improve patient outcomes.<\/p>\n<\/div><\/div>

        <\/div>
        <\/div><\/div>\n","protected":false},"excerpt":{"rendered":"

        Fellowship in Medical Imaging, Precision Health, and Artificial Intelligence Background The Samuel D. Pressman Fellowship in the Department of Radiology at Dartmouth Health (DH), the Geisel School of Medicine, and the Center for Precision Health and Artificial Intelligence (CPHAI) will enable MD, MS, MPH, and PhD students at Geisel to [\u2026] <\/p>\n

        <\/div>\n

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