Medicine
Showing 1-10 of 20 Results
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Alexander Isaac Salter
Postdoctoral Medical Fellow, Oncology
Fellow in Medicine - Med/HematologyBioI am a clinical fellow in medical oncology at Stanford University whose long-term goal is to become a translational physician-scientist who develops curative cellular immunotherapies for solid tumors. As a graduate student, I conducted the first comprehensive signaling analyses of therapeutically engineered T cells, demonstrating that signal strength, rather than quality, is a key determinant of T cell function and fate. These findings helped inform the design of next-generation cellular immunotherapies, some of which are now in clinical trials. I also co-led a collaboration with Dr. David Baker’s laboratory at the University of Washington to engineer synthetic protein “logic gates” enabling combinatorial antigen recognition with high precision, offering a potential path to more safely target solid tumors. My doctoral research resulted in 16 publications, including four prominent first-, co-first-, or second-author papers in high-impact journals, several reviews and textbook chapters, and recognition on the Forbes 30 Under 30 List.
At Stanford, I focus on translating cellular therapies for thoracic and genitourinary malignancies. Under the mentorship of Drs. Crystal Mackall and Allison Betof Warner, I am developing CAR T cells for lung cancer in non- and never-smokers and serve as a sub-investigator on an upcoming first-in-human phase 1 trial of drug-regulatable CAR T cells for adults with advanced solid tumors. -
Alejandro Sandoval Lentisco
Postdoctoral Scholar, SCRDP/ Heart Disease Prevention
BioAlejandro completed his PhD in Psychology at the University of Murcia, Spain, in 2024. His doctoral research focused on assessing transparency and risk of bias in psychology meta-analyses. Prior to this, he obtained an MSc in Cognitive and Behavioral Neuroscience from the University of Granada, Spain. In addition to evaluating methodological practices in evidence synthesis and empirical studies, he is interested in a wide range of meta-scientific questions, such as how science self-corrects and how research should be evaluated.
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Mojtaba Sedigh Fazli
Postdoctoral Scholar, Immunology and Rheumatology
BioDr. Mojtaba Fazli is a leading scientist specializing in AI/ML, computer vision, and biomedical research. He is currently a Postdoctoral Research fellow Scientist at Stanford University and a Senior Research Fellow at the Harvard Ophthalmology Artificial Intelligence Lab, Harvard University, where he previously completed a postdoctoral fellowship.
Dr. Fazli's research bridges cutting-edge artificial intelligence with groundbreaking applications in multi-scale biomedical imaging, disease modeling, and drug discovery. His expertise encompasses advanced areas of AI/ML, including computer vision for 2D/3D medical image analysis, bioinformatics, and object tracking in both 2D and 3D environments. He has played a key role in developing state-of-the-art algorithms to enhance diagnostic precision and therapeutic outcomes within the biotechnology and healthcare sectors.
With a strong foundation in both academia and industry, Dr. Fazli previously served as a Senior Open Innovation Scholar at the Novartis Institute for Biomedical Research. There, he applied his expertise in strategic planning, programming, and simulation to tackle complex biomedical challenges.
Dr. Fazli holds a Ph.D. in Computer Science, with a minor in Mathematics, from the United States, as well as a Doctorate in Business Administration from France. His academic journey also includes master’s degrees in Economics and Management, as well as Artificial Intelligence and Robotics. His interdisciplinary approach blends AI-driven innovation with practical, impactful solutions in healthcare.
At Stanford, Dr. Fazli leads research initiatives focused on integrating multimodal data in rheumatology, advancing ultrasound imaging research in Rheumatoid Arthritis, and developing AI methodologies for clinical applications. His current work also involves leveraging Generative AI and Large Language Models (LLMs) to drive innovation in medical data analysis and clinical decision support.
