Team

Dr. Gilmer Valdes, PhD

Dr Valdes, PhD is an assistant professor with dual appointment in the departments of Radiation Oncology and Epidemiology and Biostatics at University of California, San Francisco. He obtained his undergraduate degree in Radiochemistry at INSTEC, Havana and his PhD in Biomedical Physics from University of California, Los Angeles. He pursued postdoctoral training at University of California San Francisco and later did his residency in Therapeutic Radiological Physics at University of Pennsylvania. He is board certified Therapeutic Radiological Physics by the American Board of Radiology. Currently he serves as an associate editor of the Journal of Medical Physics and The British Journal of Radiology. He is a member of the Biological Effects Subcommittee and the Machine Learning Subcommittee of the AAPM. He has published over 40 peer reviewed papers. He has both theoretical and applied research interests. His main research focus are the applications of Machine Learning to Radiation Oncology and the development of new statistical procedures. He is currently funded by the NIH under a K08 award number K08EB026500 to develop accurate and interpretable machine learning algorithms.

Charles B. Simone, II, MD

Charles B. Simone, II, MD, FACRO is Research Professor and Chief Medical Officer of New York Proton Center and Full Member in Radiation Oncology at Memorial Sloan Kettering. He is an internationally recognized expert in proton therapy for thoracic malignancies and reirradiation, and in developing innovative clinical trials in thoracic oncology. Dr. Simone was previously Chief of Thoracic Oncology at University of Pennsylvania, Director of the Penn Mesothelioma and Pleural Program, and Director of Clinical Research and Operations in Radiation Oncology at Penn. He was then appointed Medical Director of Maryland Proton Treatment Center. At University of Maryland, he also served as Chair of the Clinical Research Committee for their Comprehensive Cancer Center, proton Fellowship Director, and Director of the Stereotactic Radiation Therapy Program. He completed his undergraduate and medical training at University of Pennsylvania and residency in radiation oncology at the National Cancer Institute/NIH, where he was chief resident.

Dr. Simone is an NIH, National Science Foundation, and Department of Defense-funded investigator who has published >395 scientific articles/chapters and given >250 scientific lectures to national/international audiences. He is national Principal Investigator or Co-Chair of 7 NIH-funded oncology cooperative group trials and three-time Association of Residents in Radiation Oncology Educator of the Year Award winner. Dr. Simone is Proton Collaborative Group President of the Board and Chairs the ASTRO Lung Resource Panel Committee, NRG Oncology Particle Therapy Work Group, NCI/Radiosurgery Society GRID-Lattice-Microbeam-Flash Radiotherapy Clinical Working Group, and several Particle Therapy Co-Operative Group subcommittees. He is Editor-in-Chief of Annals of Palliative Medicine.

Eric Eaton

Eric Eaton is a research associate professor in the Department of Computer and Information Science at the University of Pennsylvania and a member of the GRASP (General Robotics, Automation, Sensing, & Perception) lab, where he leads the Lifelong Machine Learning research group. Prior to joining Penn, he was a visiting assistant professor at Bryn Mawr College, a senior research scientist at Lockheed Martin Advanced Technology Laboratories, and part-time faculty at Swarthmore College. His primary research interests lie in the field of machine learning, deep learning, and interactive AI, with applications to service robotics and personalized medicine. (link)

Lyle Ungar

Dr. Lyle Ungar is a Professor of Computer and Information Science at the University of Pennsylvania, where he also holds appointments in multiple departments in the Schools of Business, Medicine, Arts and Sciences, and Engineering and Applied Science. He has published over 300 articles, supervised two dozen Ph.D. students, and is co-inventor on ten patents. His current research focuses on developing scalable machine learning methods for data mining and text mining, including deep learning methods for natural language processing, and analysis of cell phone and social media to better understand the drivers of physical and mental well-being.

Efstathios (Stathis) D Gennatas MBBS AICSM PhD

Stathis is an Assistant Professor in the Division of Bioinformatics, Department of Epidemiology & Biostatistics at the University of California, San Francisco. He completed medical training at Imperial College London and doctoral training in Neuroscience at the University of Pennsylvania. He has previously held staff scientist positions at the UCSF Memory and Aging Center, UCSF Division of Medical Physics, and the Stanford Laboratory of Artificial Intelligence in Medicine and Biomedical Physics. Stathis works on the development and application of machine learning algorithms for biomedical and clinical data, collaborating with basic researchers and clinicians across medical specialties. His own research is focused on the study of brain development in children and neurodegenerative disease in adults. He is the author of the rtemis machine learning package (https://rtemis.lambdamd.org).

Olivier Morin

Jessica Scholey

Jessica Scholey is a clinical instructor in the department of Radiation Oncology and PhD candidate in Radiology and Biomedical Imaging at the University of California, San Francisco. She obtained her undergraduate degree in Physics at the University of California, Berkeley, followed by her master’s degree and residency training in Medical Physics at the University of Pennsylvania. She is board certified in Therapeutic Medical Physics by the American Board of Radiology. She is the lead physicist for the Proton Ocular and MRI programs within the department of Radiation Oncology at UCSF. Her research interests focus on advanced imaging techniques for radiotherapy applications, specifically MRI-only treatment planning using both sequence- and deep learning-based approaches. She is a member of the AAPM Machine Learning Subcommittee, UCSF Radiology Center for Intelligent Imaging Scientific Research Group, and Particle Therapy Co-Operative Group Ocular Subcommittee.

Tomi Nano

Abdullah Zaini

Abdullah is a machine learning researcher at the GRASP lab of the University of Pennsylvania. He obtained both an M.S. in Robotics and a B.S. in Computer Science and Cognitive Science from the University of Pennsylvania. His research interests revolve around knowledge representations and how these representations affect 1) the transferability of knowledge between tasks, 2) the interpretability of intermediate states in multi-layered models, 3) the fairness and privacy implications of a model, 4) the generalization of representations learned from few samples.

Thomas Greening

Thomas Greening is a master’s student in the Computer and Information Science program at the University of Pennsylvania. His interests include distributed systems and machine learning. He is also a software engineer with 8 years of experience building web applications and data processing systems.