Rebekah is pursuing a Master of Science in Health Data Science at UCSF, building on her background in bioinformatics and biology from the University of Waterloo. She is passionate about developing data-driven systems that bridge research and real-world clinical impact. In the Sohn Lab, she is exploring applications of large language models in radiology to improve diagnostic workflows and care delivery.

Dominique Baria is a third-year medical student at the University of Nevada, Reno School of Medicine. She was a 2024 Research Initiative to Promote Diversity in Radiology (RIDR) student and has contributed to multiple projects in cardiothoracic imaging in the Sohn Lab, with a particular focus on pulmonary embolism imaging and functional lung MRI. Through this work and her clinical training, she is interested in using imaging to inform decision-making and improve the precision and effectiveness of minimally invasive care.

Masha Bondarenko earned her Bachelor of Science in Electrical Engineering and Computer Science from the University of California, Berkeley, where she developed a strong foundation in machine learning, mathematical modeling, and systems engineering. She is passionate about integrating computational methods with clinical practice to advance personalized healthcare, with a focus on imaging and clinical data for cancer screening and diagnostics.

Dr. Ali Nowroozi, MD graduated from Tehran University of Medical Sciences, Iran, in 2024, and has a long-standing background in programming and informatics. His current research focuses on advancing AI in radiology, including using AI to solve real world challenges as well as facilitating AI adoption into practice.

Gabriel F. Pérez Pagán is a second-year medical student at Universidad Central del Caribe in Puerto Rico. He completed his undergraduate studies at the University of Puerto Rico. Gabriel has a strong passion for radiology and medicine, and is currently conducting research at UCSF focused on interstitial lung disease (ILD), specifically interstitial lung abnormalities (ILA) and the clinical delays between their radiographic detection and subsequent diagnosis or management.

 is a dedicated thoracic surgeon specializing in minimally invasive approaches to treat lung cancer, esophageal cancer, and mediastinal tumors. With advanced training in video-assisted thoracoscopic surgery (VATS) and robotic-assisted techniques, he performs complex oncologic resections with precision and efficiency. His clinical practice emphasizes a multidisciplinary approach to advanced-stage thoracic malignancies, integrating surgery with chemotherapy, radiation, and emerging systemic therapies to optimize patient outcomes. 

Koharu Sakiyama is a rising senior at UC Berkeley studying Molecular & Cell Biology and minoring in Data Science. Her research interests lie in exploring the application of machine learning in medical settings to improve clinical workflow and personalized medicine. In the Sohn Lab, she is currently working on developing a large language model based framework to improve radiological communication by answering patient queries. Following her undergraduate studies, Koharu hopes to pursue a PhD in computational medicine or related field.

Juan Serna, BS is a 4th-year medical student at the University of California, San Francisco. He has previously done research in hip and shoulder arthroscopy, and is currently doing research on LLM applications to Lung Cancer CT Screening reports. He is planning to apply to Radiology residency for the 2026 Match.