Radiology informatics fellowship faculty staff and fellows

Radiology Informatics - Faculty, Staff & Current Fellows

Program Leadership

Mary Saltz

Mary Saltz, MD

Founding Program Director.

Prateek Prasanna

Prateek Prasanna, PhD

Founding Program Director

Elaine Gould

Elaine Gould, MD

Radiology Department Chair

Joel Saltz

Joel Saltz, MD, PhD

BMI Department Chair             

 

Core Faculty

Mary Saltz, MD

Janos Hajagos, PhD

Prateek Prasanna, PhD

Chao Chen, PhD

Fusheng Wang, PhD

Zhaozheng Yin, PhD

Program Coordinator : Joseph Cesaria

 

Presenting our First Class of Graduates

First Class of Graduates

 

Current Resident Participants

Year #1

 

Andrew Schlafly

Andrew Schlafly

Andrew Schlafly is a resident in Diagnostic Radiology at Stony Brook University Hospital. He received an A.B. in Mathematics from Harvard in 2010, and worked in multiple quantitatively oriented roles before ultimately attending Perelman School of Medicine (M.D. 2022). He is honored to take part in the Biomedical Informatics certificate program, and would like to learn more about this exciting field, and to work on computationally driven research projects that pertain to radiology. He aspires to follow in the footsteps of the many members of earlier classes of radiology residents at Stony Brook who have had very positive and productive experiences in the Biomedical Informatics program.

 

Rinald Paloka

Rinald Paloka

Dr. Rinald Paloka is a resident physician with the Department of Radiology at Stony Brook University Hospital. He is originally from Jacksonville, Florida where he completed a Bachelor of Arts at the University of North Florida. He went on to Florida Atlantic University Schmidt College of Medicine where he developed a passion for imaging science with a focus on community health. He hopes to use the knowledge acquired from the medical informatics program to advance clinical screening and continuity of care for patients who are lost to follow-up.

 

 

Year #2

 

Janet Shum

Janet Shum

Dr. Shum is a Brooklyn native currently in her second year of Radiology residency. She is a Boston University alumna who obtained her master's degree in Biomedical Sciences at New York Medical College. While completing her master’s, she worked in the patient relations department at Westchester Medical Center to assist patients in signing up and navigating through their medical health record portal. She obtained her medical degree from St. George's University. A medical youth debate at George Washington University in the summer before college sparked her interest in online medical records and inoperability which lead her to Health Informatics and research involving radiomics. On her free time, she adores spending time with her corgi, Zoey, and enjoying the ever-changing food scene in NYC with her husband.

 

Farshid Faraji

Farshid Faraji

Dr. Farshid Faraji is a resident physician with the Department of Radiology at Stony Brook University Hospital. He received a BA from UC Berkeley in Molecular and Cell Biology with an emphasis in Neurobiology, went on to obtain an MS in Biomedical Imaging at UCSF, and subsequently completed his MD at the University of Illinois, Chicago. He is passionate about imaging science research as it relates to cardiovascular and neurobiological applications. In his free time, he enjoys traveling, photography, and cooking.

 

Purohit -

Kush Purohit

Dr. Purohit is a diagnostic radiology resident at Stony Brook University Hospital. He is originally from Pittsburgh, where he completed a Bachelors of Philosophy in Neuroscience and developed a passion for research at the University of Pittsburgh. He went on to complete a Fulbright research scholarship studying diabetes epidemiology in India. After attending Ross University School of Medicine, he chose to pursue a career in radiology at Stony Brook. He is grateful to be a part of the Bioinformatics certificate program and is looking forward to collaborating with and learning from a diverse group of colleagues in the informatics program! His research interests include improving radiology workflow and efficiency, along with artificial intelligence and machine learning.