Nadav Brandes
Nadav Brandes
Principal Investigator

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Nadav is an assistant professor at NYU School of Medicine in the Center for Human Genetics and Genomics and the Department of Biochemistry and Molecular Pharmacology. He is also affiliated with the Courant Institute of Mathematical Sciences. He earned his PhD in computer science from the Hebrew University of Jerusalem in 2021 under the supervision of Michal Linial and Nathan Linial. He was then a postdoctoral scholar at UCSF in the lab of Jimmie Ye. In his free time, Nadav enjoys reading, cooking, meditating and watching anime shows.


Saar Shoer
Saar Shoer
Postdoctoral Fellow

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Saar earned her PhD at the Weizmann Institute of Science under the joint supervision of Prof. Eran Segal and Prof. Yitzhak Pilpel. Her doctoral research focused on leveraging statistics and data science techniques to tackle unsolved questions in the big data world of microbial genetics. As a postdoctoral fellow in the Brandes Lab, she is utilizing AI to help reduce the global burden caused by antibiotic resistance. Outside the lab, Saar enjoys surfing, snowboarding, and spending time in nature.


Po-Yu Lin
Po-Yu Lin
Assistant Research Scientist

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Po-Yu Lin, is an attending physician in the Department of Neurology and Genomic Medicine at National Cheng Kung University Hospital in Taiwan. He earned his M.D. from the National Cheng Kung University School of Medicine and completed his Master’s degree in Biomedical Informatics at NYU Grossman School of Medicine under the mentorship of Dr. Brandes. His clinical and research interests focus on variant pathogenicity interpretation and clinical decision support. After graduation, Po-Yu continued collaborating with the Brandes Lab, driven by a strong passion for the interpretability of genomic language models and their integration into clinical practice.


Anushka Sinha
Anushka Sinha
Research Associate

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Anushka completed her undergraduate studies at UC San Diego, where she gained research experience at Scripps Research. She then pursued a Master’s in Computational Biology at Carnegie Mellon University, where her academic projects fostered a strong interest in leveraging artificial intelligence, particularly large language models (LLMs), for biological research. In the Brandes Lab she applies genomic AI models to identify causal genes affecting disease risk and seeks to train the next generation of genomic language models. In her free time, Anushka enjoys taking dance classes, working out, and trying different restaurants.


Gabriella Snow
Gabriella Snow
Research Associate

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Gabriella earned her undergraduate degree from California Polytechnic State University, San Luis Obispo, where she studied Public Health and Biology. During this time, she gained research experience in the social and biomedical sciences, focusing on projects related to reproductive health and nutrition. In the Brandes Lab, she assists in preparing funding proposals that support the lab’s ongoing projects. She is additionally interested in expanding genomic AI applications to better understand mutation effects on cellular and molecular function. Outside the lab, Gabriella enjoys traveling with friends, collaging, and playing the bass.


Rishab Pulugurta
Rishab Pulugurta
Research Technician

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Rishab is a recent graduate from Duke University with degrees in Computer Science and Biology. As a researcher and engineer he is extremely drawn to the mission of pioneering a pipeline for scientific discovery and therapeutic development using generative AI along with experimental techniques! Aside from work, he loves playing chess, working out, and reading!


Akshay Nuthanapati
Akshay Nuthanapati
Non-Traditional Volunteer

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Akshay is a Master’s student at New York University, specializing in Machine Learning and Computer Engineering. His research interests lie at the intersection of AI and the natural sciences, with a particular focus on Machine Learning for Computational Biomedicine and Drug Discovery. Outside of his academic work, he enjoys exploring the history and philosophy of science and spending time hiking.