We’re interested in human and artificial intelligence. We use artificial intelligence (AI) to better understand and care for the human brain, and in study the human brain to build better AI.

We believe that investigations into the nature of artificial intelligence and human intelligence are fundamentally the same, and that by attempting to build better artificial intelligence we will discover fundamental insights into the key mechanisms behind human intelligence.

These investigations will augment our clinical work in treating neurological disorders and cancer, and lead the transition from ML guided investigations to ML guided interventions.

**Summer 2021 - Gujarati cuisine outing (Inaugural lab event)**

Our goal is to have real world impact. Be it developing tools that will be deployed to save lives, or innovating new AI technologies that will make machines more intelligent, we want to see our research realized as technologies that change the world for the better.

RESOURCES

All lab members are equipped with a workstation with two of the latest nVidia GPUs, and our team has a dedicated cluster of 3x 8xA100 nodes connected by nVLink in addition to access to NYULangone’s HPC resource BigPurple which mounts over 200 V100s.

Research
Interests

Our Team

Staff

**Eric Karl Oermann (EKO)** (@ekoermann) is an Assistant Professor of Neurosurgery, Radiology, and Data Science at NYU. He studied mathematics at Georgetown University with a focus on differential geometry. Prior to attending medical school, Dr. Oermann spent six months with the President’s Council on Bioethics studying human dignity under the mentorship of reknowned physician-philosopher Edmund Pellegrino. Dr. Oermann has won numerous awards for his scholarship including fellowships from the American Brain Tumor Association and Doris Duke Charitable Research Foundation where he was first exposed to neural networks and deep learning. He has published over one-hundred manuscripts spanning basic research on machine learning, neurosurgery, and the philosophy of medicine. Dr. Oermann was selected as one of Forbes Magazine’s 30 Under 30 for his work on using machine learning to develop prognostic models for cancer patients. Dr. Oermann completed a postdoctoral fellowship at Verily (Google Life Sciences), and served as an advisor at Google-X on Project Amber. He has founded or co-founded three startups in the medical AI space. He is interested in understanding and protecting human intelligence by using machine learning to better understand the human brain and the human brain to improve machine learning.

**Katherine (Katie) Link** is previously a Google AI Resident where she participated in Google-X’s Project Amber and a former fellow from the Allen Institute for Brain Science. She is interested in using deep learning to advance modern healthcare and medicine further our understanding of the human brain. Past projects ranged from using deep learning to reconstruct electron microscopy imaging and MRI studies, to attempting to diagnose depression from integrating psychophysics with electrophysiology recordings. Her current project is NYUMets – building the world’s largest open dataset of brain metastases (and cancer) and studying the use of recurrent models with longitudinal imaging of metastatic cancer.

**Otto** (@ottodacorgi) is a Welsh Pembroke Corgi and the mascot of our lab. He likes naps, people, and food.

**Daniel Orringer, M.D. (DO)** (@DanOrringerMD) is an Associate Professor of Neurosurgery and Pathology in the Department of Neurosurgery of the NYU Grossman School of Medicine. He is one of the inventors of stimulated Raman histology and is an international leader in the use of intraoperative, digital pathology to guide clinical care. As a neurosurgeon at NYU Langone’s Brain and Spine Tumor Center, part of Perlmutter Cancer Center, he treats people who have tumors of the spinal cord and the brain, both those that originate in the brain and spread to the brain from other organs. DO runs a highly interdisciplinary, National Health Institutes–funded research group focused on three initiatives—we aim to improve surgical outcomes for people with brain tumors, use artificial intelligence to support surgical decision-making and brain tumor diagnosis, and conduct clinical and translational trials of novel therapeutics. He is the recipient of six grants from the National Institutes of Health. He is most proud of receiving the Andrew Parsa Young Investigator Basic/Translational Research Award from the Society for Neuro-Oncology in 2016, the Congress of Neurological Surgeons’ Innovator of the Year Award in 2017, and the Congress of Neurological Surgeons’ Rosenblum–Mahaley Clinical Research Award in 2019.

Postdoctoral Fellows

**Young Joon (Fred) Kwon, Ph.D.** is a physician-scientist in training and an aspiring radiologist. I have research experience and peer-reviewed publications in molecular imaging, radiation physics, computer vision, and artificial intelligence. Clinically, I have worked as a certified EMT and am currently a senior clinician in a student run, physician supervised clinic at Mount Sinai. For my PhD thesis, I developed machine learning algorithms to increase accessibility of artificial intelligence research and to assist clinicians in interpreting medical imaging data.

Graduate Students

**Lavender Yao Jiang** graduated from Carnegie Mellon majoring in Electrical and Computer Engineering and Mathematical Sciences. She is interested in natural language processing and its application in healthcare. She is the lead researcher and principle engineer of NYUTron, one of the world’s largest and most sophisticated efforts to study large language models in healthcare. While at CMU, Lavender had the pleasure of working on signal processing, neuroscience, and robotics projects with Drs. José M.F. Moura, Pulkit Gover, and Howie Choset. In her free time, Lavender enjoys cooking, bouldering, and playing video games. She

**Chris Xujin Liu** graduated from Carnegie Mellon University with degrees in Electrical and Computer Engineering and Biomedical Engineering. He interested in the intersection of biological intelligence and machine intelligence, and studies deep learning models of human neuroscience. In his free time, he enjoys playing jazz guitar and bouldering.

MEDICAL STUDENTS 2022-2023
Alexander “Scanner” Cheung (NYU 2023)
Rachel Gologorsky (ISMMS 2024)
Aly Valliani (ISMMS 2023)
Mustafa Nasir-Moin (HMS 2026)

RESIDENTS 2022-2023
Sean Neifert, M.D. (Neurosurgery 2028)

UNDERGRADUATES 2022-2023
Grace Von Oiste (Harvard University Biomathematics 2024)
Ming Cao (NYU CS/DS 2023)
Chenkang Stephen Zhang (NYU CS/DS 2023)
Lucy Wu (NYU CS/DS 2023)
Gracy Yang (NYU CS/DS 2023)
Gavin Yang (NYU CS/DS 2023)

Former Team Members
John Zech, M.D. (Columbia University, Radiology)
Rachel Bronheim, M.D. (HSS, Orthopedic Surgery)
Martin Kang, M.D. (Tempus Inc.)
Brett Marinelli, M.D. (MSHS, Interventional Radiology)
Sulaiman Somani, M.D. (Stanford, Internal Medicine)
Annika Brundyn, M.S. (nVidia)
Jesse Swanson, M.S. (ByteDance)
Brian E. Murphy, M.S. (NYU Langone Health)
Yifan Li, M.S. (Virginia Tech SOM)
Michael A George, M.S. (Rosalind Franklin SOM)

**2022 Spring - “OBaby” Shower (mixed reality) for soon-to-be youngest lab member (Vivian)**

Team brunch with our undergraduate recruits for Summer 2022. I guess Sunflower Gramercy is our new “team spot” ?

Joining OLAB

Our lab is composed of artificial intelligence (AI) researchers and physician-scientists from a wide range of backgrounds including mathematics, computer science, neuroscience, linguistics, informatics, and medicine. We are always looking for highly motivated individuals to join our research team both in general and for specific projects. We are proud to be a diverse team, with diverse nationalities, ethnicities, languages, genders, and ages. We seek to create a supportive environment for innovative and bold scientific research as well as the personal and professional development of all our members.

Our work is powered by Future OLAB Cluster #1 (Name subject to change), a dedicated 24x A100 GPU cluster for neuro-AI research, as well as personal GPU workstations (dual 3090s) that we purchase for each graduate level student in the lab.

PhD Students

Those interested in working in the OLAB for their PhD are encouraged to apply to the PhD program in the Vilcek Institute of Graduate Biomedical Sciences or the Center for Data Science. Prospective students interested in learning more about the research going on in the lab are encouraged to send a brief email describing their interests and a copy of their CV to Eric Oermann, MD. We also encourage interested applicants to learn about our lab by reaching out to current lab members via email. Prospective graduate students are expected to be passionate about our research and competent programmers, but need not be experts in machine learning or neuroscience.

Postdoctoral Fellows

We welcome applications for postdoctoral fellows. Applicants are expected to have a strong background in machine learning and to be skilled in programming in Python. Our lab is located in the Tisch Hospital of NYU Langone Medical Center, providing immediate access to a world class clinical environment and excellent opportunities for multidisciplinary interaction with our close collaborators at the Center for Data Science and Mount Sinai Health System. Interested applicants can send a brief e-mail describing their interests and a copy of their CV to Eric Oermann, MD.

Our Funders

Funders enable breakthrough science and technology that furthers our understanding of AI, neuroscience, and neurosurgery.

If you are interested in contributing to our research, please contact Eric Oermann, MD.

ResearchInterests

Our Team

Staff

Postdoctoral Fellows

Graduate Students

Joining OLAB

PhD Students

Postdoctoral Fellows

Our Funders

Research
Interests