NY
AGIM

About NYAGIM

The New York Area Group in Modeling and Informatics (NYAGIM) is a thriving community of greater New York City area scientists focused on advancing in silico methods in drug discovery.

Our Mission

We are a growing community focused on the advances of in silico methods related to drug discovery, and how they increasingly impact and transform pharmaceutical research. Our scientific interest covers a wide range of fields, including computational chemistry, medicinal chemistry, chemoinformatics, machine learning, molecular modeling, structural biology, and protein design.

NYAGIM is an inclusive forum for all academia and industry scientists interested in this particularly dynamic scientific interface, to connect, interact, learn and share.

What We Do

Quarterly Events

We organize quarterly events featuring scientific seminars, discussions, and networking opportunities.

Community Building

Connect with peers from academia and industry working in computational drug discovery.

Knowledge Sharing

Learn from leading experts and share insights on the latest computational methods.

NYC Community

Serving the greater New York City area scientific community and beyond.

Our Leadership

NYAGIM is organized by a dedicated team of scientists passionate about advancing computational methods in drug discovery.

Dr. Sarah Chen

Dr. Sarah Chen

Lead Organizer

Columbia University

Dr. Michael Rodriguez

Dr. Michael Rodriguez

Co-Organizer

Schrödinger

Dr. Emily Watson

Dr. Emily Watson

Co-Organizer

Memorial Sloan Kettering

Dr. James Kim

Dr. James Kim

Co-Organizer

NYU School of Medicine

Interested in Volunteering?

We're always looking for passionate individuals to help organize events and grow our community.

Get in Touch

Scientific Focus Areas

Computational Chemistry
Medicinal Chemistry
Chemoinformatics
Machine Learning
Molecular Modeling
Structural Biology
Protein Design
Drug Discovery
In Silico Methods

Join Our Community

Connect with peers, learn from experts, and stay updated on the latest in computational drug discovery.

View Upcoming Events