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Sr. Director, AI/ML

Ensem Therapeutics

• Leading the development of a physics-informed AI/ML platform for drug discovery and optimization.
• Contributing to the development of generative models for molecular design and protein metastable-state sampling, leveraging diffusion, autoregressive models, and reinforcement learning.
• Training and evaluating deep learning models for structure and pose prediction, binding affinity, and molecular design.
• Assisting in the design and implementation of an automated pipeline using LLMs, VLMs, and OCSR models to extract biochemical data from patents and scientific literature.

Director, AI/ML

1859, Inc.

• Led a team of AI/ML scientists to build deep-learning models for drug discovery and optimization.
• Built a scalable compute infrastructure for training and inference, enabling high-throughput screening of billions of compounds
• Developed graph neural networks and SE(3) Transformer models for structure- and ligand-based drug design.
• Implemented generative models to design molecules optimized for potency, selectivity, ADMET, and drug-likeness.
• Communicated technical insights and research outcomes to senior leadership and external stakeholders.

Staff Machine Learning Scientist

Atomwise

• Designed and implemented Atomwise's ligand-based drug discovery platform, integrating domain-specific constraints and rigorous validation protocols.
• Built pipelines for data ingestion, curation, training, and inference at scale.
• Implemented sample-efficient 3D graph neural networks to model over 30 potency and ADMET properties simultaneously.
• Implemented generative models to design molecules optimized for potency, selectivity, ADMET, and drug-likeness.
• Communicated technical insights and research outcomes to senior leadership and external stakeholders.

Machine Learning Engineer

Ford Motor Company

• Contributed to the development and enhancement of Path Planning algorithms for Ford's Level 2 autonomous driving system (BlueCruise).
• Assisted in the implementation and evaluation of sensor fusion algorithms for integrating camera and radar inputs.
• Designed and refined real-time models to handle complex road and lane configurations under noisy sensor conditions.
• Researched ML-based trajectory prediction and path-planning algorithms.

PhD

Michigan State University, East Lansing, MI, USA

Machine Learning and Drug Discovery

• Machine Learning
• Drug Discovery
• Computer Science
• Electrical and Computer Engineering