Scientist II, AI Research (02/26 – Present)

Scientist I, AI Research (03/25 – 02/26)

• Developed and led technical initiatives at the intersection of LLM post-training and experimental science—enabling Lila’s central AI agent to learn from proprietary laboratory data, experimental workflows, and feedback from the physical world

National Science Foundation Graduate Research Fellow, PhD Candidate

• Developed numerous state-of-the-art deep learning frameworks for molecular design and protein-ligand binding prediction, spanning use cases in oncology, infectious disease, gene editing, and cardiotoxicity, with multiple methods deployed at major pharmaceutical companies such as Pfizer and Novartis

Researcher, Computational Safety Sciences (Contractor)

• Developed a generative deep learning framework for re-engineering drug candidates for reduced hERG liability while preserving their primary pharmacology, and applied it to internal drug development programs dealing with hERG-related challenges

Founding Scientist

• Led the foundational scientific efforts, established collaborations with numerous industry partners including Pfizer, NVIDIA, Novartis, and Moderna, and published the initiative’s first collaborative paper as first author—efforts that ultimately catalyzed a $10M investment from the Connecticut State government

Scientific Data Annotator (Contractor)

• Contributed to the fine-tuning of OpenAI’s large language models by crafting scientifically rigorous Q&A-based prompts pertaining to mathematics, physics, and chemistry to enhance the models’ scientific domain expertise

Scientific Software Developer (Intern)

• Led the development of a deep learning model for classifying protein-protein interaction interfaces which was integrated into the company’s virtual screening pipeline for PROTACs

Science & Technology Consultant (Contractor)

• Consulted for NASA on cutting-edge advancements pertaining to energy storage, privacy-preserving networks, image detection, aerial surveillance, and aerodynamic levitation

Undergraduate Researcher

• Revealed insights into excited-state mechanisms in binuclear rhenium(I)-based organometallic systems using computational methods (quantum chemistry calculations) and experimental spectroscopy (NMR, UV-Vis, fluorescence, and IR spectroscopy), ultimately leading to anion sensor-based applications

Teaching Fellow

• Matrix Methods in Quantum Mechanics10/23 – 12/23
• Machine Learning & Quantum Computing03/23 – 06/23
• Advanced General Chemistry II01/25 – 05/25
• General Chemistry I08/24 – 12/24

Teaching Assistant

• Inorganic Chemistry Fall 202009/20 – 12/20
• Chemical Principles I Fall 202009/20 – 12/20
• Inorganic Chemistry Fall 201909/19 – 12/19
• Chemical Principles II Spring 201901/19 – 05/19
• Introduction to Chemistry Fall 201709/17 – 12/17