Education
Sept. 2019 – June 2024
Doctor of Philosophy in Chemistry
University of California San Diego, CA, USA · CGPA 4.0/4.0
- Advisors: Prof. Rommie E. Amaro and Prof. J. Andrew McCammon
- Specialization: Theoretical and Computational Biophysics
Aug. 2012 – June 2017
Integrated BS-MS (Chemistry Major, Physics Minor)
IISER Thiruvananthapuram, KL, India · CGPA 8.6/10.0
- INSPIRE Fellow · Swiss Government Excellence Scholar (2017)
Postdoctoral Research
Sept. 2024 – Present
Flatiron Research Fellow
Center for Computational Biology & Center for Computational Mathematics, Flatiron Institute, New York
- Developed cryoWEight — maximum-entropy reweighting framework for cryo-EM guided MD ensembles.
- Developed ManifoldEM — geometric ML approach to infer free-energy landscapes from cryo-EM images.
- Developed seekrflow — automated milestoning pipeline with ML force fields for drug-target kinetics.
- Designed stable hinge proteins with conformational switching for therapeutic applications.
Industry Experience
June 2023 – Present
Collaborative Researcher
Janssen (Johnson & Johnson), La Jolla, CA
- Developed thermodynamic-kinetic metrics using deep learning to predict PROTAC permeability and residence times.
- Improved binding-kinetics predictions for kinase targets via multiscale simulations.
June – Sept. 2024
Multiscale Modeling Scientist Intern
Genentech, Inc., South San Francisco, CA
- Developed AI-enhanced multiscale molecular and Brownian dynamics simulations for protein-protein kinetics.
- Built end-to-end computational workflow for kinetic pathway modeling.
June – Aug. 2023
Computer-Aided Drug Design Intern
Janssen (Johnson & Johnson), La Jolla, CA
- Employed deep learning and enhanced sampling to predict permeability of protein degraders.
- Developed Python workflow for blind cellular permeability prediction of beyond-rule-of-five molecules.
June – Sept. 2022
Research & Early Development Intern
Genentech, Inc., South San Francisco, CA
- Employed MSM and enhanced sampling to estimate transition rates of protein degraders between metastable states.
- Developed Python framework for customizable force field parameters for protein degraders.
Teaching & Mentoring
Sept. – Dec. 2025
Co-Instructor, CHEM-GA 2600: Statistical Mechanics
New York University (with Prof. Marc Tuckerman)
- Graduate-level course on equilibrium/non-equilibrium statistical mechanics, simulation algorithms, path integrals.
May – Aug. 2025
Research Mentor
Simons–National Society of Black Physicists Scholars Program
- Advising undergraduate scholars on computational biology projects.
Sept. 2020 – June 2022
Teaching Assistant — 4 Undergraduate Courses
Department of Chemistry, UC San Diego
- Physical Biochemistry II · Chemical Physics (Statistical Thermodynamics II) · Biophysical Thermodynamics · General Chemistry I
Technical Skills
Programming
Python, Bash, AWK, MATLAB, R, Mathematica, LaTeX
Molecular Simulation
AMBER, CHARMM, NAMD, OpenMM, GROMACS, WESTPA, BrownDye, VMD, MDTraj, MDAnalysis, PyMOL, Schrödinger
Quantum Chemistry
ORCA, Gaussian, Q-Chem, VASP, Quantum ESPRESSO, Chemcraft, Avogadro
Cheminformatics
RDKit, OpenEye, AutoDock Vina, rDock, MOLDEN, OpenBabel
Free Energy Methods
Alchemical TI, FEP+, SEEKR/SEEKR2, YANK, Perses
Cryo-EM
RELION, ManifoldEM, cryoSPARC, cryoDRGN, EMAN2
AI / ML
PyTorch, TensorFlow, Keras, scikit-learn
HPC
CUDA, OpenMP, MPI, SLURM, PBS, AWS, Google Cloud, Azure HPC, Lustre, GPFS
Data & Visualization
Pandas, Matplotlib, Seaborn, Tableau, Gnuplot, Jupyter
DevOps
Git, GitHub Actions, Docker, Singularity, Travis CI, Jenkins