Industry
2011–2016 · Bangalore, India
Before entering research, I worked as a Mainframe Application Developer at IBM India. Those years taught me how software is designed, maintained, supported, and improved when reliability matters and many people depend on it.
That experience still shapes my scientific work. I approach computational workflows as systems that should be reproducible, inspectable, maintainable, and useful to someone beyond their original developer—the same concerns that now guide my work on research automation and TritonDFT.
Teaching
Classroom teaching, computational labs, assessment, and research mentoring.
UC Merced · 2016–2018
Led a weekly classroom session and laboratory for physical-science and engineering students. Designed practice problems, introduced each experiment with a focused theory overview, and provided feedback through homework and laboratory grading.
UC Merced · 2016–2018
Facilitated two laboratory sessions each week, connecting programming concepts with worked coding examples. Managed assignments through CatCourses, evaluated code, and applied academic-integrity checks.
UC Merced · February 2025
MSE 119 / MBSE 219 / PHYS 246 · 50 minutes
Led an interactive computational lesson connecting Newtonian dynamics with Euler, Verlet, and Velocity Verlet integration. Students examined timestep accuracy, implemented numerical algorithms, and worked through a LAMMPS friction example involving MoS₂.
UC Merced · November 2024
MSE 152 · Materials Processing & Performance II
Guided students through binary phase diagrams, tie lines, the lever rule, invariant reactions, and the iron–carbon system. Group activities connected alloy composition and processing conditions with phase fractions and resulting microstructures.
UC Merced · October 2024
MSE 152 · Materials Processing & Performance II
Developed an activity-centered lecture on edge, screw, and mixed dislocations; Burgers vectors; slip systems; and Schmid’s law. Students applied these ideas to work hardening, grain refinement, and alloy-strengthening strategies.
UC Merced · September 18, 2024
PHYS 181/281 · 75 minutes
Created and taught an interactive Jupyter lesson on forward, backward, and central differences; truncation and roundoff errors; optimal step size; and error analysis, supported by pre- and post-class assessments and practical examples.
Research mentoring
Mentored an undergraduate summer researcher and junior graduate students. I currently guide graduate students in Quantum ESPRESSO, VASP, DFT fundamentals, practical simulation choices, and TritonDFT-assisted workflows.
Speaking
Invited opportunities to connect computation, materials physics, and AI for science.
Mathematical Biology SMART Team / Directed Study Group · UC Merced
Invited seminar · California State University, Fresno
Materials and Biomaterials Science and Engineering · UC Merced
Conferences
Selected talks and posters across AI for science, quantum materials, and hybrid perovskites.
AI Science at Scale Annual MeetingSanta Fe, New Mexico
UC Merced School of Engineering Industry DayMerced, California
APS Global Physics SummitDenver, Colorado
APS Global Physics SummitAnaheim, California
MRS Spring Meeting & ExhibitSeattle, Washington
APS March MeetingLas Vegas, Nevada
APS March MeetingChicago, Illinois
Molecular Foundry User MeetingOnline · hosted by Lawrence Berkeley National Laboratory
APS March MeetingOnline
Molecular Foundry User MeetingOnline · hosted by Lawrence Berkeley National Laboratory
Workshop on Recent Developments in Electronic Structure MethodsUniversity of California, Merced
APS March Meeting · presentation cancelled due to COVID-19Denver, Colorado
APS March MeetingBoston, Massachusetts
Molecular Foundry User MeetingLawrence Berkeley National Laboratory · Berkeley, California
APS Bridge Program and National Mentoring Community ConferenceStanford University and Google headquarters · California
Additional experience
Approximately two years
Built a foundation through sustained Coursera coursework, moving from core machine-learning ideas to practical modeling and neural networks.
Two-week intensive institute · LLNL
Applied that training in a multidisciplinary molecular-binding project using exploratory analysis, feature engineering, random forests, support-vector machines, and a three-dimensional convolutional neural network.
Foundations
Formative projects that developed my experimental, atomistic, and first-principles perspective.
M.Sc. Applied Physics · 2009
An experimental investigation of critical behavior in binary-fluid mixtures at IIEST Shibpur.
M.Tech. Materials Engineering · 2011
Studied ground-state properties of homo- and hetero-clusters of group-IV elements with the IACS Kolkata research group.
Graduate research · 2016–2017
Used molecular dynamics in LAMMPS to investigate water-mediated interactions in sliding MoS₂ interfaces.