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Shomik V

- Research Program Mentor

PhD candidate at Massachusetts Institute of Technology


Renewable energy (solar), heat transfer, computational materials science


I'm Shomik Verma, a graduate student at MIT in Mechanical Engineering. I'm interested in the future of energy, especially photovoltaics. I'm continually amazed by the elegance of PV and its potential to transform the world's energy landscape. I'm currently interested in how multi-scale modeling techniques can be used to optimize energy conversion technologies - from atomistic simulations at the nanoscale to improve PV cell performance to large-scale heat transfer modeling at the meter-scale for efficient system design. Outside of research, I play tabla (an Indian classical percussion instrument), I like to jam with fellow musicians and mix my own music. I also play basketball and badminton. In my free time I devour anything sci-fi.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Machine learning to optimize optical performance of solar cells

With the rise of large-scale materials databases such as the Materials Project and ICSD, a wealth of information is already available for many types of materials. However, these databases are often missing essential information about optical properties (such as absorption) as these calculations are expensive. One strategy is to use machine learning as a tool to speed up expensive calculations. This will allow high-throughput screening of large databases and identification of promising candidate materials for photovoltaic applications.

Novel applications of thermophotovoltaics

While conventional photovoltaic cells use light from the sun to generate electricity, another branch of photovoltaics, called thermophotovoltaics or TPV, use light from a heat source instead. This is beneficial as any unused light by the TPV cell can be reflected back to the heat source and reabsorbed, instead of lost. Recently, a surge of interest in TPV has pushed their efficiency above 40%, and models show efficiencies as high as 60% are feasible in the next few years. With these high efficiencies come boundless potential applications in power plant design, waste heat recovery, concentrated solar power, etc. This project would involve focusing on one such application and designing an efficient system that incorporates TPV cells.

Coding skills

Python, Matlab

Languages I know

Spanish, intermediate. Hindi, intermediate

Teaching experience

6 semesters as a teaching assistant for Statics and Mechanics of Materials at Duke University. Also tutored middle school competition math as a high schooler.


Work experience

Georgia Tech Nanoscale Thermal Radiation Lab (2019 - 2019)
Research Assistant


Duke University
BSE Bachelor of Science in Engineering (2019)
Cambridge University
MPhil Master of Philosophy (2020)
Materials Science
Imperial College London
MPhil Master of Philosophy
Materials Science
Massachusetts Institute of Technology
PhD Doctor of Philosophy candidate

Completed Projects

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