Hemanth Neelgund Ramesh

I am a PhD student in Mechanical Engineering at the University of Washington, advised by Prof. Shijing Sun and Prof. Aniruddh Vashishth. I am currently a research intern at Microsoft Research in Redmond, working with the Deep Learning Group.

In past life, I worked on the physics and chemistry of batteries and electrolyzers. I developed diffusion models with Amazon, LLM-based extraction tools with PNNL, and methods for materials development. I was fortunate to contribute to a paper with Nobel Laureate M. Stanley Whittingham.

I received my M.S. from the UW and my B.Tech. from NITK Surathkal, both in Materials Science and Engineering.

Research interest: I am interested in building scientific AI agents and collaborative robots that accelerate discovery in materials science by combining reinforcement learning, self-evolving algorithms, and autonomous experimentation.

Full list on Google Scholar. (* equal contribution)

1. Hemanth Neelgund Ramesh, Shijing Sun, Chyi-Fu Hong, André Snoeck. Conditional Diffusion Models for Energy Efficient Routing. Submitted to Amazon internal conference.
2. H Neelgund Ramesh, S Sun, G Cao. Decoupling complex cell aging with explainable machine learning: a perspective, Journal of Physics: Energy, 8(2), 021001, 2026.
3. S Cheng, X Cui, HN Ramesh, WC Chueh, S Sun. Small-data machine learning for resolving degradation challenges in energy devices, APL Machine Learning, 4(2), 2026.
4. Y Lin, HN Ramesh, AJ Gironda, L Lin, X Jia, Y Guo, GT Seidler, T Hu, et al. K+ pre-intercalated hydrate vanadium pentoxide as cathode for enhanced stability and kinetics in sodium ion batteries, Journal of Power Sources, 653, 237766, 2025.
5. J Xiao, X Cao, B Gridley, W Golden, Y Ji, S Johnson, D Lu, F Lin, J Liu, et al. From mining to manufacturing: scientific challenges and opportunities behind battery production, Chemical Reviews, 125(13), 6397–6431, 2025.
6. S Mondal, H Neelgund Ramesh, X Ma, S Cheng, T Angeles, S Sun. Reducing Electric Vehicle Range Anxiety with Trip-Specific Charge Usage Predictions, ChemRxiv, 2025.
7. RD Mohili, K Mahabari, M Patel, NR Hemanth, AH Jadhav, K Lee, et al. HF-free low-temperature synthesis of MXene for electrochemical hydrogen production, Nanotechnology, 36(10), 105401, 2025.
8. HN Ramesh. Understanding the Impact of Cycling Parameters on Cell Ageing Using Explainable Machine Learning, University of Washington, 2024. (Thesis)
9. R Mohili, NR Hemanth, K Lee, NK Chaudhari. MXene-transition metal compound sulfide and phosphide hetero-nanostructures for photoelectrochemical water splitting, Solar-Driven Green Hydrogen Generation and Storage, 129–139, 2023. (Book Chapter)
10. R Mohili*, NR Hemanth*, H Jin*, K Lee, N Chaudhari. Emerging high entropy metal sulphides and phosphides for electrochemical water splitting, Journal of Materials Chemistry A, 11(20), 10463–10472, 2023.
11. M Patel, NR Hemanth, J Gosai, R Mohili, A Solanki, M Roy, B Fang, et al. MXenes: promising 2D memristor materials for neuromorphic computing components, Trends in Chemistry, 4(9), 835–849, 2022.
12. NR Hemanth*, RD Mohili*, M Patel, AH Jadhav, K Lee, NK Chaudhari. Metallic nanosponges for energy storage and conversion applications, Journal of Materials Chemistry A, 10(27), 14221–14246, 2022.
13. NR Hemanth*, T Kim*, B Kim*, AH Jadhav, K Lee, NK Chaudhari. Transition metal dichalcogenide-decorated MXenes: promising hybrid electrodes for energy storage and conversion applications, Materials Chemistry Frontiers, 5(8), 3298–3321, 2021.
14. RP Magisetty, H NR, A Shukla, R Shunmugam, B Kandasubramanian. Poly(1,6-heptadiyne)/NiFe2O4 composite as capacitor for miniaturized electronics, Polymer-Plastics Technology and Materials, 59(18), 2018–2026, 2020.
15. NR Hemanth, B Kandasubramanian. Recent advances in 2D MXenes for enhanced cation intercalation in energy harvesting applications: a review, Chemical Engineering Journal, 392, 123678, 2020.
16. RP Magisetty, NR Hemanth, P Kumar, A Shukla, R Shunmugam, et al. Multifunctional conjugated 1,6-heptadiynes and its derivatives stimulated molecular electronics: Future moletronics, European Polymer Journal, 124, 109467, 2020.

Awards & Fellowships

• Herbold Data Science Fellowship (2024–2025) — 1 of 5 recipients across the entire UW graduate school.
• Mechanical Engineering Departmental Fellowship (2024–2025) — awarded to an outstanding incoming graduate student at ME UW.

Invited Talks & Posters

• Amazon Machine Learning Conference, Seattle (Oct 2025) — Invited Poster Presentation
• Collaboration for Autonomous Science Instruments Workshop, San Diego (Oct 2025) — Invited Talk
• Emerging Ideas in AI for Materials and Mechanical Design, Duke University (Jul 2025) — Invited Poster Presentation
• Artificial Intelligence and Machine Learning for Materials, Purdue University & Los Alamos National Laboratory (May 2025) — Invited Poster Presentation
• American Chemical Society Spring 2025, San Diego (Mar 2025) — Selected Oral Presentation

Teaching

• Graduate Chemistry Tutor, STARS Program, University of Washington (February – June 2023)
  • Taught Chemistry 142 and Chemistry 152 for ∼30 students.
  • Mentored highly motivated Washington state residents from low-income backgrounds & under-served high schools to graduate with degrees in engineering and computer science.

Yes another Jon Barron's source code.