Ritesh Kumar - AI for Energy
About Research Publications CV
Ritesh Kumar - AI for Energy

About

Indian Institute of Science, Bangalore, India | August 2017 – January 2022
Advisor: Prof. Abhishek Singh
Thesis: Rational design of efficient catalysts using first-principles and machine learning

Indian Institute of Science, Bangalore, India | July 2015 – July 2017
Advisor: Prof. Abhishek Singh
Thesis: Earth-abundant electro- and photocatalysts as energy alternatives: An ab initio study

Sri Venkateswara College (University of Delhi), New Delhi, India | July 2012 – April 2015
First Division

Eric & Wendy Schmidt AI in Science Fellow

University of Chicago, Pritzker School of Molecular Engineering | January 2022 – Present
Advisor: Prof. Chibueze Amanchukwu

Research Focus:

  • Developing custom machine learning techniques for electrolyte discovery for next-generation batteries
  • Building the largest liquid electrolyte databases for accelerated materials discovery
  • Enhancing Bayesian optimization for real-world discovery in data-scarce and noisy-label settings
  • Developing generative AI and unsupervised frameworks for molecular discovery
  • Elucidating atomistic insights into experimental electrolyte performance using ab initio molecular dynamics
  • Formulating computational descriptors to explain aprotic electrolyte effects in industrial reactions (CO₂/CO reduction)

Software Development:

  • Co-developed AtomBridge: Automated conversion of STEM images to crystal structures using LLMs and computer vision (GitHub)
  • Led development of curAItor-agent: Automated scientific data extraction using LLMs and AI agents (GitHub)

Awards & Honors

  • CAS Future Leader Top 100 Award, American Chemical Society (March 2025)
  • Selected for Future Faculty Mentoring Program, AIChE (October 2025)
  • Eric & Wendy Schmidt AI in Science Postdoctoral Fellow ($80,000/year, January 2023 – January 2026)
  • Selected for Oxford Research Software Engineering (OxRSE) Workshop, University of Oxford (June 2024 & September 2025)
  • All India Rank 38 in IIT-Joint Admission test for Master’s (IIT-JAM) Examination (February 2015)
  • IASc-INSA-NASI Summer Research Fellowship (May 2014 – July 2014)

Funding agency: Data Science Institute, University of Chicago
Role: PI
Amount: $10,000
Project: Self-driving battery lab to accelerate scientific discovery

Funding agency: University of Chicago Women’s Board
Role: Co-I
Amount: $50,000
Project: AI-guided autonomous high-throughput battery manufacturing platform

  • Organizer: AI+Science Schmidt Fellows Speaker Series (2023-2025)
  • Session Chair & Organizer: AI+Science Summer School, University of Chicago (2024)
  • Reviewer: Nature Communications, ACS Applied Energy Materials, Digital Discovery, JOSS, Catalysts
  • Discussion Leader: Computational Materials Science and Engineering Gordon Research Seminar (2024)
  • Judge: Student Slam Contest, 243rd ECS Meeting (2023)
  • Moderator: National Postdoctoral Association Community Forum (2023)

Skills & Expertise

Computational Methods:

  • Density Functional Theory (DFT)
  • Ab initio Molecular Dynamics (AIMD)
  • Machine Learning & Deep Learning
  • Bayesian Optimization
  • Generative AI

Programming & Tools:

  • Programming languages: Python, Matlab
  • DFT: VASP, Quantum ESPRESSO, Gaussian, CP2K
  • MD: LAMMPS
  • ML packages: PyTorch, TensorFlow, Scikit-learn
  • High-performance computing