Anshuman Kumar

Anshuman Kumar

Postdoctoral Scholar, SME

University of California, Davis

OpenAI

Biography

Hi, welcome to my website.

I am a postdoctoral scholar at UC, Davis working with Prof. Ambar Kulkarni in advancing computational catalysis approaches via machine learning. I worked as a subject-matter expert (SME) with OpenAI. I completed my PhD in computational materials science at University of California, Riverside in 2023 under Prof. Bryan Wong. Earlier, I was a software engineer at Accenture.

Download my CV.

You can read my PhD dissertation here.

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Interests
  • Machine Learning
  • Data Science
  • Computational Chemistry
  • Computational Materials
  • High Performance Computing
Education
  • PhD in Computational Materials Science, 2023

    University of California, Riverside, USA

  • MS in Electrical Engineering, 2017

    University of California, Riverside, USA

  • BE in Electronics and Communication Engineering, 2011

    Manipal Institute of Technology, Karnataka, India

Skills

Python
C/C++
Java
SQL
CUDA
TensorFlow
PyTorch
Pandas
OpenCV
R
Docker
Plotly
Statistics
Computational Chemistry
Molecular Dynamics

Experience

 
 
 
 
 
Postdoctoral Scholar
University of California, Davis
June 2024 – Present California

Responsibilities include:

  • Implementation and integration of ML approaches for computational catalysis
 
 
 
 
 
Engineer, SME
OpenAI (contract)
June 2024 – August 2024 California

Responsibilities include:

  • Prompt engineering, subject matter expert in Computational Sciences (Physics, Chemistry, Materials), Fluid Dynamics, Robotics, and programming.
 
 
 
 
 
Reviewer
NeurIPS, Machine Learning- Science and Technology, Journal of Open Source Software (JOSS)
May 2024 – Present

Responsibilities include:

  • Reviewing papers/codes on application of ML in science and tech; Reviewing softwares at JOSS
 
 
 
 
 
Postdoctoral Associate
University of California, Riverside
July 2023 – May 2024 California

Responsibilities include:

  • Development of Regression and generative AI models to predict the band gap of 1-D and 2-D polymers based on their composition and crystal structure
  • Optimization and development of machine learning potential in density functional theory and molecular dynamics calculations
  • Enabling Clustering Algorithm for the screening of multi-component elements and high-entropy alloys, which are novel materials with high performance and stability
 
 
 
 
 
Research Assistant
University of California, Riverside
September 2017 – March 2023 California

Responsibilities include:

  • Development, Implementation, and Integration of Quantum Methods (DFT, DFTB, TD-DFT)
  • Atomistic Modelling, Electronics Structure, Electronic Transport, Molecular Dynamics, Metadynamics and Computational Chemistry, Range-separated Functional
  • High Performance Computing on clusters (eg., SDSC Access, Texas Stampede, John Hopkins Rockfish)
  • Published 11 peer-reviewed journal articles, 1 book chapter, and 2 conference proceedings during my Ph.D.
 
 
 
 
 
Data Analyst / Senior Software Engineer
Accenture
June 2011 – August 2015 Bangalore, India

Responsibilities include:

  • Development and deployment of Cisco’s Quote-to-Order (Q2O) web application in java
  • Designed and implemented phishing security vulnerabilities on web browsers using javascript
  • Derived insights into user behavior using Data Analysis with Python and SQL
  • Translated business requirements into technical specifications

Recent Publications

To view my complete list of publications, please visit my Google Scholar profile.

Awards

  • Dissertation Year Program Fellowship       University of California, Riverside      2021 & 2022

  • Department Fellowship, MSE                       University of California, Riverside      2017

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