Awesome AI for Science
📄
Papers
🧭
Topics
🔥
Trending
🗺️
Map
🏆
Leaderboards
🎓
Learn
🤖
Ask AI
⋯
More
👥
Authors
📚
Reading Packs
📊
Datasets
🛠️
Tools
📰
News
📝
Blogs
✉️
Newsletter
🎯
Research Radar
🔖
Saved
+ Add Paper
☾
☀
← authors
·
overview
Loading author…
🤖
Ask AI
Apurba Nandi — most-cited papers & profile · AI for Science
← authors
·
overview
Apurba Nandi
10
papers ·
2
citations ·
21
h-index
University of Engineering & Management · Emory University · University of Luxembourg
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Extending the atomic decomposition and many-body representation, a chemistry-motivated monomer-centered approach for machine learning potentials
2024 · 1 citations
The quantum nature of ubiquitous vibrational features revealed for ethylene glycol
2025 · 1 citations
Fidelity of Machine Learned Potentials: Quantitative Assessment for Protonated Oxalate
2026
VPT2 Calculations of Vibrational Energies of CH3COOC6H4COOH Done in Seconds on a Laptop Using a Machine Learned Potential
2026
"Gold-Standard" $Δ$-Machine Learned and Transferable Potential for Linear Alkanes
2025
$Δ$-Machine Learning to Elevate DFT-based Potentials and a Force Field to the CCSD(T) Level Illustrated for Ethanol
2024
Permutationally invariant polynomial regression for energies and gradients, using reverse differentiation, achieves orders of magnitude speed-up with high precision compared to other machine learning methods
2021
Quantum calculations on a new CCSD(T) machine-learned PES reveal the leaky nature of gas-phase $trans$ and $gauche$ ethanol conformers
2022
A Machine Learning Approach for Rate Constants III: Application to the Cl($^2$P) + CH$_4$ $i̊ghtarrow$ CH$_3$ + HCl Reaction
2022
No Headache for PIPs: A PIP Potential for Aspirin Outperforms Other Machine-Learned Potentials
2024
Top co-authors
Riccardo Conte
· 7
Paul L. Houston
· 6
and Joel M. Bowman
· 5
Chen Qu
· 5
Priyanka Pandey
· 4
Joel M. Bowman
· 3
Qi Yu
· 3
Qi Yu
· 3
Chen Qu
· 2
Paul L. Houston
· 2
Alexandre Tkatchenko
· 1
and Markus Meuwly
· 1
Topics
Chemistry
Physics ML
Materials
Drug Discovery