Dr. Sandip Giri

Computational Chemist | Postdoc Candidate

Specialized in molecular design, chemical space exploration, and machine learning-driven property prediction. Seeking postdoctoral position to advance cutting-edge research in computational chemistry and materials discovery.

Email +91-8609698075 Scholar ORCID GitHub LinkedIn

Core Research Expertise

            Chemical Space Exploration: Automated discovery methods using stochastic algorithms and neural network potentials
Molecular Design: Development of novel compounds for sustainable aviation fuels and organic optoelectronics (TADF emitters)
Machine Learning in Chemistry: Data-driven property prediction and ML potentials (AIQM2, MACE, AIMNet2)
Computational Methods: DFT, multi-scale modeling, surface hopping dynamics, and high-throughput virtual screening
Software Development: Extended PyAr framework for cluster generation and automated structure generation

        

Featured Achievements

Novel Molecule Discovery

Identified 20 novel hydrocarbon aviation fuel candidates and 42 synthesizable TADF emitters through automated chemical space exploration

Software Creation

Creator of HydroMol, a web-based platform for hydrocarbon visualization and chemical space exploration, developed and maintained https://github.com/anooplab/pyar during my PhD

Research Publication

7 peer-reviewed publications in high-impact journals (IF 3.3-5.2), plus 1 in minor revision and 1 preprint

Research Leadership

Mentored 8 MSc students; independently led multiple research projects from conception to publication

Education

PhD (Chemistry) from IIT Kharagpur; MSc from NIT Durgapur; Expertise in advanced computational chemistry

Technical Proficiency

Proficient in ORCA, Gaussian, SHARC, Python, and ML frameworks; Expert in HPC and workflow automation

Featured Projects

CSPilot – Agentic Computational Chemistry Platform

Creator and Lead Developer

Developed an AI-driven workflow platform integrating ORCA, xTB, Multiwfn, global minima discovery, catalyst design tools (stk, ASE, AGAPI), LangGraph, and open source tools
Implemented automated molecular generation, workflow planning, verification, and reporting capabilities
Supports comprehensive quantum chemistry workflows, structure generation, and agent-based execution
Technical Stack: LangGraph, PyTorch, Streamlit web server, agent building, NLP, Language models, MongoDB

Resources: GitHub Repository | Documentation | DOI: 10.5281/zenodo.20568039

Recent Publications

Computational Exploration of Small Hydrocarbon Networks

Journal of Computational Chemistry

Vol. 46(25), e70236 (2025) | DOI: 10.1002/jcc.70236

Exploring the Chemical Space of Non-Covalent Molecular Clusters

Journal of Computational Chemistry

Vol. 46(32), e70287 (2025) | DOI: 10.1002/jcc.70287

Data-Driven Exploration of Synthesizable Strained Hydrocarbons for Sustainable Aviation Fuels

Sustainable Energy and Fuels

(Accepted on 02-06-2026) | IF: 4.1| DOI: 10.1039/D6SE00364H

Chemical Space Exploration of Organic Donor-Acceptor TADF Emitters

Journal of Materials Chemistry C

(Accepted on 24-06-2026)| IF: 5.2| DOI: 10.1039/D6TC00707D

From Knowledge to Action: Outcomes of the 2025 Large Language Models (LLM) Hackathon for Applications in Materials Science and Chemistry

Digital Discovery

https://arxiv.org/pdf/2605.03205

Computational Investigation of Meso-Substituted, Heavy Atom-Free BODIPY Derivatives as Photosensitizers: Insights From TDDFT and Dynamics Studies

Chemistry - An Asian Journal

Vol. 20, e202401325 (2025) | IF: 3.3 | DOI: 10.1002/asia.202401325

Selective synthesis of the missing tiara-like Ni10, Ni5, and Ni6 thiolates by the C-S bond cleavage of bis(thioether) molecules with a DFT study

Dalton Transactions

Vol. 53, 14875-14886 (2024) | IF: 3.3 | DOI: 10.1039/d4dt02047b

Exploring the Conformational Space of a Sulfonyl-Based Ionic Liquid on Platinum-Based Mono and Bimetallic Surfaces

Langmuir

Vol. 41, 3187-3198 (2025) | IF: 3.9 | DOI: 10.1021/acs.langmuir.4c03883

Hydrogen Bond-Assisted Excited State Switching and Fluoride Responsive Behavior of Orthogonal Spiroborate Ester Derived from Naturally Occurring α-Mangostin

European Journal of Organic Chemistry

Vol. 28(21), e202401411 (2025) | DOI: 10.1002/ejoc.202401411

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