Hello, I am Avanish Mishra
Staff Scientist at Los Alamos National Laboratory — integrating first-principles methods and molecular dynamics with machine learning and quantum computing to accelerate materials discovery
Atomistic to continuum
AI/ML-driven discovery
For chemistry & materials
Simulation ↔ experiment
I am a staff scientist in the Theoretical Division at Los Alamos National Laboratory, specializing in the design of structural materials for extreme environments and functional materials for energy-to-electronics applications.
My work integrates first-principles methods (DFT, VASP, Quantum ESPRESSO) and molecular dynamics (LAMMPS) with emerging paradigms such as machine learning — including graph neural networks, generative AI, active learning, and large language models — and quantum computing (Qiskit, pySCF) to accelerate materials discovery.
I have contributed to open data infrastructure (aNANt database, JARVIS-Leaderboard, URSA) and authored 37+ peer-reviewed publications with 2,330+ citations and an h-index of 17.
Ph.D. Materials Science
Indian Institute of Science, Bangalore
(2014–2019)
M.Sc. Physics · B.Sc. Physics, Math & Chemistry — DDU Gorakhpur University
Director's Postdoc Fellow — LANL, 2022
Science in 3 (Top 30 postdocs) · Kawazoe Prize · GATE AIR 36 · CSIR-NET AIR 58
DFT · MD · VASP · LAMMPS · Quantum ESPRESSO
pySCF · Qiskit · ASE · GenAI · LLMs · Agentic AI
TMS · APS · MRS · ICME
Symposium co-organizer: TMS 2025 & 2026 AI-ICME
Leveraging artificial intelligence, machine learning, and quantum computing to solve the hardest problems in materials science
Data-driven discovery fusing physics-based descriptors with ML models. Active learning, graph neural networks, and explainable AI for accelerated materials design.
Learn more →Hybrid quantum–classical strategies for correlated materials. Variational algorithms, error mitigation, and domain-specific workflows for catalysis and energy storage.
Learn more →Predictive models for extreme environments — fusion reactors, shock deformation, and radiation damage. Multiscale simulations from atoms to continuum.
Learn more →Engineering materials from bulk to 2D — complex oxides, heterostructures, and hybrids for energy, electronics, and photonics.
Learn more →Computational tools for texture analysis, diffraction simulation, and orientation relationships from atomistic data.
Learn more →A selection of recent contributions to AI-driven materials science
Leading research in materials informatics, quantum computing for chemistry, generative AI for process–structure mapping, and virtual characterization tools.
Developed physics-informed ML for grain boundary property prediction using strain functional descriptors. Selected as one of 30 postdocs for "Science in 3" at LANL.
Pioneered virtual characterization tools for shock-induced deformations, phase transformation mechanisms, and diffraction fingerprinting in dynamic loading.
Dissertation: "Exploration of exfoliation, functionalization and properties of MXenes via first-principles and machine learning."
Codes, databases, and AI-powered tools I've developed and contributed to
India's first computational materials database — 23,000+ MXenes with optimized structures and electronic properties for ML training.
Database · ML-Ready · Ph.D.Python package for virtual texture analysis from atomistic microstructures: orientation relationships, misorientations, Schmid factors.
Python · AnalysisOfficial contributor to NIST's benchmarking platform for materials science ML methods and AI models.
NIST · AI BenchmarkingContributor to LANL's Universal Research and Scientific Agent — an AI-powered research assistant for scientific discovery.
LANL · LLM AgentOur interdisciplinary team at Los Alamos National Laboratory
Staff Scientist, Theoretical Division, LANL
Co-advised with Dr. Yu Zhang, LANL
We are actively recruiting motivated researchers at all levels who are passionate about AI, quantum computing, and materials science
Send your CV and a brief statement of research interests.
Work at the forefront of AI + materials science at one of the world's premier research laboratories. Our group offers a unique combination of cutting-edge science, world-class computing resources, and a collaborative, mentorship-driven environment.
Access to LANL supercomputers & quantum hardware
AI, quantum computing, physics & chemistry
Mentorship & pathways to staff positions
Located in beautiful Northern New Mexico
Open to Non-sensitive Foreign Nationals, Permanent Residents, and US Citizens.
Interested in collaboration, open positions, or quantum materials research?