Autonomous materials design
Physics-informed, uncertainty-aware and generative learning frameworks that connect composition, processing, microstructure and performance.
- Active learning
- Inverse design
- Uncertainty
Materials scientist · Düsseldorf
Designing metals that learn, adapt, and endure.
Group Leader for Artificial Intelligence in Materials Science at the Max Planck Institute for Sustainable Materials—bridging physical metallurgy, autonomous materials design and sustainable processing.
Nature CommunicationsAdvanced ScienceActa Materialia
Research atlas / 01
From physical mechanisms to autonomous discovery.
My research connects metallurgical insight with modern computational intelligence. The goal is not prediction alone, but experimentally grounded design rules that remain interpretable, transferable and useful.
Sustainable metallurgy
Scrap-tolerant alloy design, circular processing and machine-guided strategies that reduce reliance on primary critical resources.
- Circular alloys
- Residual Cu
- Critical materials
Green steelmaking
Mechanistically interpretable models of hydrogen-based direct reduction, bridging transformation kinetics and process intensification.
- HyDR
- Kinetics
- Constitutive learning
Complex metallic systems
Composition–structure–property relations in metallic glasses, high-entropy alloys and other compositionally complex materials.
- Metallic glasses
- HEAs
- Mechanical behavior
Selected work / 02
Research built across disciplinary boundaries.
Attention-enhanced variational learning for physically informed discovery of exceptionally hard multicomponent bulk metallic glasses
A. Bajpai, J. Wang, B. Ratzker, B. M. Sesen, F. Kark & D. Raabe
Coupled influence of structural relaxation and compositional complexity on deformation behavior and intermittent plasticity in Cu–Zr-based metallic glasses
A. Bajpai, J. Wang, B. Ratzker, R. Miyar, H. Holz, N. P. Gurao, K. Biswas & D. Raabe
Physics-constrained constitutive learning of rate-limiting timescales for efficient hydrogen-based direct reduction for green steelmaking
A. Bajpai, B. Ratzker, P. Cavaliere & D. Raabe
Compositional complexity buffers free-volume sensitivity and serrated flow in metallic glasses
A. Bajpai, J. Wang & D. Raabe
Deformation zone connectivity governs time-dependent load relaxation in Cu–Zr-based metallic glasses
A. Bajpai, J. Wang & D. Raabe
Active learning strategies for design of sustainable alloys
Z. Rao*, A. Bajpai* & H. Zhang · *equal contribution
22 peer-reviewed publications
12 first / equal-first author works
01 research monograph
01 published patent
Leadership / 03
Building research systems—and the teams behind them.
At MPI-SusMat, I coordinate researchers across machine learning, thermodynamics, microstructure analysis, alloy processing and structural properties, with a focus on coherent computational– experimental workflows.
AI × metallurgy06researchers
3Postdoctoral researchers
1PhD researcher
2Master’s students
Scientific direction
Research planning, framework development, technical mentoring and integration of physical modelling with experimental validation.
Collaborative programmes
PI-level materials-design work packages and international proposals in sustainable alloys, autonomous metallurgy and causal materials design.
Professional service
Symposium co-organization, guest editing, peer review and early-career mentoring across materials science and machine intelligence.
Trajectory / 04
A practice shaped by research and engineering.
From industrial vehicle engineering to physical metallurgy and autonomous materials discovery, each stage adds a distinct systems-level perspective.
2024—presentCurrent
Group Leader · Artificial Intelligence for Materials Science
Max Planck Institute for Sustainable Materials · Düsseldorf
Leading an international multidisciplinary team and developing physics-informed, uncertainty-aware workflows for autonomous metallurgy.
2024—2026
Alexander von Humboldt Postdoctoral Fellow
Max Planck Institute for Sustainble Materials · Düsseldorf
Integrated thermodynamic reasoning, experimental metallurgy and interpretable machine learning across metallic materials systems.
2023—2024
Max Planck Gesellschaft Postdoctoral Fellow
Max Planck Institute for Iron Research · Düsseldorf
Integrated thermodynamic reasoning, experimental metallurgy and interpretable machine learning across metallic materials systems.
2017—2023
M.Tech–PhD Dual Degree · Materials Science and Engineering
Indian Institute of Technology Kanpur · India
Compositional design, thermal stability and mechanical behavior of multicomponent metallic glasses. GPA 8.3/10.
2015—2016
Technical Manager · Vehicle Layout Operations
Tata Motors · India
Engineering experience in vehicle layout operations before doctoral research.
2011—2015
Bachelor of Engineering · Materials and Metallurgical Engineering
Punjab Engineering College, Chandigarh · India
Foundation in metallurgical engineering and materials processing. GPA 7.7/10.
Recognition / 05
Selected honours and research distinctions.
Recognition spanning international fellowships, journal distinctions, invited scholarship and award-winning research communication.
Editors’ Highlight
Nature Communications · Materials science and chemistry theme
Editor’s Choice Article
Computational Materials Science · April 2026
Alexander von Humboldt Fellowship
Postdoctoral research at MPI-SusMat
Max Planck Gesellschaft Fellowship
Postdoctoral research at MPIE
Journal of Materials Research cover
Machine-learning-assisted design of multicomponent metallic glasses
ACS Sustainable Chemistry & Engineering cover
Conducting graphene synthesis from electronic waste
Methods / 06
One research language, multiple scales.
The work moves deliberately between computation, thermodynamics, processing and characterization—because robust materials design rarely lives inside a single method.
Computational materials science
CALPHAD-informed thermodynamics · atomistic simulation · molecular dynamics · composition–processing–property modelling
Machine learning
Active learning · transfer learning · generative modelling · uncertainty quantification · symbolic regression · model interpretation
Experimental metallurgy
Vacuum arc melting · mechanical alloying · cryomilling · heat-treatment design · mechanical characterization
Characterization
Synchrotron XRD · SEM · EPMA · DSC · nanoindentation · AFM · Raman · XPS · microstructure quantification
Beneficiation and Management of Technological Waste
CRC Press · with Krishanu Biswas and Arunabh Meshram
Electric switch casing from waste printed circuit boards
Published Indian patent application · 202411011268
Contact / Düsseldorf
Let’s build better materials—and better ways to discover them.
I welcome conversations on autonomous materials design, sustainable metallurgy, complex metallic systems and collaborative research programmes.
Institution
Max Planck Institute for Sustainable Materials
Location
Düsseldorf, Germany
Profiles