SLAC National Accelerator Laboratory
Showing 1-50 of 70 Results
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Changzhi Ai
Postdoctoral Scholar, Photon Science, SLAC
BioChangzhi Ai is a Postdoctoral Researcher at the SUNCAT Center for Interface Science and Catalysis at Stanford University and SLAC National Accelerator Laboratory. He specializes in developing machine learning models for surface and interfacial chemistry, with broader expertise in atomistic modeling for materials science and chemistry. His research also explores agentic AI for scientific discovery, automation of active learning workflows, global optimization algorithms, and high-throughput materials screening. He obtained his PhD from the Technical University of Denmark.
His current research focuses on the development of scalable, physically informed machine learning potentials, particularly equivariant neural network architectures, for accurately modeling complex chemical environments. His work spans heterogeneous catalysis, multi-metallic alloy design, reaction kinetics, and surface and interfacial chemistry, with an emphasis on uncovering structure–property relationships at the atomic scale.
In addition, he has extensive experience integrating machine learning models into simulation pipelines and deploying them in large-scale computational environments. His technical expertise includes deep learning frameworks such as PyTorch, distributed training (DDP and multi-node GPU systems), and scientific computing tools including LAMMPS, ASE, and TorchScript/LibTorch for production-level deployment. He also develops end-to-end automated workflows for data generation, model training, and adaptive sampling in materials discovery.
Keywords:
Machine Learning Potentials (Equivariant GNNs), Atomistic Simulations, Molecular Dynamics, Active Learning & Workflow Automation, High-Throughput Screening, Global Optimization Algorithms, Scientific Machine Learning, Distributed GPU Computing, PyTorch & TorchScript, LAMMPS Integration, ASE, HPC Systems, Data-Driven Materials Discovery
Code & Projects:
GitHub: https://github.com/changzhiai -
Suman Bhasker Ranganath
Postdoctoral Scholar, Photon Science, SLAC
Current Research and Scholarly InterestsDevelopment of machine-learning models from high-throughput catalysis simulations.
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Igor Daniel de Araujo Evangelista
Postdoctoral Scholar, Photon Science, SLAC
BioDr. Evangelista's primary research focus lies in computational modeling and theoretical analysis of semiconductor materials using advanced quantum mechanical methods, including Density Functional Theory, Quantum Monte Carlo, and ab-initio Molecular Dynamics. Evangelista investigates the electronic, structural, and mechanical properties of materials, collaborating closely with experimental groups to bridge theoretical predictions with empirical results. He is also interested in the development of empirical potentials and enhancing materials modeling through the application of machine learning techniques.
Evangelista entered the Department of Materials Science and Engineering at the University of Delaware as a Ph.D. candidate in 2018, after completing an master degree in Physics 2016-2018 at Federal Fluminense University (Brazil). Recent work includes collaborations with experimental groups to bridge theoretical predictions with empirical results, as well as applying machine learning to creating of empirical potentials to accelerate materials modeling. Evangelista has also contributed to understanding electron mobility in metal-oxide semiconductors and strain effects in two-dimensional materials. These studies showcase his expertise in electronic structure and materials design for next-generation semiconductor technologies. -
Maitrayee Ghosh
Postdoctoral Scholar, Photon Science, SLAC
BioI am a postdoctoral scholar at the High Energy Density Sciences Division in the SLAC National Accelerator Laboratory in the Stanford University. I have received my PhD from the University of Rochester in 2023 in high-pressure chemistry. My research interests include theoretical and computational investigations of materials in both ambient and high-pressure regimes, that can be relevant for planetary sciences and inertial confinement fusion. I hail from Kolkata, India, and enjoy reading fictions and traveling in my leisure.
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Sheikh Rubaiat Ul Haque
Postdoctoral Scholar, Photon Science, SLAC
BioRubaiat received his undergraduate degree in Applied Physics from the University of Tokyo in 2017. He then moved to the University of California San Diego where he finished his PhD in Physics under Professor Richard Averitt in 2023. During his PhD, he discovered light-induced terahertz parametric amplification and photonic time crystal state in excitonic insulator candidate Ta2NiSe5. He has also demonstrated efficient nonresonant nonlinear magnon generation in a Mott insulating Heisenberg antiferromagnet Sr2IrO4 as well as broadband optical control of plasmonic modes in semiconducting metamaterials.
Currently, Rubaiat is a postdoctoral scholar at Stanford University working on terahertz field-induced ultrafast dynamics in van der Waals magnets under the guidance of Professors Tony Heinz and Aaron Lindenberg. He has shown that intense terahertz pulses can modulate symmetry and drive transitions to a hidden ferrimagnetic state in van der Waals antiferrognet MnPS3. He has recently extended his research to THz spectroscopy of 2D materials. His broader interests also include cavity control and Floquet/Kapitza engineering of quantum materials. -
Sathya Narayanan Jagadeesan
Postdoctoral Scholar, Photon Science, SLAC
BioSathya Narayanan Jagadeesan is a postdoctoral scholar at the SLAC-Stanford Battery Center, with joint appointments in the Applied Energy Division at SLAC National Accelerator Laboratory and the Department of Materials Science and Engineering at Stanford University. He earned his Ph.D. in Chemical Engineering from Worcester Polytechnic Institute. His research focuses on earth-abundant and non-critical battery chemistries, including aqueous iron, sodium-sulfur, and sodium-ion systems, using advanced synchrotron X-ray characterization and data-driven approaches to understand interfacial chemistry and degradation mechanisms. His work aims to advance scalable and resilient energy storage technologies that reduce reliance on critical materials and strengthen the reliability of modern electric grids. He is driven by translating fundamental insights into practical solutions that support long-duration and widely deployable energy storage.
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Jiarui Li
Postdoctoral Scholar, Photon Science, SLAC
BioI am currently a postdoctoral condensed matter experimentalist, material physicist, optical spectroscopist, and X-ray scatterer at Stanford University and SLAC National Lab. At Stanford, I work jointly with Harold Hwang and Wei-Sheng Lee on investigating the complex interplay between charge, spin, lattice, and orbital degrees of freedom in functional oxide quantum materials under extreme (strain) conditions. My expertise lies in the use of scattering, spectroscopy and imaging techniques to investigate materials, utilizing a range of photon sources from high-brightness X-rays generated at large synchrotron light sources, to lab laser source.
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Christopher J. Miller
Postdoctoral Scholar, Photon Science, SLAC
BioI am a chemist and Postdoctoral Scholar at SLAC National Accelerator Laboratory, where my research focuses on the core challenges of electrochemical energy conversion and sustainable chemistry. Working within the DOE BETO CO2RUe consortium, I investigate the dynamic behavior of catalysts in CO₂ electrolyzers. My primary approach involves using advanced operando characterization techniques, particularly X-ray Absorption Spectroscopy (XAS), to build comprehensive models that link a catalyst's atomic-scale structure to its real-world device performance.
My philosophy is that progress requires bridging fundamental science with practical systems engineering. To that end, my expertise includes the ground-up design, construction, and automation of experimental systems. I specialize in building fully integrated electrochemical test stations and gas delivery infrastructure, tailored to deliver high-quality, reproducible data with robust safety features and remote-operation capabilities. Complementing this hardware, I develop custom MATLAB software suites to automate data processing and analysis, significantly accelerating the path from raw data to actionable scientific insight.
In addition to my research, I am deeply committed to education and professional service. As a recent fellow in Stanford's Preparing Future Professors (PFP) program, I received formal training in pedagogy and gained direct mentorship experience at San Jose State University. This commitment extends to the broader scientific community through my long-standing leadership roles within the American Chemical Society (ACS), where I contribute to governance, chemical safety initiatives, and professional development for younger chemists. I am always interested in discussing new collaborations at the intersection of spectroscopy, catalysis, and system design.
