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Willie John PadillaView profile

Professor

• Electromagnetic metamaterials
• Metasurfaces
• Artificial intelligence
• +10 more

Willie John Padilla serves as the Dr. Paul Wang Distinguished Professor in the Department of Electrical and Computer Engineering at Duke University's Pratt School of Engineering. His research spans electromagnetic metamaterials and metasurfaces with applications across microwave, terahertz, and infrared frequencies. Dr. Padilla leads the Padilla Lab, which specializes in THz, infrared, optical and magneto-optic properties of novel materials using various spectroscopic methods. Ph.D. from University of California, San Diego (2004) Dr. Padilla's research focuses on theoretical, computational, and experimental investigation of electromagnetic metamaterials with particular emphasis on artificial intelligence and deep learning applications. His work explores the tailoring of thermal radiation beyond natural materials limitations, developing metamaterial emitters based on MEMS, graphene, and liquid crystals for controlled thermal emission. His lab investigates high-temperature metamaterials capable of withstanding extreme environments for thermal photovoltaic systems. Padilla's research bridges fundamental electromagnetic theory with practical applications in energy harvesting, computational imaging, and sensing technologies. His recent publications demonstrate a strong trend toward integrating machine learning with metamaterial design and characterization, particularly physics-informed learning approaches that combine domain knowledge with neural networks. This represents a significant shift in the field toward more efficient design methodologies that overcome traditional computational limitations in electromagnetic simulation. IEEE Fellow (2025) Optica Fellow (2013) Presidential Early Career Award for Scientists and Engineers (2009) Dr. Padilla actively mentors doctoral students including Yang Deng, Rixi Peng, and Natalie A Rozman, with research spanning from fundamental metamaterial physics to practical applications. His team includes Visiting Researcher Omar Khatib and Adjunct Assistant Professor Evan Runnerstrom, creating a multidisciplinary research environment that bridges electrical engineering, materials science, and computational methods. The Padilla Lab maintains strong focus on both fundamental research and practical applications, with particular emphasis on developing metamaterial solutions for energy harvesting, thermal management, and advanced imaging systems. Current projects include developing metamaterial emitters for controlled thermal radiation beyond the Stefan-Boltzmann law and exploring high-temperature metamaterial designs for extreme environment applications.

Vladimir G ZelevinskyView profile

Professor

• Mesoscopic Nuclear Physics
• Quantum Chaos
• Nuclear Structure and Reactions
• +2 more

Vladimir G. Zelevinsky is a Professor in the Department of Physics & Astronomy at Michigan State University's College of Natural Science, with research focused on mesoscopic nuclear systems. His work bridges nuclear structure, quantum chaos, and applications to quantum computing. His primary research interests explore the mesoscopic world between elementary particles and macroscopic bodies, specializing in quantum chaos in nuclei, continuum shell modeling, symmetries and phase transitions, and connections to quantum signal transmission. He investigates how weakly bound nuclei form quantum skins and halos, and develops theoretical frameworks coupling intrinsic properties with continuum effects. Analysis of his recent publications reveals a strong emphasis on exotic decay processes, resonance phenomena in light nuclei, quantum chaos signatures in level statistics, and applications of nuclear physics to fundamental symmetry tests. His work increasingly connects nuclear theory with quantum information science and condensed matter mesoscopic systems. His educational background includes a Ph.D. in Physics from the Budker Institute of Nuclear Physics (Novosibirsk) in 1964. While specific advising details aren't provided, his Continuum Shell Model collaborations with A. Volya represent significant theoretical contributions to nuclear reaction theory.

• IoT Security
• Machine Learning Applications in Cybersecurity
• Digital Twins for Critical Infrastructure Security
• +4 more

Dr Faiza Medjek is a Senior Lecturer in Cyber Security at the University of the West of England (UWE), co-leading the NCSC-Certified MSc Cyber Security program. Previously, she spent 18 years at CERIST research center, serving as both member and head of the Cyber-Physical System Security team. She holds a PhD focused on securing IPv6 RPL protocols in IoT environments, with research cited over 500 times. Research interests include: IoT Security with emphasis on intrusion detection and routing protocols Lightweight Machine Learning applications for real-time threat mitigation Digital Twins in critical infrastructure protection AI/Quantum cryptography integration for data integrity Trust management systems for vehicular networks Hardware acceleration in cybersecurity implementations Her publications ( 7 entries ) span IoT security frameworks, AI-driven defense mechanisms, and trust-based routing protocols. Research combines theoretical innovation with practical applications in healthcare and transportation sectors. Academic roles: Co-Programme Leader at UWE Journal reviewer Supervisor for undergraduate and postgraduate students

Hanchen WangView profile

Research Fellow

• Artificial Intelligence for Science
• Biomedical AI Agents
• Multi-omics Analysis
• +7 more

Hanchen Wang is a Postdoctoral Research Fellow at Stanford AI Lab and Genentech, working under Jure Leskovec and Aviv Regev. He holds a PhD in Computer Science from Cambridge University completed in 3 years under Joan Lasenby, and a BS in Physics from Nanjing University where he was valedictorian. His research bridges artificial intelligence and biomedical discovery, with appointments spanning both academic and industry settings. Wang's research focuses on AI for Science , particularly developing autonomous agents for biomedical discovery. His work spans multi-omics analysis , spatial transcriptomics , live-cell imaging , and perturbation assays , with applications in cancer therapeutics , autoimmune diseases , and neurological disorders . He has pioneered multiple AI agent frameworks including Biomni (a general-purpose biomedical agent), SpatialAgent, and PerTurboAgent for specialized biological discovery tasks. His publication record demonstrates significant impact across both computer science and biology venues, with first-author papers in Nature , Nature Biotechnology , and NeurIPS . His research has been deployed by Anthropic, Amazon Web Services, and Genentech, and featured in Nature , The Economist , and DeepMind communications. Chan Zuckerberg Initiative Faculty Applicant Bootcamp participant UCSF Gladstone Institute Trainee-to-Tenure Track Program member OpenAI Researcher Access Program recipient Multiple conference travel awards Wang actively mentors early-career researchers including PhD students from institutions like CSHL, MIT, Harvard, and KAIST. He serves as Area Chair for ICLR 2026, organizes workshops on AI for Science at major conferences, and gives invited talks at leading institutions including Harvard, Yale, and the Broad Institute. His research is supported by Genentech internal funding ($500k/year) and OpenAI resources.

• Computer Science
• Electrical Engineering
• Artificial Intelligence
• +3 more

Abu Sebastian is a Distinguished Research Scientist at IBM Research - Zurich and a Visiting Professor in Materials at the University of Oxford . With over 200 publications and 100 patents, he pioneered in-memory computing , neuromorphic systems , and phase-change memory technologies . His work has been recognized by the IEEE Control Systems Technology Award , ERC Grants , and Ovshinsky Lectureship . Education: B.E. (Hons.) in Electrical and Electronics Engineering from BITS Pilani, India M.S. and Ph.D. in Electrical Engineering with minor in Mathematics from Iowa State University Research Interests focus on AI hardware , analog computing , and emerging memory technologies . His groundbreaking work includes phase-change memory-based neural networks , neuro-vector symbolic architectures , and hybrid CMOS/memristive neuromorphic systems . Scientific Awards: IEEE Fellow ERC Advanced Grant (2025) Ovshinsky Lectureship (2019)

Ulya R. KarpuzcuView profile

Associate Professor

• Physics of Computing
• Energy-Efficient Computing
• Application-Domain Specialized Architectures
• +6 more

Ulya R. Karpuzcu is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Minnesota, Twin Cities. Her research spans physics of computing, energy-efficient computing, application-domain specialized architectures, hardware security and reliability, and approximate computing. Her research interests focus on understanding how physical principles shape computing paradigms to address emerging energy problems. Key areas include: Physics of computing and physical limits of computation Energy-efficient computing through novel architectures Hardware security and reliability Approximate computing techniques Spintronics and non-volatile memory computing Quantum computing architectures Dr. Karpuzcu's recent publications show a strong focus on in-memory computing, Ising machines for combinatorial optimization, spintronics-based architectures, and quantum computing. Her work bridges theoretical foundations with practical hardware implementations, particularly exploring energy-efficient solutions through novel computing paradigms that address physical constraints. Her notable awards include: NSF CAREER Award (2016) on 'Trading Communication and Storage for Computation to Enhance Energy Efficiency' NSF SPX grant (2017) on scalable in-memory processing using spintronics NSF CCF grant (2014) on soft (approximate) near-threshold voltage computing NSF XPS grant (2014) on approximate communication to enhance energy efficiency Dr. Karpuzcu actively mentors PhD students and undergraduate researchers, with her lab 'wide open to motivated Ph.D. students and undergraduate researchers.' She has served on technical program committees for major conferences including ISCA, HPCA, MICRO, and ICCAD, and has co-organized workshops on Near-threshold Voltage Computing. She teaches courses on computer architecture, physics of computation, and quantum computing, including developing innovative courses like 'Physics of Computation' inspired by Richard Feynman's lectures.

Dieter HornsView profile

Professor

• Astroparticle Physics
• High Energy Astrophysics
• Gamma-ray Astronomy
• +4 more

Prof. Dr. Dieter Horns is a Professor (W2) for Astroparticle Physics at the University of Hamburg, Faculty of Mathematics, Informatics and Natural Sciences, Institute of Experimental Physics. He has held this position since 2007. Previously, he was an Assistant at the University of Tübingen (2004-2007) and Research Assistant at Max-Planck Institute for Nuclear Physics (2001-2004). He obtained his Doctorate in Physics from Universität Hamburg in 2000. His research focuses on high-energy astrophysics (keV-TeV range), multi-wavelength investigations of gamma-ray sources, experimental techniques for ground-based air Cherenkov telescopes (HESS I&II, CTA), time-domain astrophysics, low-noise photon detection, and dark matter searches (WISPs). He leads significant projects including the HAFUN research building and coordinates dark matter research for the Quantum Universe Cluster of Excellence. Horns' publications demonstrate expertise in gamma-ray astronomy, dark matter phenomenology, cosmic ray physics, and telescope instrumentation. His recent work shows strong focus on CTA/LST-1 telescope operations, pulsar studies, dark matter constraints, and cosmic ray measurements using H.E.S.S. data. He has trained 32 B.Sc. students, 44 M.Sc. students, 22 PhD students, and 13 PostDocs since 2007. He coordinates the Quantum Universe Research School and leads multiple international collaborations including H.E.S.S. and CTA. As Principal Investigator for the HAFUN research building, he oversees major instrumentation projects.

Anatoly MaksimchukView profile

Researcher

• High-Intensity Laser-Plasma Interactions
• Table-Top Particle Accelerators
• Laser Wakefield Acceleration
• +4 more

Dr. Anatoly Maksimchuk is a Research Scientist in the Electrical Engineering and Computer Science Department at the University of Michigan's College of Engineering. He plays a pivotal role in the Center for Ultrafast Optical Science (CUOS) and serves on the Executive Committee of the Michigan Institute for Plasma Science and Engineering (MIPSE). As co-PI of the $20M ZEUS facility, he oversees laser beam delivery systems and manages experimental areas. Laser-Matter Interaction at Relativistic Intensities Table-Top Plasma Accelerators High-Power Short Pulse Lasers Medical Applications (Cancer Therapy, Imaging) Nuclear Physics (Isotope Production) Quantum Electrodynamics Regime Studies Dr. Maksimchuk's research includes groundbreaking work on electron/ion acceleration, nonlinear Thomson scattering, and relativistic harmonics generation. Recent publications focus on ZEUS facility development and extreme laser-plasma interactions. 2021 University of Michigan Research Faculty Achievement Award 2013 Fellow of the American Physical Society 2009 & 2014 College of Engineering Outstanding Research Scientist Awards His work has appeared in 200+ publications with 4000+ citations, including in Nature , Science , and Physical Review Letters . He mentors doctoral committees and supervises student researchers, collaborating with Nobel laureate Gérard Mourou.

Paul CampbellView profile

Researcher

• Magnetized High Energy Density Physics
• Laboratory Astrophysics
• Laser-Plasma Accelerators
• +3 more

Paul Campbell is an Assistant Research Scientist associated with the ZEUS Laser Facility at the University of Michigan, Ann Arbor. His work focuses on particle acceleration and magnetic field generation during intense laser-plasma interactions, with applications in high-energy-density physics and laboratory astrophysics. He holds a PhD in Applied Physics from the University of Michigan and previously held a DOE Fusion Energy Sciences postdoctoral fellowship. Education: PhD in Applied Physics, University of Michigan; BS in Physics, University of the South (Sewanee, Tennessee). Research interests include: Laser-plasma accelerators Neutron source optimization Magnetized plasmas Ultrafast diagnostics Pulsed power systems Recent publications span experimental and computational domains, including: Advancements in neutron generation and imaging via dense plasma focus (2024-2025) Multi-messenger diagnostics for laser-driven shocks (2025) Thermonuclear fusion yield improvements in Z-pinch systems (2024) Analysis of plasma stagnation and instability mechanisms (2023-2024) Interdisciplinary work on digital mental health regulation (2024-2025) He contributes to the development and operation of high-power laser systems like MJOLNIR, focusing on diagnostics, stability, and energy coupling efficiency. His contact details include campbpt@umich.edu, and he is affiliated with the High Field Science research group.

Itay HenView profile

Associate Professor

• Quantum Computing
• Computational Physics
• Quantum Simulation
• +4 more

Itay Hen is an Associate Professor of Research in the Department of Physics and Astronomy and Principal Scientist at the Information Sciences Institute (ISI), University of Southern California. He has held research faculty positions at USC since 2013, progressing from Assistant Professor (2016-2020) to his current Associate Professor role since 2020, while leading ISI's quantum computing initiatives. His educational background includes dual bachelor's degrees in Physics and Psychology from Tel Aviv University, followed by a Ph.D. in Physics from the same institution in 2009. Postdoctoral training included theoretical condensed matter research at Georgetown University and UC Santa Cruz, plus a senior scientist role at NASA Ames Research Center within the Quantum Artificial Intelligence Laboratory—a NASA/Google/USRA collaboration. Dr. Hen's research centers on Quantum Computing and Computational Physics , with specific expertise in gate-based quantum simulation algorithms, quantum annealer limitations, and methods for studying equilibrium/non-equilibrium properties of strongly correlated quantum systems. His work bridges theoretical frameworks with practical quantum hardware applications. Analysis of his 15 most recent publications (2017-2025) reveals consistent focus on quantum algorithms and Monte Carlo techniques, with accelerating output in 2024. Key themes include Feynman path integrals, spin/Bose-Hubbard model simulations, and quantum spectrum estimation, primarily published in Physical Review journals and Quantum. He leads the Hen Lab at USC's ISI, which operates within the Quantum Artificial Intelligence Laboratory framework. His research has been supported through NASA/Google/USRA collaborations focused on quantum optimization for complex computational problems, though specific grant details and student mentorship records aren't provided in the source material.

Kerem CamsariView profile

Assistant Professor

• Probabilistic Computing
• Quantum Computing
• Neuromorphic Engineering
• +3 more

Kerem Camsari is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California Santa Barbara since 2020. He earned his Ph.D. from Purdue University in 2015, where he also worked as a postdoctoral researcher. His research focuses on probabilistic computing, quantum circuits, and domain-specific hardware accelerators for the "beyond-Moore" era of electronics. Key Affiliations: Assistant Professor, UC Santa Barbara (2020–present) Postdoctoral Researcher, Purdue University (post-2015) Founding Member, IEEE Nanotechnology Council Technical Committee His work established a modular framework connecting emerging materials to circuits/systems, later applied to p-bits and p-circuits as bridges between classical and quantum computing. He actively contributes to IEEE, serving as Senior Member. Scientific Awards: IEEE Magnetics Society Early Career Award (2021) Bell Labs Prize ONR Young Investigator Award NSF CAREER Award

Tor AamodtView profile

Professor

• Computer Architecture
• GPU Architecture
• Deep Neural Networks
• +4 more

Tor Aamodt is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia within the Faculty of Applied Science. He has been a faculty member at UBC since 2006 and maintains an active research program in computer architecture with a focus on GPU systems. His academic journey includes a BASc, MASc, and PhD from the University of Toronto, followed by industry experience at NVIDIA where he worked on the memory system architecture of the GeForce 8 Series GPU. Professor Aamodt's research spans computer architecture with particular expertise in accelerators for deep neural networks and graphics processor unit architecture for non-graphics computing. His work has evolved from foundational GPU architecture research to cutting-edge applications in ray tracing, robotics acceleration, and energy-efficient computing. He has made significant contributions to understanding GPU memory systems, interconnect architectures, and the application of GPUs to machine learning workloads. His research group has developed influential tools including the first widely used GPGPU architecture simulator and the Vulkan-Sim ray tracing simulator. His recent publications reveal a strong trend toward real-time ray tracing acceleration and robotics applications, with substantial work on optimizing tree traversal algorithms for ray tracing workloads. The research shows a clear evolution from general GPU architecture studies to specialized hardware-software co-design for specific application domains, particularly in rendering and robotics. His group consistently publishes at top-tier architecture venues including MICRO, ISCA, and ASPLOS. IEEE Micro Top Picks (3 papers) Communications of the ACM Research Highlight MICRO Conference Hall of Fame NVIDIA Academic Partnership Award (2010) NSERC Discovery Accelerator (2016-2019) Google Faculty Research Award (2016) SAMSUNG Global Research Outreach Award (2023) IISWC 2023 Best Paper Award Professor Aamodt has advised numerous graduate students who have gone on to positions at leading technology companies including Google. His research has been supported by major grants from NSERC, NVIDIA, Google, and Samsung. He has served in leadership roles including Program Chair for ISPASS 2013 and General Chair for ISPASS 2014, and was a Visiting Associate Professor at Stanford University during his 2012-2013 sabbatical. His group maintains active collaborations with industry partners and has produced influential open-source tools including GPGPU-Sim and Vulkan-Sim.

Sanghoon SongView profile

Researcher

• Ultrafast X-ray Scattering
• Condensed Matter Physics
• Materials Science
• +3 more

Sanghoon Song is a Staff Scientist at the SLAC National Accelerator Laboratory , affiliated with Stanford University . He specializes in ultrafast x-ray scattering and coherent x-ray diagnostics , with a focus on nonequilibrium material dynamics and time-resolved structural analysis . Key Techniques : X-ray Photon Correlation Spectroscopy (XPCS), Split-Delay Systems, Femtosecond X-ray Emission Spectroscopy Research Themes : Structural relaxation in supercritical fluids, Charge Density Wave dynamics, Nanoscale phase transitions His work has developed novel instrumentation for X-ray free-electron lasers, including high-pressure cells and split-delay optics. Recent studies demonstrate sub-picosecond decorrelation in glass-forming liquids and stochastic domain wall dynamics in ferroelectric superlattices. He explores electron-phonon coupling through Fe K-edge spectroscopy and contributes to macromolecular femtosecond crystallography at LCLS. Collaborations include Stanford synchrotron radiation facilities and Korean Physical Society initiatives for women in physics. Scientific Awards : ORCID: 0000-0003-3493-1850

Shayantan ChaudhuriView profile

Research Fellow

• Computational Chemistry
• Quantum Chemistry
• Covalent Drug Design
• +3 more

Shayantan Chaudhuri is a Research Fellow at the School of Chemistry, University of Nottingham, joining the Hirst Group in September 2023. His work focuses on quantum chemistry methods to characterize and accelerate covalent drug design, alongside prior research in computational simulation of metal nucleation on diamond electrodes and property-driven generative design of organic molecules and metal nanoparticles. Research Interests: Quantum Chemistry and DFT-based Methods Materials Science (metal nanoparticles, diamond surfaces) Machine Learning Applications Covalent Drug Design Scientific Contributions: Developed methods for quantum many-body dispersion calculations Investigated stability of gold atoms on diamond surfaces Studied electrochemical ozone generation using doped diamond electrodes Explored adiabatic vs. non-adiabatic electron transfer in 2D materials

Nandini AnanthView profile

Professor

• Quantum Mechanics
• Theoretical Chemistry
• Physical Chemistry
• +5 more

Nandini Ananth is a Professor in the Department of Chemistry and Chemical Biology at Cornell University's College of Arts and Sciences. Her research focuses on developing theoretical simulation techniques to understand chemical selectivity at the molecular level through quantum mechanical principles. Her educational background includes: Postdoctoral research at California Institute of Technology PhD from University of California, Berkeley MSc from Indian Institute of Technology Madras Professor Ananth's research spans theoretical, physical, and materials chemistry with emphasis on quantum mechanical processes in complex chemical systems. Her group develops and applies techniques based on semiclassical theory and path integral formulations to investigate charge and energy transfer pathways in condensed phases. This work has significant implications for designing novel materials, particularly in organic photovoltaics where understanding exciton generation, transport, and dissociation is critical for improving solar energy conversion efficiency. Analysis of Professor Ananth's recent publications (2021-2024) reveals continued innovation in computational methodologies for quantum dynamics. Her work bridges theoretical chemistry and materials science, with key advancements in path integral methods, ring polymer molecular dynamics, and semiclassical approaches to nonadiabatic processes. A notable trend is the increasing computational sophistication of her methods, including GPU acceleration and hybrid quantum-classical algorithms, while maintaining focus on fundamental physical chemistry questions related to energy conversion processes. Among her notable scientific achievements is the NSF CAREER Award for her project "Theoretical Investigation of Photo-induced Charge and Energy Transfer in Organic Photovoltaic Materials". Professor Ananth actively mentors graduate students in her research group, with publications showing collaborations with numerous students and postdoctoral researchers. Her work has been supported by significant funding including the NSF CAREER award, which focuses on theoretical investigations of charge and energy transfer mechanisms relevant to organic photovoltaic materials development. The Ananth Group at Cornell University maintains strong connections with the university's Center for Advanced Computing and collaborates across chemistry, physics, and materials science disciplines. They continue to advance computational methodologies while applying them to challenging problems in energy conversion and quantum dynamics, particularly in the areas of singlet fission and nonadiabatic reaction dynamics.