Accelerator-Driven Light Sources Professors and Supervisors | ApplySharif

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Gordon WetzsteinView profile

Associate Professor

Stanford UniversityUnited States

Gordon Wetzstein is an Associate Professor of Electrical Engineering and, by courtesy, Computer Science at Stanford University. He leads the Stanford Computational Imaging Lab and co-directs the Stanford Center for Image Systems Engineering (SCIEN). His research focuses on computational imaging, wearable computing, and neural rendering, blending computer graphics, vision, AI, and optics. Education: Ph.D., Computer Science, University of British Columbia (2011) Diploma, Media Systems Science, Bauhaus University (2006) Research Interests: His work spans computational displays , holography , non-line-of-sight imaging , and AI-driven optical systems . Key projects include Autofocals (gaze-contingent eyeglasses) and neural holography systems. He explores applications in AR/VR, medical imaging, and scientific visualization. Publications: Recent work includes advances in 3D holography, gaze-tracking systems, and AI-optics integration. His papers address challenges in display efficiency, light-field processing, and real-time imaging. Awards: Fellow of Optica NSF CAREER Award (2016) PECASE (2019) ACM SIGGRAPH Significant New Researcher Award (2018) Advising & Grants: He advises over 20 doctoral and postdoctoral students. His lab collaborates with industry (e.g., Raxium, Google) and has secured grants from NSF, DARPA, and private foundations. Labs & Teams: His lab develops cutting-edge systems like neural holography and non-line-of-sight imaging. The SCIEN center fosters interdisciplinary image systems research.

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Thomas BlumensathView profile

Professor

University of SouthamptonUnited Kingdom

Professor Thomas Blumensath is a Professor of Signal and Image Processing at the University of Southampton and a Fellow at the Alan Turing Institute. He is the Academic Lead in Image Processing and Reconstruction at the University's μ-VIS X-ray Imaging Centre and Director of Research at the Institute of Sound and Vibration Research (ISVR). His research focuses on advanced algorithms for solving inverse problems in tomographic imaging, combining machine learning, optimization, and statistical methods. Key areas include X-ray tomography strategies, GPU-accelerated reconstruction, and multimodal imaging applications. Education: B.Sc. (Hons) Music Technology and Audio System Design, University of Derby (2002) PhD in Electronic Engineering (Bayesian Signal Processing), University of London (2006) Research Interests: Professor Blumensath's work spans theoretical and applied signal/image processing, with emphasis on tomographic imaging techniques. His current projects address efficient reconstruction methods, spectral X-ray CT, and applications in manufacturing and plant science. He collaborates with advanced imaging facilities like Diamond Light Source and ISIS neutron imaging beamline. Key Contributions: His research bridges computational methods (e.g., compressed sensing) with practical imaging challenges, including limited-angle tomography and stereo imaging strategies. He leads the National Research Facility for Lab X-ray CT and has developed the TIGRE reconstruction toolbox. Grants & Projects: Active funding includes EPSRC projects on tomographic sensitivity monitoring and CT-based manufacturing inspections. Completed projects cover constrained reconstruction, AM process verification, and industrial CT metrology. Awards: Alan Turing Institute Fellowship Teaching & Leadership: He teaches modules on machine learning, biomedical image processing, and robotics. Leads the BEng Control Engineering program at the Joint Education Institute with Harbin Engineering University. Labs/Teams: Active in the Signal Processing, Audio and Hearing research group (SPAH) and the Institute for Life Sciences. Oversees the μ-VIS X-ray Imaging Centre's research initiatives.

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Callie HaoView profile

Assistant Professor

Georgia Institute of TechnologyUnited States

Callie Hao is an Assistant Professor in the Department of Electrical and Computer Engineering at the Georgia Institute of Technology since 2021, holding the ON Semiconductor Junior Professorship. Her research bridges hardware efficiency and algorithmic innovation with significant industry and federal recognition. Education: Ph.D. in Electrical Engineering, Waseda University (2017) M.S. and B.S. in Computer Science and Engineering, Shanghai Jiao Tong University Research Focus: Dr. Hao pioneers software/hardware co-design for edge AI, specializing in hardware-efficient machine learning algorithms, FPGA-based reconfigurable computing, graph neural networks, and electronic design automation (EDA). Her work emphasizes neural architecture search, high-level synthesis optimization, and memory-efficient systems for embedded and IoT applications, driven by the philosophy that "1 + 1 > 2" for transformative efficiency gains. Publication Impact: Her 15 most recent publications (2023-2026) reveal a strategic shift toward machine learning-driven EDA tools, with 60% focused on high-level synthesis frameworks and 40% on graph neural network acceleration. Key trends include simulation speed breakthroughs (LightningSim), automated accelerator generation (GNNBuilder), and cryptographic hardware innovations (Cryptonite), predominantly published in top-tier venues like MICRO, ICCAD, and DAC. Awards & Recognition: NSF CAREER Award (2024) and Intel Rising Star Faculty Award (2023) Best Paper Awards at MLCAD 2024 and GLSVLSI 2021 ON Semiconductor Junior Professorship (2025) and Sutterfield Family Early Career Professorship (2022) DAC-SDC competition championships (2018-2020) Mentorship & Funding: Dr. Hao advises 8+ Ph.D. students in the Sharc Lab, with Rishov Sarkar winning the Oscar P. Cleaver Award and Qualcomm Innovation Fellowship. Her research is funded by DARPA (2021) for ultra-light video intelligence systems and supported by industry awards from Amazon and Sony. She actively serves on program committees for DAC, ICCAD, and DATE conferences. Lab Leadership: As director of the Sharc Lab (Software/Hardware Co-design lab), she cultivates interdisciplinary research at the intersection of FPGA design, machine learning, and EDA, requiring expertise in Verilog/HLS, GNNs, and compiler technologies while maintaining strict focus on real-world hardware implementation.

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Louise WillingaleView profile

Associate Professor

University of Michigan-Ann ArborUnited States

Dr. Louise Willingale is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan. Specializing in high-intensity laser-plasma interactions, she leads experimental research at facilities including the ZEUS laser system and OMEGA EP. Her work combines experimental diagnostics with numerical modeling to advance understanding of relativistic plasma physics and ion acceleration mechanisms. Education: PhD in Physics from Imperial College London (2007) Research Focus: Investigates relativistic laser-plasma interactions through ion acceleration, magnetic field generation, and direct laser acceleration of electrons. Her work spans underdense/near-critical density plasmas, shock formation physics, and extreme electromagnetic field generation in laboratory astrophysics contexts. Recent Publication Trends: 2024-2025 studies emphasize ZEUS laser facility development, optimization of acceleration mechanisms (direct laser acceleration, wakefield acceleration), and magnetic field dynamics in multi-PW laser-solid interactions. Common subfields include collisionless shocks, radiation-driven plasma instabilities, and advanced diagnostics for relativistic charge particles. Labs & Collaborations: Affiliated with the Center for Ultrafast Optical Science (CUOS) and the Center for High-Energy-Density Laboratory Astrophysics Research (CHEDAR), working closely with the ZEUS laser facility team.

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Thiago Batista SoeiroView profile

Professor

University of TwenteNetherlands

Thiago Batista Soeiro serves as a Full Professor with exceptional scholarly impact, evidenced by over 200 research publications and an h-index of 27. His work fundamentally advances power electronics applications in transportation and energy systems, particularly through innovations in electric vehicle infrastructure and sustainable power conversion technologies. Despite the absence of explicit institutional affiliation in source materials, his research permeates critical IEEE journals and conferences. Professor Soeiro's research portfolio centers on: Power converter design for electric vehicle charging systems AI-driven battery health estimation using electrochemical impedance spectroscopy Wireless power transfer optimization for automotive applications High-efficiency topologies for more electric aircraft Hydrogen energy system integration Advanced semiconductor utilization in grid-connected systems Analysis of his 2023-2025 publications reveals accelerating innovation in wide-voltage-range converters, predictive battery management, and fault-tolerant power systems. His work increasingly bridges machine learning with power electronics, notably through computation-light AI models for battery diagnostics, while maintaining strong focus on practical implementation challenges in EV charging and aircraft electrification. No scientific awards or honors were documented in the available materials. Similarly, information regarding student supervision, research grants, laboratory facilities, or collaborative teams was not provided in the source texts.

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Benedikt GüntherView profile

Researcher

Technical University of MunichGermany

Benedikt Günther is a research scientist at the Technical University of Munich (TUM) working within the Chair of Biomedical Physics led by Prof. Dr. Franz Pfeiffer. His research focuses on the Munich Compact Light Source (MuCLS), a laboratory-scale inverse Compton X-ray source that provides synchrotron-like radiation for biomedical applications. Günther plays a key role in developing, optimizing, and characterizing this innovative technology, contributing to both its fundamental physics and practical medical applications. His primary research interests center around X-ray physics and imaging techniques, particularly laser enhancement cavities for inverse Compton X-ray sources, X-ray microscopy, dynamic phase-contrast imaging, and X-ray spectroscopy. Günther's work bridges fundamental physics with practical medical applications, developing instrumentation that brings synchrotron-quality imaging to conventional laboratory settings. His research has significant implications for improving medical diagnostics while making advanced imaging techniques more accessible. Analysis of Günther's publication record reveals a consistent focus on advancing compact X-ray source technology and its applications. His work demonstrates expertise in both theoretical modeling and experimental implementation, with publications spanning instrument development, imaging techniques, and specific medical applications. The research shows progression from fundamental source characterization to increasingly sophisticated biomedical applications, particularly in breast imaging, dental diagnostics, and materials science. 2019 Best Poster Award at the combined meeting of the 68th Denver X-ray Conference (DXC) & 25th International Congress on X-ray Optics and Microanalysis (ICXOM) for 'Full-Field Structured Illumination Super-Resolution X-ray Transmission Microscopy' Günther regularly presents his work at major international conferences including the International Particle Accelerator Conference, High-Brightness Sources and Light-driven Interactions Congress, and specialized X-ray imaging meetings. His research is conducted within the Munich Compact Light Source facility, a collaborative project involving physicists, engineers, and medical researchers working to develop laboratory-scale synchrotron technology for widespread biomedical use.

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Aldo MozzanicaView profile

Researcher

Paul Scherrer InstituteSwitzerland

Aldo Mozzanica is a Researcher at the Paul Scherrer Institute (PSI) in Switzerland, affiliated with the Laboratory for X-ray Nanoscience and Technologies. He holds a degree in Physics from Insubria University and a Ph.D. from the University of Milan, where his doctoral work focused on scintillating fiber vertex detectors for CERN's Antiproton Decelerator facility. At PSI, he leads detector development projects for synchrotron and free-electron laser applications. His research centers on advancing X-ray detector technology, including: Developing next-generation integrating pixel/strip detectors (JUNGFRAU, GOTTHARD) Improving frame rates, noise performance, and radiation hardness Exploring novel detector concepts for XFEL/synchrotron applications Enabling new experimental capabilities in structural biology and materials science Mozzanica's 135+ publications focus on X-ray detector innovation, with recent work emphasizing: Hybrid pixel detector optimization for 4th-generation light sources On-chip digitization and charge transport modeling High-speed data acquisition systems Applications in crystallography, spectroscopy, and phase-contrast imaging As principal developer of the JUNGFRAU detector, he oversees: ASIC design, testing, and characterization Readout electronics and firmware development Module production and supply chain management Commissioning at SwissFEL endstations

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Sunil MittalView profile

Assistant Professor

Northeastern UniversityUnited States

Sunil Mittal is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University, specializing in quantum and topological photonics. He joined Northeastern in 2021 and holds a PhD from the University of Maryland, College Park, alongside master’s degrees in Physics and Optoelectronics. His research focuses on quantum photonics, topological photonics, nonlinear photonics, and two-dimensional materials, with notable contributions to topological frequency combs and photonic quadrupole phases. Education: PhD in Electrical Engineering (University of Maryland, 2014), MS in Physics and Optoelectronics, and industry experience in optical telecommunications. Research highlights include pioneering work on topological sources of quantum light and non-Hermitian photonics systems. Recipient of 2024 and 2022 Stanford University citations (top 2% most-cited scientists) Lead co-PI on a $1.5M NSF DMREF grant (2024) for photonic materials development Recipient of Northeastern’s FY24 TIER 1 Interdisciplinary Research Seed Grant His Quantum Photonics Lab explores topological photonics applications in quantum computing and optical communication. Recent projects include using deep learning to accelerate photonic material design and studying excitonic Mott insulators in 2D heterostructures.

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Mikael JohanssonView profile

Professor

KTH Royal Institute of TechnologySweden

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.

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Jun XiaoView profile

Assistant Professor

University of Wisconsin-MadisonUnited States

Jun Xiao is an Assistant Professor in the Department of Materials Science and Engineering at the University of Wisconsin-Madison since August 2021. He holds additional affiliations with the Physics and Electrical & Computer Engineering departments. His research focuses on quantum materials, light-matter interactions, and terahertz optoelectronics. Ph.D. in Applied Science and Technology from UC Berkeley (2018) Postdoctoral scholar at Stanford University and SLAC National Accelerator Laboratory Bachelor's degree in Physics from Nanjing University Research interests include structure-property relationships in quantum materials, ultrafast optical engineering, and THz device development. His lab explores non-equilibrium phase transitions, quantum collective excitations, and photocarrier dynamics for energy and computing applications. Recent publications emphasize topological semimetals for THz sensing, stacking order engineering in 2D materials, and spin-mechanical coupling in antiferromagnets. His group integrates ultrafast lasers, quantum transport measurements, and in-situ strain control to study ferroelectricity, magnetism, and electron correlations. Scientific awards include Nature Communications Editor's Suggestion (2018) Nature Nanotechnology publication (2015) Jun Xiao's lab operates 2D material preparation and multimodal characterization facilities, including ultrafast laser systems, CW light sources, and cryogenic strain cells. He teaches courses on quantum materials and device physics, including MS&E 803 and MS&E 456.

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Matthew R. EdwardsView profile

Assistant Professor

Stanford UniversityUnited States

Matthew R. Edwards is an Assistant Professor of Mechanical Engineering at Stanford University, affiliated with the School of Engineering. His research focuses on high-power lasers and plasma physics, developing optical diagnostics for fluids and plasmas, and exploring light-matter interactions. He holds a PhD and prior degrees from Princeton University in Mechanical and Aerospace Engineering, followed by a Lawrence Fellowship at Lawrence Livermore National Laboratory. Education : PhD in Mechanical and Aerospace Engineering, Princeton University (2019) MA in Mechanical and Aerospace Engineering, Princeton University (2015) BSE in Mechanical and Aerospace Engineering, Princeton University (2012) Research Interests : Edwards' work bridges mechanical engineering and plasma physics, emphasizing ultrafast laser-plasma interactions, plasma-based optical components, and applications in energy science. His lab, the SAPPHIRE Laser Laboratory, explores femtosecond laser technologies for creating novel optical elements (e.g., plasma gratings, holographic lenses) and advancing laser-driven particle acceleration, fusion research, and diagnostic tools. Key areas include: Design of plasma-based optical components for high-power laser control Simulation of laser-matter interactions at relativistic intensities Development of compact light and particle sources Research Trends : His recent articles (2024–2025) highlight advancements in plasma gratings, relativistic birefringence, and laser wakefield acceleration. Notable contributions include ionization-based compression of ultrafast laser pulses and polarization control in underdense plasmas. Awards/Grants : No awards explicitly listed, but his Lawrence Fellowship indicates prior recognition. His work aligns with grants in plasma physics and laser technology. Labs/Teams : He leads the SAPPHIRE Laser Laboratory , collaborating with the PULSE Institute and National Ignition Facility (NIF) on plasma optics and high-energy laser applications.

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Matthias FuchsView profile

Professor

Karlsruhe Institute of TechnologyGermany

Prof. Matthias Fuchs is a Professor and Head of Department for Accelerator Research and Development I at the Karlsruhe Institute of Technology (KIT). His research focuses on advanced accelerator technologies, laser-plasma acceleration, and ultrafast X-ray science. He is affiliated with the IBPT group (Institut für Beschleunigerphysik und Teilchenphysik) and coordinates activities at the Department of Physics. His work bridges fundamental plasma physics with applied accelerator engineering, aiming to develop next-generation compact light sources and ultra-short wavelength technologies. Research interests include laser-plasma electron acceleration, quasi-isochronous storage ring dynamics, and nonlinear X-ray optics. His team explores parametric excitation mechanisms, high-order beam dynamics, and novel X-ray wave mixing phenomena in materials like silicon. Collaborations involve developing predictive laser stabilization techniques and high-bandwidth imaging systems for precision experiments. No scientific awards are explicitly listed, but his contributions to the Snowmass 2021 report on advanced accelerators highlight his influence in the field. He leads the Accelerator Research and Development I group, overseeing projects like the FLUTE compact storage ring commissioning and compact transverse deflecting system experiments. His lab work focuses on creating tunable X-ray sources and studying betatron radiation generation through transverse oscillating bubbles in plasma.

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Paolo PrandoniView profile

Lecturer

Swiss Federal Institute of Technology in LausanneSwitzerland

Paolo Prandoni is a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences (IC). He serves as a Scientist in the Audiovisual Communications Laboratory (LCAV) and teaches in the SSC-ENS and SIN-ENS units, focusing on signal processing theory and practical applications in audiovisual communications. He earned his PhD from EPFL after completing all prior education there, driven by childhood fascination with long-distance telephony. His doctoral work established foundations in communication systems that continue to inform his research. Prandoni's research spans audio/image processing, machine learning for media analysis, and DSP education. Key areas include computational photography (e.g., spectral imaging, stained glass rendering), speech quality assessment via transfer learning, music information retrieval (e.g., fingering prediction), and audience analytics through his company Quividi. His work consistently bridges theoretical signal processing with real-world implementation. Recent publications reveal a strategic shift toward machine learning integration in signal processing tasks, particularly non-intrusive speech assessment and lensless imaging reconstruction. Simultaneously, he advances DSP pedagogy through MOOC development and hands-on teaching tools using off-the-shelf hardware, emphasizing accessibility and practical skill development. No scientific awards are documented in the provided materials. He has advised PhD student Thanikachalam Niranjan (thesis: Image Based Relighting of Cultural Artifacts , 2016) and teaches Communication Systems and Computer Science courses. His educational impact extends through the open-access textbook Signal Processing for Communications (2008) and tools like MultiPub for maintainable online classes. Industry engagement includes Quividi co-founding (2006) and ongoing CSO role in attention analytics. As a core LCAV laboratory member, he collaborates on interdisciplinary projects including cultural heritage digitization, embedded signal processing systems, and real-time audience measurement, leveraging EPFL's infrastructure for both academic and commercial applications.

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Carsten WelschView profile

Professor

University of LiverpoolUnited Kingdom

Professor Carsten Welsch is a leading physicist in accelerator science and technology at the University of Liverpool. He founded the QUASAR Group in 2008 and served as Head of the Physics Department from 2016 to 2023. His work bridges cutting-edge research in antimatter physics, beam diagnostics, and innovative accelerator design with strategic leadership in education and international collaboration. PhD in Accelerator Physics, University of Frankfurt Postdoc, Max Planck Institute for Nuclear Physics CERN Fellow (2005) His research focuses on low-energy antimatter physics , plasma wakefield acceleration , and dielectric laser accelerators , with applications in medicine and global challenges. Recent publications highlight advancements in betatron radiation modeling, positronium cooling, and plasma-driven acceleration techniques. He has secured over 25M€ in EU funding for networks like AVA and EuPRAXIA, trained 100+ Marie Curie Fellows, and founded D-Beam Ltd for beam instrumentation. Awards include the Viddy Platinum Award (2022) and Helmholtz-University YIG Award (2006). As Director of the LIV.INNO Center for Doctoral Training, he champions data-intensive science education. His outreach efforts have impacted millions globally, emphasizing discovery science and accelerator technology's societal benefits.

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Karl KrushelnickView profile

Professor

University of Michigan-Ann ArborUnited States

Karl Krushelnick is a Professor in the Department of Nuclear Engineering and Radiological Sciences at the University of Michigan, serving as Director of the Center for Ultrafast Optical Science (CUOS) and Associate Director for High Field Science. His research focuses on high-intensity laser-plasma interactions, relativistic electron beams, and applications in radiation generation, magnetic reconnection, and biomedical sensing. Research Interests: Basic relativistic plasma studies Table-top particle accelerators Ultra-strong magnetic fields Ultrafast laser technology Quantum electrodynamics (QED) in extreme light regimes Key Trends in Publications: Krushelnick’s recent work investigates zettawatt-equivalent laser experiments, orbital angular momentum effects on laser absorption, magnetic reconnection dynamics, and neutron generation mechanisms. His team explores laser wakefield acceleration, betatron X-ray diagnostics, and filamentation control for advanced applications in physics and engineering.

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