Dr. Gábor Takács is a Professor at the Department of Theoretical Physics , Budapest University of Technology and Economics (BME), leading the BME 'Momentum' Statistical Field Theory Research Group . His work focuses on quantum field theory, integrable systems, and non-equilibrium dynamics in low-dimensional quantum systems. Research interests include: • Quantum Field Theory • Statistical Mechanics • Condensed Matter Physics • Integrability and its breaking • Boundary Effects in Quantum Systems His recent publications analyze confinement in spin chains, TTbar deformations, and quantum quenches in integrable models. He has been awarded the Lendület and Momentum grants for his research. Supervised students include prominent researchers like Balázs Pozsgay and Dávid Horváth, contributing to quantum field theory and condensed matter physics.
Theodore J. Allen is a Professor of Physics at Hobart & William Smith Colleges (HWS), where he has held academic roles since 2000, progressing from Assistant Professor (2000-2005) to Associate Professor (2005-2023) and currently serving as a full Professor. He holds a Ph.D. in Theoretical Physics from the California Institute of Technology (1988), an M.S. in Physics from Caltech (1984), and a B.S. in Applied Mathematics, Engineering, and Physics from the University of Wisconsin-Madison (1982). His research focuses on QCD, relativistic boundstates, hybrid mesons, and BRST quantization. Notable contributions include modeling QCD strings, analyzing gluonic excitations, and exploring confinement dynamics. Allen has collaborated extensively with researchers like M.G. Olsson and S. Veseli, investigating topics such as scalar confinement and light quark mass dependence in meson spectroscopy. Allen has served as Department Chair at HWS (2004–2006, 2008–2009, 2013–2019) and held roles in academic committees, including the HWS Career & Professional Development Liaison to the American Physical Society. His awards include the NSF Graduate Fellowship (1982–1985) and multiple academic excellence scholarships from UW-Madison. Teaching highlights include courses in calculus-based physics, quantum mechanics, and relativity at HWS. He has also taught at the University of Wisconsin-Madison, SUNY Institute of Technology, and Caltech as a teaching assistant. His service includes refereeing for Physical Review Letters and Modern Physics Letters.
Tilmann Rabl is a Professor affiliated with the Hasso Plattner Institute (HPI) at the University of Potsdam, Germany. His research focuses on database systems, distributed computing, and scalable data processing. He leads projects exploring serverless cloud infrastructure, stream processing, and machine learning integration with databases. Key areas of research include optimizing GPU-based data processing, developing benchmarks like TPCx-IoT and TPCx-AI, and advancing techniques for distributed systems, including RDMA and NVLink-based architectures. His work emphasizes practical systems, such as Skyrise (serverless data processing), Rhino (distributed state management), and PROTEUS (scalable machine learning). Rabl has contributed to foundational tools like BlockJoin for matrix partitioning and has explored performance trade-offs in persistent memory and CXL device memory. His collaborative projects address challenges in real-time data analytics, sensor data coherence, and interoperable data science workflows.
Jorge Pullin is a Professor and Horace C. Hearne, Jr. Chair of Theoretical Physics at Louisiana State University (LSU), affiliated with the Department of Physics & Astronomy within the College of Science. He holds a Ph.D. from the Instituto Balseiro, Argentina (1988). His research focuses on quantum gravity and general relativity, particularly canonical quantization methods and loop quantum gravity. Collaborating with Rodolfo Gambini since 1990, Pullin has co-authored influential works like the book Loops, knots, gauge theories and quantum gravity (1996). He challenges mainstream string theory by advocating for quantization of general relativity itself. His work also explores black hole collisions, leveraging LSU's access to the world's fastest university-controlled supercomputer for numerical relativity simulations, and contributes to gravitational wave detection via LIGO collaborations. Recent articles highlight interdisciplinary efforts in quantum foundations, including interpretations of quantum mechanics and consciousness theories, alongside advancements in dark matter searches and scalar field interactions with quantum black holes. Pullin's group has pioneered the Lazarus Project and developed novel lattice-based quantum gravity approaches. Awards: Hearne Chair of Theoretical Physics His advising and grants activities reflect no listed students but significant collaborative efforts. Research is anchored at the Hearne Institute of Theoretical Physics, where he leads investigations into quantum gravity's implications for spacetime and black hole physics.
Óscar Oballe-Peinado is a professor at the Department of Electronics, School of Engineering, University of Málaga. His work focuses on tactile sensors, FPGA-based embedded systems, and robotics, particularly addressing crosstalk elimination, sensor calibration, and smart preprocessing techniques. He contributes to both academic research and educational innovations, including remote digital electronics laboratories. PhD in Electronics (University of Málaga, 2016) Active researcher in tactile sensor technology and FPGA implementations Supervisor of Raúl Lora Rivera's research on texture detection and compliance recognition His research explores advanced methods for tactile sensor optimization, including hysteresis correction, quantization error reduction, and compliance recognition algorithms. Recent publications (2023-2024) focus on smart tactile preprocessing and embedded FPGA implementations for robotics. The 2023-2024 articles emphasize his contributions to tactile sensor applications in robotic manipulation, texture detection, and compliance recognition using FPGA-based embedded systems. These works align with trends in smart sensor interfaces and real-time processing for robotics. Collaborated on improving remote digital electronics laboratories using Raspberry Pi 4 (2022) Developed FPGA-based tactile sensor suite electronics (2017)
Dr. Peter D'Eath is a Professor in the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge, affiliated with the Relativity and Gravitation Group. His research focuses on quantum gravity, black hole physics, and cosmology. He has contributed to understanding gravitational radiation in ultra-relativistic collisions and quantum effects in black hole evaporation. His work includes studies of supersymmetric field theories and their implications for cosmological models. Research Interests: Quantum aspects of black holes and their evaporation Gravitational radiation in high-energy collisions Supergravity theories and cosmological solutions Interactions between massive self-gravitating bodies His notable collaborations include work with Andrew Farley on quantum amplitudes in black hole evaporation, demonstrating phase coherence in quantum gravitational systems. Recent publications explore applications of supergravity models and gauge-invariant theories in cosmology. Advising: PhD Student: Andrew Farley (1997-2002) He is part of the Relativity and Gravitation Group at DAMTP, which operates the COSMOS supercomputer and contributes to theoretical cosmology research through the Stephen Hawking Centre for Theoretical Cosmology.
Nitin Samarth is the Verne M. Willaman Professor of Physics and Professor of Materials Science/Engineering at the Pennsylvania State University, part of the Eberly College of Science. He holds a Ph.D. from Purdue University (1986) and an M.S. from IIT Bombay (1980). His research focuses on condensed matter physics, quantum information, and spintronics, with expertise in synthesizing quantum materials like topological insulators and exploring their electronic and magnetic properties. His honors include the David Adler Lectureship Award (APS, 2024), Fellowships from the AAAS and APS, and awards for teaching excellence. He leads NSF-funded projects on quantum materials, including the Center for Nanoscale Science and the 2D Crystal Consortium. His group studies phenomena such as quantum spin dynamics, superconductivity at interfaces, and topological spintronics. Dr. Samarth has advised over 40 graduate students and postdocs, many of whom hold academic and industry positions globally. His research group emphasizes inclusivity and cutting-edge synthesis techniques like molecular beam epitaxy (MBE). Current projects explore van der Waals heterostructures, quantum anomalous Hall insulators, and spin-charge interconversion in Dirac semimetals.
Mohammad Mahdi Khalili is an Assistant Professor in the Department of Computer Science and Engineering at The Ohio State University's College of Engineering. He also serves as a part-time Research Scientist at Yahoo! Research, focusing on theoretical and applied machine learning with emphasis on robustness, interpretability, and model compression for large-scale systems including LLMs. Dr. Khalili earned his Ph.D. in Electrical Engineering and Computer Science and MSc in Applied Mathematics from the University of Michigan, Ann Arbor. Prior to OSU, he was a research scientist at Yahoo Research and a postdoctoral researcher at UC Berkeley. His research spans mechanistic interpretability of foundation models , privacy-aware model compression , and fairness in sequential decision-making . Current projects include counterfactual reasoning for fair ML, physiological signal analysis for worker health monitoring, and corruption analysis in model mechanisms. His work bridges theoretical guarantees with practical healthcare and security applications. Recent publications reveal strong focus on model compression techniques (block-wise sparsity, quantization) and interpretability methods for LLMs, with growing emphasis on physiological signal processing applications. The 2024-2025 papers show increasing integration of healthcare domains like ECG analysis and construction worker monitoring. Dr. Khalili currently advises four PhD students: Zhiqun Zuo: Counterfactual Reasoning Zhongteng Cai: Privacy-Aware Model Compression (UAI travel grant recipient) Ding Zhu: Trustworthy Model Compression & Time Series Analysis Vishnu Chhabra: Mechanistic Interpretability His research is supported by two NSF grants (health monitoring systems and dynamic environment robustness), a Translational Data Analytics Institute grant for medical AI, and a College of Engineering grant for large-scale systems. The lab recently acquired a dedicated GPU server for intensive computations. He actively contributes to the ML community through invited talks (Midwest Machine Learning Symposium) and publications in top venues including NeurIPS, ICML, and UAI.
Jean-Luc Danger is a Professor at TELECOM Paris where he currently heads the Digital Electronic Systems Research Group. He is affiliated with the Secure and Safe Hardware (SSH) Research Team within the Information Processing and Communication Laboratory (LTCI). With a career spanning over three decades in academia after 12 years in industrial research at PHILIPS and NOKIA, Professor Danger has established himself as a leading expert in hardware security and cryptographic implementations. Professor Danger received his degree in electrical engineering from SUPELEC in 1981 before embarking on his industrial career. His academic journey began in 1993 when he joined TELECOM Paris, where he has since made significant contributions to the field of hardware security. His educational background in electrical engineering provided the foundation for his later specialization in secure hardware design and analysis. Professor Danger's research primarily focuses on embedded systems security , physically unclonable functions (PUFs) , side-channel attacks and countermeasures , and fault injection techniques . His work bridges the gap between theoretical cryptography and practical hardware implementations, addressing critical security challenges in modern computing systems. His research has evolved from foundational work on cryptographic algorithms to more recent investigations into hardware Trojans, aging effects on security primitives, and automotive security systems. Professor Danger has been particularly influential in developing methodologies for analyzing and protecting against electromagnetic fault injection attacks and side-channel information leakage. His extensive publication record demonstrates a consistent focus on hardware security challenges, with recent work showing increased attention to automotive security systems, machine learning applications for intrusion detection, and reliability issues in security primitives affected by aging and process variations. The trajectory of his research shows a natural progression from pure cryptographic implementations to more holistic security approaches that consider the entire hardware stack and its vulnerabilities. Through his leadership of the Secure and Safe Hardware research team, Professor Danger has fostered a collaborative environment that bridges theoretical security research with practical hardware implementation challenges. His work has contributed significantly to the development of standardized methodologies for evaluating hardware security and has influenced both academic research and industry practices in secure hardware design.
Markus Gross is a Professor of Computer Science at ETH Zurich, where he founded the Computer Graphics Laboratory in 1994. He also serves as the Chief Scientist of the Walt Disney Studios and Director of DisneyResearch|Studios, a position he has held since 2008. His work bridges academia and industry, with research that has been applied in Hollywood films, sports broadcasting, and medical applications. Professor Gross received his Master of Science in electrical and computer engineering and his Ph.D. in computer graphics and image analysis from Saarland University in Germany in 1986 and 1989. His research spans multiple domains of computer graphics and visual computing. Early in his career, he pioneered point-based graphics techniques that offered alternatives to traditional triangle-based rendering pipelines. More recently, his work has focused on digital humans, AI characters, and machine learning applications for visual computing. His research has led to significant practical applications, including the Medusa capture system used in Hollywood films, the blue-c immersive telepresence system, and the Liberovision technology now used by major sports broadcasters. Analysis of his recent publications reveals a strong focus on neural rendering techniques, particularly around Gaussian splatting and diffusion models. His work increasingly integrates AI with traditional computer graphics methods, with applications in digital humans, medical visualization, and video processing. Many papers demonstrate practical applications in film production, medical treatment planning, and interactive systems. Professor Gross has received numerous prestigious awards throughout his career: 2024 Eurographics Gold Medal 2021 Steven Anson Coons Award for outstanding creative contributions to computer graphics 2019 Technical Achievement Award from the Academy of Motion Picture Arts and Sciences 2013 Karl Heinz Beckurts-Preis 2013 Konrad-Zuse-Medaille für Informatik 2013 Technical Achievement Award from the Academy of Motion Picture Arts and Sciences 2012 Academy Sci-Tech Oscar award for Wavelet Turbulence Professor Gross has mentored numerous Ph.D. students throughout his career, with 20 Ph.D. students contributing to his blue-c project alone. His research has been supported by significant funding from both academic and industry sources, enabling the creation of multiple startups including Cyfex, Novodex, LiberoVision, Dybuster, and Animatico (acquired by Nvidia in 2022). He leads the Computer Graphics Laboratory at ETH Zurich and DisneyResearch|Studios, fostering collaboration between academic research and practical industry applications. His teams have developed groundbreaking technologies that have impacted film production, sports broadcasting, medical visualization, and educational technology.
Dr. Yu Bi is an Assistant Professor in the Department of Electrical, Computer and Biomedical Engineering at the University of Rhode Island. His research focuses on hardware security, supply-chain security, and deep learning hardware acceleration. He holds a Ph.D. from the University of Central Florida (2016), an M.S. from New York University (2012), and a B.S. from Xidian University (2010). His work emphasizes fault-tolerant neural network architectures, adversarial attack mitigation, and secure hardware design. Notable contributions include frameworks like SHIELDeNN and Fiji-FIN, addressing vulnerabilities in quantized neural networks and inference accelerators. His research bridges emerging transistor technologies with cybersecurity solutions. Publications highlight trends in hardware-assisted cybersecurity, adversarial machine learning defense mechanisms, and the application of entropy modeling to analyze attack impacts. Ongoing studies explore post-Moore’s Law hardware innovations and backdoor attack countermeasures in large language models.
Casey E. Berger is an Assistant Professor of Physics at Bates College, affiliated with the Department of Physics and Astronomy. Their research focuses on quantum many-body systems, computational physics, and theoretical frameworks addressing challenges like the sign problem in quantum simulations. Berger employs advanced methods such as complex Langevin dynamics, Monte Carlo techniques, and machine learning to explore phenomena in rotating quantum matter, lattice field theories on curved manifolds, and quantum technologies for climate science. Key research areas include the development of numerical approaches to tackle sign problems in fermionic systems, the study of virial expansions in trapped fermions, and the application of quantum computing to environmental challenges. Their work bridges theoretical physics with computational innovation, emphasizing interdisciplinary solutions to fundamental problems in quantum mechanics and statistical physics. Berger’s publications span topics from quantum counter-terms in curved spacetime to the thermodynamics of rotating matter, reflecting a commitment to advancing both foundational and applied aspects of physics. Their research contributes to the broader goals of simulating complex quantum systems and leveraging quantum technologies for societal applications.
Gail Weiss is a Lecturer and Post-Doctoral Researcher at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Natural Language Processing Laboratory (NLP) within the School of Computer and Communication Sciences. She holds dual roles in research and teaching, contributing to both academic research and coursework in natural language processing and formal methods. Her research focuses on the intersection of formal language theory and machine learning, particularly exploring the capabilities of neural networks such as recurrent neural networks (RNNs) and transformers in recognizing formal languages. Recent work examines the vulnerability of higher education to AI tools and advances methods for extracting formal models from neural architectures. Teaching includes courses like 'Topics in Natural Language Processing' and contributes to the EDIC academic program. Her research has been published in top venues, addressing theoretical foundations of neural networks and practical applications in knowledge representation. She is based at INR 240 in Lausanne.
João Pimentel Nunes is a Full Professor at the Department of Mathematics, Higher Technical Institute (Technical University of Lisbon). His research focuses on Mathematical Physics, Gauge Theories, and String Theory, with a particular emphasis on geometric quantization and symplectic geometry. He is affiliated with the Center for Mathematical Analysis, Geometry and Dynamical Systems. Habilitation in Mathematics (IST, 2012) Ph.D. in Physics (Brandeis University, 1996) M.A. in Physics (Brandeis University, 1994) Degree in Technological Physics Engineering (IST, 1991) His recent publications explore topics like Mabuchi rays, Kahler metrics, and geometric quantization techniques. Notable collaborations include work with J. Mourão, T. Baier, and W. Kirwin. Research applications span quantum field theory, symplectic geometry, and complex structures in physics. He has taught courses on Mathematical Analysis II/III, Differential Geometry, and Topology at IST, emphasizing differential calculus in R^n, integration on manifolds, and classical vector calculus theorems like Stokes' and Green's. His teaching materials include detailed class summaries and problem sets.
Josh Baker is a Professor and Associate Vice President for Research at the University of Nevada, Reno, affiliated with the University of Nevada School of Medicine's Department of Pharmacology. His research focuses on the thermodynamics of muscle contraction, quantum heat engines, and entropic stability of biological systems. Ph.D. in Biochemistry, Biophysics, and Molecular Biology (University of Minnesota, 1999) B.S. in Physics (Hamline University, 1987) Research interests span muscle thermodynamics, mechanochemical coupling, and multiscale modeling of biological systems. His work explores the intersection of physics and biology to understand fundamental cellular processes. Current research trends examine quantum thermodynamics in muscle systems, entropic forces in cellular stability, and multiscale modeling approaches. Publications analyze phenomena from single molecule dynamics to whole-cell behaviors. Notable roles include Director of NIH NV INBRE since 2016 and leadership in research innovation at the University of Nevada. His work bridges experimental and theoretical approaches in biophysics.
