Find Academic Supervisors

• Quantum Engineering
• Quantum Optics
• Photonics
• +3 more

Rachel N Clark is a Lecturer in the School of Physics at the University of Bristol, actively contributing to the Quantum Engineering Technologies research group with a focus on quantum photonics and quantum light source development. Education: Master of Physics (MPhys) Master of Science (MSc) Doctor of Philosophy (PhD) Her research spans Quantum Engineering , Quantum Optics , and Photonics with concentrated expertise in solid-state quantum emitters—particularly aluminum nitride color centers—and single photon source engineering. Key investigations include evanescent-field photon collection enhancement, room-temperature quantum emitter characterization, and nanofabrication of quantum photonic devices for improved efficiency and integration. Analysis of her 13 publications (2022-2025) reveals dominant trends in aluminum nitride quantum emitter development, with 60% of works addressing room-temperature quantum light sources and photon collection efficiency. Her research bridges fundamental quantum optics with practical quantum technology applications, emphasizing scalable fabrication methods and metrology standards for quantum photonic systems. No scientific awards were documented in the provided materials. Information regarding graduate students, research grants, or specific laboratory teams beyond her Quantum Engineering Technologies affiliation was not indicated in the source texts.

• Mathematics
• Physics
• Biology
• +23 more

Andrei Khrennikov is Professor of Mathematics at the Department of Mathematics, Linnaeus University, where he also serves as director of the International Center for Mathematical Modeling (ICMM) . He leads a vibrant research group focused on interdisciplinary modeling in physics, biology, cognition, and social systems. Research Interests: His work spans a vast interdisciplinary landscape, including mathematical physics, p-adic and non-Archimedean analysis, quantum foundations, quantum-like modeling of cognition and decision-making, econophysics, and biological dynamics . He is a pioneer in applying quantum probability and formalism outside quantum physics, especially in psychology and social sciences. The Växjö series of quantum theory conferences , which he organizes, is the longest-running continuous conference series on quantum foundations, fostering dialogue between theorists, experimentalists, and philosophers. His recent publications (2021–2025) show a strong focus on quantum cognition, p-adic biology, entanglement models, and social laser theory , often leveraging generalized probability and open quantum systems frameworks. Scientific Contributions: Developed quantum-like models for cognition, decision-making, and biological processes. Pioneered use of p-adic and ultrametric analysis in genetics and brain dynamics. Advanced classical random field models as alternatives to quantum interpretations. Introduced the social laser model for collective emotional amplification in societies. He is actively involved in major research projects such as QUARTZ (Quantum Information Access and Retrieval Theory) and DYNALIFE (Information, Coding, and Biological Function) . His work bridges mathematics, physics, and cognitive science, promoting a unified framework for understanding complex systems through quantum-inspired tools.

Shuangping LiView profile

Assistant Professor

• Probability Theory
• High-Dimensional Statistics
• Theoretical Machine Learning
• +5 more

Shuangping Li is an Assistant Professor in the Department of Statistics and Data Science at Yale University. She was previously a Stein Fellow in the Department of Statistics at Stanford University (2022–2025). Her research lies at the intersection of probability theory, high-dimensional statistics, theoretical machine learning, and the theory of algorithms. Ph.D. in Applied and Computational Mathematics, Princeton University (2022) B.Sc. in Mathematics, University of Hong Kong Her research interests include probability theory , high-dimensional statistics , theoretical machine learning , and theory of algorithms . She investigates foundational aspects of random constraint satisfaction problems, neural networks, spectral methods, and phase transitions in high-dimensional models. Her work often draws from statistical physics and combinatorics to explain algorithmic behavior. The recent articles highlight a strong focus on binary perceptrons , clustering in network models , and algorithmic phase transitions . Keywords across publications include probability, theoretical computer science, machine learning, and statistical inference. Subfields reveal deep engagement with spin glass theory, discrepancy minimization, spectral embedding, and information-computation gaps. Scientific awards include: Stein Fellow, Department of Statistics, Stanford University (2022–2025) She has advised and taught at both Stanford and Yale, including courses such as Advanced Probability , Theory of Probability , and Stochastic Processes . She has organized seminars at Stanford and has delivered invited talks at institutions including Cornell, Duke, UC Berkeley, and Princeton. Her collaborative research involves prominent scholars such as Allan Sly, Emmanuel Abbe, and Tselil Schramm. There is no mention of external grants, but her postdoctoral fellowship suggests research funding support. She is involved in academic service through organizing the Stanford Statistics and Probability Seminars. She maintains an active research presence with publications in top venues like STOC, FOCS, COLT, ICLR, and journals such as Annals of Probability and Annals of Statistics .

• Nonparametric Statistics
• High-Dimensional Statistics
• Inverse Problems
• +3 more

Cristina Butucea is a Professor of Statistics and Machine Learning at ENSAE-CREST, Institut Polytechnique de Paris . She was nominated an IMS Fellow (2019) for her contributions to nonparametric and high-dimensional statistics. She has co-organized major conferences like Fréjus 2018 , Luminy 2019-2020 , and Oberwolfach 2021 , and serves as Associate Editor for ALEA . Fields of interest: Nonparametric statistics, quantum statistics, differential privacy, inverse problems, machine learning. Awards: IMS Fellowship, conference organization leadership. Research trends: Focuses on optimal estimation under privacy constraints, quantum state reconstruction, high-dimensional inference, and adaptive nonparametric methods. Email: Cristina.Butucea@ensea.fr | Cristina.Butucea@ip-paris.fr

Fabrizio RiguzziView profile

Professor

• Logic Programming
• Statistical Relational Artificial Intelligence
• Probabilistic Logic Programming
• +3 more

Fabrizio Riguzzi is a Full Professor at the Department of Mathematics and Computer Science of the University of Ferrara, Italy. His academic career spans over two decades at the same institution, having served as Associate Professor (2014-2020) and Assistant Professor/Ricercatore (1999-2014). He is an active researcher in the fields of Logic Programming and Statistical Relational Artificial Intelligence with numerous publications and leadership roles in international conferences. His educational background includes: PhD in Electronic and Computer Engineering from the University of Bologna (1999) Laurea in Computer Engineering from the University of Bologna (1995) Riguzzi's research focuses on probabilistic approaches to artificial intelligence, particularly probabilistic logic programming and statistical relational AI. His work bridges symbolic reasoning with probabilistic methods, developing frameworks for uncertain knowledge representation and reasoning. He has made significant contributions to probabilistic answer set programming, neuro-symbolic integration, and applications in areas like network intrusion detection and knowledge graph completion. His research demonstrates how logical formalisms can be enhanced with probabilistic reasoning to tackle real-world problems with uncertainty. An analysis of his recent publications reveals a strong trend toward integrating neural and symbolic approaches in AI, with significant work on probabilistic answer set programming frameworks. His research spans theoretical foundations of probabilistic logic programming, practical implementations, and applications in cybersecurity, knowledge graphs, and decision-making under uncertainty. The interdisciplinary nature of his work connects computer science theory with practical AI applications. His notable awards include: Alain Colmerauer 10-Year Test-of-Time Award at ICLP 2021 Best Paper Award for "BUNDLE: A Reasoner for Probabilistic Ontologies" at RR-2013 Highly Commended Paper Award for "Probabilistic declarative process mining" at KSEM 2010 Riguzzi has supervised several PhD students to completion, including Elena Bellodi, Riccardo Zese, and Giuseppe Cota, who have gone on to win prestigious awards for their theses. He has served in numerous editorial roles, including Associate Editor of the Journal of Artificial Intelligence Research and Editor in Chief of Intelligenza Artificiale. His leadership extends to organizing major conferences like ILP 2018 and serving on program committees for top AI venues including IJCAI, AAAI, and ECAI. He is a member of the ML@unife research group and has developed several online systems including cplint, TRILL, and an Online AUC calculator. His work has fostered collaborations across the AI research community, particularly in the areas of probabilistic logic programming and neuro-symbolic AI.

Richard AnantuaView profile

Assistant Professor

• Computational Astrophysics
• Black Holes
• General Relativity
• +7 more

Richard Anantua is an Assistant Professor in the Department of Physics and Astronomy within the College of Sciences at the University of Texas at San Antonio (UTSA), and also serves as an Adjunct Professor at Rice University since 2024. His research group is pioneering Event Horizon Telescope (EHT) science in Texas, focusing on computational and theoretical astrophysics related to black holes and relativistic phenomena. Assistant Professor, UTSA – 2022–Present Adjunct Professor, Rice University – 2024–Present Postdoctoral Fellow, Harvard-Smithsonian Center for Astrophysics – 2019–2021 Postdoctoral Fellow, UC Berkeley – 2016–2019 Education: Ph.D. in Physics – Stanford University M.S. in Physics – Stanford University B.S. in Physics and Philosophy – Yale University B.S. in Economics and Mathematics – Yale University Ed.M. in Education Policy and Management – Harvard University Richard Anantua’s research focuses on computational astrophysics , particularly the modeling of emission near supermassive black holes using general relativistic magnetohydrodynamic (GRMHD) simulations. His work bridges theoretical models with observational data from cutting-edge instruments like the Event Horizon Telescope (EHT) and its next-generation counterpart (ngEHT). Key areas include black hole accretion flows, relativistic jets, plasma physics, and neutrino emission. He has developed methodologies to connect simulation variables—such as electron temperature, magnetic field strength, and current density—to observable signatures across the electromagnetic spectrum. The recent publications from his group reflect a strong trend in high-resolution modeling of black hole environments , with emphasis on M87, Sgr A*, and theoretical constructs like primordial black holes and dark matter alternatives. These works integrate numerical simulations with observational predictions, particularly for EHT and ngEHT capabilities, covering emission morphology, jet stability, plasma composition, and neutrino physics. The interdisciplinary nature of his research spans astrophysics, plasma physics, and computational science. Scientific Engagement and Mentorship: Active mentor of postdoctoral researchers, PhD students, master’s students, and undergraduates at UTSA. Group members regularly present at national conferences such as the American Astronomical Society (AAS) and SCEECS. Supervised master’s thesis on GRMHD emission modeling. Anantua has been involved in major collaborations, including the Event Horizon Telescope Collaboration during his postdoc at Harvard, and continues to lead a vibrant research group at UTSA. His lab focuses on advancing computational tools for black hole imaging and theoretical modeling of extreme astrophysical environments.

• Quantum Physics
• Quantum Computing
• Quantum Error Correction
• +3 more

Dr. Dominic Williamson is a theoretical quantum physicist and DECRA Research Fellow at the School of Physics, University of Sydney. He specializes in quantum phases of matter and their applications to quantum error correction and computing. His work bridges condensed matter theory and quantum information science, focusing on fracton topological phases and fault-tolerant quantum architectures. Education: PhD in Physics from the University of Vienna (2017); Postdoctoral research at Yale University, Stanford University, and IBM Quantum. Current roles include faculty membership at the University of Sydney’s Quantum Science Group and prior industry experience at IBM and PsiQuantum. Research interests: Topological phases of matter, quantum error correction codes (e.g., fracton codes, QLDPC systems), fault-tolerant quantum computing architectures, and non-Abelian anyon systems. Recent breakthroughs include low-overhead quantum architectures and novel approaches to parallelized logical measurements. Grants: 2022 ARC Discovery Early Career Researcher Award for topological phases in quantum computation. Collaborations include projects on gauging logical operators and quantum code surgery. Professional activities: Editor for Quantum , frequent speaker at international conferences, and mentor for students at all levels (undergraduate to postdoctoral). Active in open-source research and public engagement through platforms like arXiv and Google Scholar.

• Beyond the Standard Model
• Supersymmetry
• String Theory
• +3 more

Professor Steve Abel is a Professor in the Department of Mathematical Sciences and the Department of Physics at Durham University, with additional affiliation to the Institute for Particle Physics Phenomenology. His research spans theoretical physics with a strong focus on string theory, particle physics phenomenology, and emerging applications of quantum computing. Professor Abel's research interests include: Beyond the Standard Model physics Supersymmetry and string model building Applications of quantum computing to particle physics Genetic algorithms in theoretical physics Non-supersymmetric string vacua Analysis of Professor Abel's recent publications reveals a significant shift toward interdisciplinary research combining traditional theoretical physics with cutting-edge computational techniques. His work increasingly focuses on applying quantum computing and machine learning methods to solve complex problems in string theory and particle physics. Many recent papers explore quantum simulation of field theories, quantum annealing for string model building, and genetic algorithms for solving physics problems. This represents a convergence of theoretical physics with computational science that is transforming how fundamental physics research is conducted. Professor Abel has received recognition for his work, most notably a Cern Theory 6 month Scientific Associateship. His research collaborations span international institutions across Europe and North America, reflecting the global nature of theoretical physics research. Professor Abel actively supervises graduate students, including Puya Mirkarimi. His research program likely involves collaboration with various research groups at Durham University working on theoretical particle physics, quantum computing applications, and computational methods for theoretical physics problems.

Wenchao GeView profile

Assistant Professor

• Quantum Information Science
• Quantum Optics
• Quantum Metrology
• +3 more

Wenchao Ge is an Assistant Professor in the Department of Physics at the University of Rhode Island . Previously, he held faculty positions at Southern Illinois University (2020–2022) and was a postdoctoral researcher at institutions including Texas A&M University and the U.S. Army Research Lab. He earned his Ph.D. in Physics from Texas A&M University (2015) and a B.S. in Applied Physics from Xi’an Jiaotong University (2009). His research focuses on theoretical quantum optics and quantum information science , with emphasis on quantum sensing, quantum computing, and quantum communication. His group explores fundamental limits of quantum mechanics for information processing, including protocols for multi-parameter sensing, parametric amplification in trapped-ion systems, and quantum resource theories. He leads the Ge Quantum Theory Group , which collaborates with experimentalists to advance quantum technologies. Research interests: Quantum metrology, quantum computing, trapped-ion systems, and optomechanical systems. Notable achievements: Developed protocols for Heisenberg-limited quantum sensing and quantum-enhanced entangling gates. Published in Nature Physics , Phys. Rev. Lett. , and Phys. Rev. A . Teaching: Courses on quantum entanglement and quantum information science. He has received grants from NSF (ExpandQISE and quantum sensing programs) and the SIU Open Textbook Initiative. He was elected Secretary/Treasurer of the APS New England Section (2023) and actively participates in international conferences and quantum education initiatives. His group advises graduate and undergraduate students on projects spanning theoretical and applied quantum physics, including summer internships and capstone research.

Nicolás QuesadaView profile

Associate Professor

• Quantum Information
• Quantum Computing
• Quantum Optics
• +7 more

Nicolás Quesada is an Associate Professor in the Department of Engineering Physics at Polytechnique Montréal, where he holds the MEI Chair in Quantum Photonics. He serves as Director of COPL (Centre d'optique, photonique et laser) and is a member of INTRIQ (Institut transdisciplinaire d'informatique quantique). His research program focuses on quantum information, quantum computing, and quantum optics, with particular emphasis on photonic implementations of quantum technologies. Dr. Quesada earned his B.Sc. in Physics from Universidad de Antioquia in 2010, followed by M.Sc. and Ph.D. degrees in Physics from the University of Toronto. During his doctoral studies, he was awarded both Vanier and Stoicheff scholarships. Prior to joining Polytechnique Montréal, he worked at Xanadu Quantum Technologies as lead developer of the Strawberry Fields and The Walrus software libraries, where he led theoretical efforts demonstrating photonic quantum advantage. His research interests span quantum photonics, quantum computing, and quantum optics, with specific focus on Gaussian Boson Sampling, squeezed light generation, non-Gaussian light sources, and quantum benchmarking techniques. His group develops theoretical frameworks and computational tools for next-generation quantum light sources needed for fault-tolerant quantum computers, quantum communication networks, and quantum sensors. His work bridges theoretical quantum information science with practical photonic implementations. Analysis of his recent publications reveals a strong focus on advancing Gaussian Boson Sampling as a platform for quantum advantage, developing mathematical frameworks for quantum optics, and engineering practical photonic quantum devices. His work spans from fundamental quantum optics to applied quantum computing, with increasing emphasis on verification and benchmarking of quantum computational advantage. Dr. Quesada has received notable recognition including the Vanier Canada Graduate Scholarship and the Stoicheff Scholarship during his doctoral studies. His research has attracted significant funding, including a $6 million grant for quantum projects at Polytechnique Montréal announced in January 2025 and involvement in a $1.91 million NSERC quantum sensing project led by Professor Denis Seletskiy. He has supervised two Master's students to completion in 2024: Dalbec-Constant, N. who worked on photon counting from transition-edge sensors, and Zhao, J. who researched optimal pumps for spontaneous parametric down-conversion. His research group collaborates extensively with both academic and industry partners in the quantum technology sector. As Director of COPL, he oversees one of Canada's leading photonics research centers, facilitating interdisciplinary research across quantum optics, classical optics, and laser technologies.

Roman FriggView profile

Professor

• General philosophy of science
• Philosophy of physics
• Statistical mechanics
• +11 more

Roman Frigg is Professor of Philosophy at the London School of Economics and Political Science (LSE) , affiliated with the Department of Philosophy, Logic and Scientific Method . He serves as Director of the Centre for Philosophy of Natural and Social Science (CPNSS) and Co-Director of the Centre for the Analysis of the Time Series (CATS) . Holding a PhD from the University of London and MScs in theoretical physics and philosophy from the University of Basel, his research spans philosophy of science , statistical mechanics , and climate modeling . Education : PhD (University of London), MSc (University of Basel: Theoretical Physics, Philosophy) His work addresses foundational questions in statistical mechanics and thermodynamics , including equilibrium theory, entropy interpretation, and relations between Boltzmannian and Gibbsian frameworks. Recent publications focus on probabilistic forecasts in chaotic climate models , culminating in the co-authored book The Fundamentals of Thermodynamics (Springer, 2025). Articles explore topics like the Ergodic Hierarchy , GRW quantum theory , and robustness analysis in climate science. Roman has made significant contributions to reconciling deterministic dynamics with objective probability via Humean interpretations. His collaborations with Charlotte Werndl, Carl Hoefer, and David Lavis have produced key insights into typicality , chaos-randomness relations , and non-equilibrium thermodynamics . Scientific Awards : Friedrich Wilhelm Bessel Research Award (Alexander von Humboldt Foundation) Roman supervises PhD students on topics ranging from scientific representation to quantum mechanics and climate policy uncertainty . His website provides access to his publications and teaching materials.

Andrej BogdanovView profile

Professor

• Cryptography
• Computational Complexity
• Pseudorandomness
• +6 more

Andrej Bogdanov is a Professor at the University of Ottawa in the School of Electrical Engineering and Computer Science . He earned his B.S. and M.Eng. from MIT and Ph.D. from UC Berkeley . Before joining Ottawa, he held positions at the Chinese University of Hong Kong , ITCS (Tsinghua) , DIMACS (Rutgers) , and the Institute for Advanced Study . He has served as a Visiting Professor at the Tokyo Institute of Technology (2013) and the Simons Institute (2017, 2021). Research Interests : Computational complexity, cryptography foundations, pseudorandomness, one-way functions, property testing, quantum algorithms, and sublinear-time algorithms. Teaching : Courses on Discrete Mathematics, Great Algorithms, Computational Complexity, and Cryptography at University of Ottawa, Chinese University of Hong Kong, and Rutgers University. Publications : 15+ recent works in TCC , CRYPTO , ICALP , RANDOM , and journals like Journal of Cryptology and Theory of Computing . Service : Program co-chair for SAC 2026 , and committee member for major conferences including CRYPTO , TCC , Eurocrypt , and FOCS . Advising : 12 current and former Ph.D./M.Phil. students, with postdoctoral advisees at institutions like IIT Palakkad and Academia Sinica . His work bridges theoretical computer science with applications in cryptography, quantum computing, and network security.

Claudia KlüppelbergView profile

Professor

• Applied Probability
• Mathematical Statistics
• Financial Risk Management
• +3 more

Claudia Klüppelberg is a Professor and Chair of Mathematical Statistics at the Center for Mathematical Sciences, Technische Universität München (TUM). Her academic journey includes positions at ETH Zurich, University of Mainz, and TUM since 1997. She holds a Carl von Linde Senior Fellowship at TUM-IAS, focusing on Risk Analysis and Stochastic Modeling. Her research bridges applied probability, statistics, and their applications in finance and insurance, emphasizing extreme value theory, risk processes, and stochastic networks. She has received prestigious awards such as the New Frontiers in Risk Management Award (2007) and Cross of Merit (2001). Her work addresses real-world challenges in financial risk management, including systemic risk in networks and operational risk modeling. Her recent publications explore causal analysis of extreme risks in networks, max-linear models, and Bayesian networks for extreme events. She contributes to academic leadership as an editorial board member and advisor, promoting interdisciplinary stochastic sciences.

Michael ZurelView profile

Research Fellow

• Quantum Information
• Quantum Computation
• Quantum Contextuality
• +7 more

Michael Zurel is a NSERC Postdoctoral Fellow in the Department of Mathematics at Simon Fraser University, working under Dr. Nadish de Silva, Canada Research Chair in the Mathematics of Quantum Computation. His research focuses on foundational aspects of quantum computation, quantum information, and nonclassical physics. Key interests include quantum contextuality, negativity in quasiprobability representations, and classical simulation algorithms for quantum systems. He holds a PhD, MSc, and BSc in Physics and Mathematics from the University of British Columbia (2024, 2020, 2019), all supervised by Dr. Robert Raussendorf. His doctoral work explored classical descriptions of quantum computations via hidden variable models and quasiprobability representations. His master’s thesis addressed hidden variable models and classical simulation algorithms for quantum computation with magic states on qubits. Research interests emphasize bridging quantum foundations with computational efficiency, particularly how nonclassical features like contextuality enable quantum advantage. Collaborators include prominent figures such as Robert Raussendorf, Juani Bermejo-Vega, and Cihan Okay. His scientific achievements include the NSERC Postdoctoral Fellowship. Advising and grants are not explicitly detailed, but his work is supported by foundational research grants. He collaborates actively within quantum information theory and computational physics communities.

• Quantum Computing
• Atomic Electronics
• Quantum Devices
• +2 more

Professor Michelle Y Simmons AO is a Laureate Fellow and Director of the Centre of Excellence for Quantum Computation and Communication Technology at UNSW Sydney. She founded Silicon Quantum Computing (SQC), Australia's first vertically integrated quantum computing company, and pioneered atomic electronics by creating devices in silicon with atomic precision. Research focuses on quantum computing, spin qubits, and atomic-scale engineering Key achievements: first quantum gates with donor atoms, 3D atomic chip architecture Recent publications highlight advancements in silicon qubit fabrication, quantum coherence, multi-qubit control, and noise mitigation. These works emphasize scalable architectures and practical quantum computing solutions. Scientific awards include: 2023 Prime Minister’s Prize for Science 2023 Swiss Erna Hamburger Prize 2022 AmCham Alliance Award 2021 Bakerian Medal 2018 Australian of the Year 2017 L’Oréal-UNESCO Laureate Her leadership in quantum research has secured major industry partnerships (CBA, Telstra, Commonwealth Bank) and driven the development of silicon-based quantum technologies. Current work involves optimizing spin qubit performance and exploring applications of quantum computing in materials science and information processing.