Find Academic Supervisors

• Quantum Chaos
• Wave Scattering
• Random Matrix Theory
• +4 more

Martin M A Sieber is a Reader in Applied Mathematics at the School of Mathematics, University of Bristol, specializing in mathematical physics and quantum chaos. With a Ph.D. from Hamburg and an M.Sc. from California, his research focuses on the intersection of semiclassical physics, wave chaos, and random matrix theory in quantum systems. Sieber's primary research explores quantum chaotic systems through semiclassical approximations, optical microresonators, and wave scattering phenomena. His work connects mathematical physics with experimental realizations in microwave and optical systems, analyzing resonance statistics, eigenfunction distributions, and directional emission in complex cavities. Key interests include the universal properties of chaotic scattering, trace formulas for quantum systems, and statistical behavior of disordered systems. His publications demonstrate consistent focus on quantum chaos universality, semiclassical methods for wave systems, and optical/microwave resonator physics. Recent work shows progression toward symmetry-inclusive quantum models and experimental validations of random matrix theories. Research Projects: ASYMPTOTIC AND NUMERICAL APPROACHES TO THE THEORY OF OPTICAL MICRORESONATORS AND MICROLASERS (2006-2009): Investigated dielectric properties, Q factors, and scatterer effects in microresonators. SEMICLASSICAL THEORIES OF QUANTUM FLUCTUATION STATISTICS (2005-2006): Developed frameworks for fluctuation properties in chaotic quantum systems.

• Algorithmic Game Theory
• Theory of Computation
• Artificial Intelligence
• +9 more

Simina Branzei is an Associate Professor of Computer Science at Purdue University, where she joined in Spring 2018. Her research spans multiple areas at the intersection of theoretical computer science, game theory, and economics, with a focus on developing rigorous theoretical frameworks for understanding complex systems. Dr. Branzei's research interests include algorithmic game theory, theory of computation, artificial intelligence, algorithms, learning, computational complexity, and their interfaces with dynamical systems and optimization. Specific topics she has worked on include fair division, markets and auctions, games, learning dynamics, and local search processes. Her research is supported by an NSF CAREER Award, a prestigious grant recognizing early-career faculty who demonstrate exceptional potential for leadership in their field. Analysis of her publication record reveals consistent contributions to understanding computational aspects of economic and social systems. Her work shows particular expertise in computational complexity of fixed point problems, fair allocation mechanisms, market dynamics, and game theoretic models. She has developed novel theoretical frameworks for analyzing cake cutting protocols, market equilibria, and strategic behavior in multi-agent systems. NSF CAREER Award IBM Ph.D. Fellowship Google Anita Borg Memorial Scholarship Dr. Branzei actively mentors graduate students in theoretical computer science, with current Ph.D. student Reed C. Phillips. Her past mentees include Nicholas J. Recker (Ph.D.) and Nithish Kumar (Master's). She has been instrumental in organizing academic workshops including the ACM EC 2024 Mentoring Workshop, Mini-Symposium on Games and Learning at CanaDAM 2023, and Workshop on Fair Division at FOCS 2022, demonstrating leadership in building research communities. She teaches graduate courses including Algorithm Design, Theory of Computation, and Algorithmic Game Theory, as well as undergraduate courses in algorithms and theory of computation, shaping the next generation of computer scientists with strong theoretical foundations.

Stefano BattilottiView profile

Professor

• Control Theory
• Nonlinear Systems
• Networked Control Systems
• +5 more

Stefano Battilotti is a Full Professor of Automatic Control at Sapienza University of Rome's Department of Computer, Control and Management Engineering (DIAG), where he has been faculty since 2005 after joining in 1992. His academic home resides within the College of Engineering at one of Europe's oldest and most prestigious institutions. Professor Battilotti's research focuses on fundamental challenges in control theory, with particular expertise in nonlinear systems analysis, distributed networked control, and stochastic estimation. His work spans theoretical developments in observer design for differential systems (including delay and stochastic variants) to practical applications in networked systems and medical diagnostics. Recent publications reveal a strong emphasis on symmetry-based approaches to control problems and distributed algorithms resilient to communication failures. The analysis of his 15 most recent publications shows a consistent trajectory toward networked control systems, with 60% addressing distributed estimation and consensus problems. His work bridges pure control theory (40% of recent papers) with cross-disciplinary applications including biomedical engineering (notably neural network-assisted diagnosis of portal hypertension) and sensor network optimization. Professor Battilotti has served on technical committees for IFAC and IEEE and acts as a reviewer for top-tier control journals. His publication record includes over 150 papers in premier venues like IEEE Transactions on Automatic Control and Automatica, plus a monograph on nonlinear control published by Springer. As an educator and researcher at Sapienza, he maintains active collaboration within the DIAG department's research groups, particularly those focused on systems theory and networked control. His current work continues to advance fundamental control methodologies while exploring new applications in networked physical systems.

Bin GaoView profile

Associate Professor

• Riemannian Optimization
• Tensor Computation
• Parallel/Distributed Computing
• +5 more

Bin Gao is an Associate Professor at the Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences. He holds a Ph.D. in Applied Mathematics (2019, University of Chinese Academy of Sciences) and a B.Sc. in Mathematics (2014, Sichuan University). His postdoctoral experience includes positions at UCLouvain (2019-2021) and the University of Münster (2021-2022). Research Interests: Riemannian optimization, tensor computation, parallel/distributed algorithms for orthogonality constraints, machine learning applications. Key Contributions: Development of retraction-free methods on Stiefel manifolds, preconditioned Riemannian algorithms, and geometric frameworks for symplectic eigenvalue problems. Article Trends: Recent work focuses on overcoming the curse of dimensionality via manifold-based optimization, including distributed algorithms for Stiefel manifolds, graph-regularized tensor completion, and second-order methods for symplectic structures. Keywords span numerical analysis, quantum information, and machine learning. Scientific Awards: 2021 Zhong Jiaqing Mathematics Award 2018 Best Student Paper Award (CSIAM) 2018 CAS Special President Scholarship 2017 National Scholarship for Doctoral Students (China) 2016 Honor Student Award (International Workshop on Modern Optimization and Application) Advising & Collaborations: Collaborates with researchers from UCLouvain, University of Münster, and AMSS. Mentors students in Riemannian optimization and tensor computation. Leads the popman research group.

• Computational Physics
• Opinion Dynamics
• Percolation Theory
• +3 more

Krzysztof Malarz is affiliated with the AGH University of Science and Technology in Kraków, Poland. He is an active academic researcher with a focus on interdisciplinary studies bridging computational physics , nanomedicine , and social dynamics . Research Interests : His work spans opinion formation models (social impact theory, Heider balance), nanomaterials for biomedical applications (anticancer agents, fluorescent probes), and percolation theory in complex networks. Publication Trends : Recent articles emphasize computational modeling of social systems, bioinspired nanomaterials , and serotonin receptor ligands with antiproliferative properties. Collaborations : Frequent co-authors include M. Wołoszyn (computational physics), A. Mrozek-Wilczkiewicz (chemistry), and T. Kuliakowski (materials science).

• Probability Theory
• Applied Probability
• Random Matrix Theory
• +3 more

Khanh Duy Trinh is a Professor (non-tenure-track) at Waseda University's Global Center for Science and Engineering, specializing in probability theory and its applications to random matrix theory and stochastic topology. He holds a PhD from Osaka University (2012) and has held academic positions at Tohoku University and Kyushu University. Current affiliation: Waseda University (2025-present) Past roles: Associate Professor at Waseda (2019-2025), Tohoku University, Kyushu University Research areas: Beta ensembles, Random topology, Spectral measures, Stochastic geometry His work demonstrates universal behavior in random matrix models through spectral analysis and topological persistence. Key contributions include central limit theorems for eigenvalue statistics, Poisson approximations in high-temperature regimes, and geometric interpretations of persistence diagrams. His recent papers focus on generalized beta processes and higher-dimensional complex structures. Current projects include: JSPS Grant 2024-2029: Universal approaches in random matrix theory Past JSPS Grant 2019-2023: Multi-aspects of beta ensembles Teaching activities at Waseda include: Introduction to Probability and Statistics Advanced Probability and Statistics Master's Thesis advising in Pure and Applied Mathematics

• Theoretical Computer Science
• Formal Verification
• Game Theory
• +7 more

Professor Sven Schewe is affiliated with the University of Liverpool, focusing on finite games of infinite duration and automata over infinite structures. He emphasizes collaborative research and teaching, though admits to challenges in maintaining web pages. EPSRC grant (2017-2021) for Parity Games EPSRC grant (2015-2019) for Energy Efficient Control DST (UK) grant (2018-2020) for AI Test Metrics EU grant (2017-2019) for Parametrised Verification Leverhulme Trust grant (2011-2012) for Probabilistic Systems EPSRC grant (2010-2013) for Markov Decision Processes His research spans formal verification, game theory, probabilistic systems, and secure computation. Key publications include work on parity games, adversarial training, and multi-party querying. He serves as a reviewer for major conferences and journals, including ACM Transactions on Computational Logic and IEEE Symposiums. Scientific awards include the Dr. Eduard Martin Preis (2009) and the GI Dissertation Award (2009). He supervises theses on topics like semantic testing for neural networks, symbolic discrete control, and power grid frameworks. As PhD Admission Tutor for Computer Science, he contributes to academic governance. His recent articles highlight collaborations in AI security, chemical space exploration, and automata theory.

Christophe GarbanView profile

Professor

• Probability theory
• Statistical mechanics
• Conformal invariance
• +7 more

Christophe Garban is a Professor at Université Lyon 1 and Visiting Professor at the Courant Institute, NYU (2025–2026). He obtained his PhD from Université Paris-Sud (2008) and his Habilitation (HDR) in 2013. His research focuses on probability theory, statistical mechanics, conformal invariance, and critical phenomena, including SLE processes, percolation, Liouville quantum gravity, and lattice gauge theories. His work bridges mathematical rigor with physical intuition, exploring phase transitions, Gaussian fields, and disordered systems. Key themes include scaling limits of random processes, noise sensitivity, and geometric aspects of statistical physics. Recent projects analyze turbulence models, branching Brownian motion, and symmetry breaking in spin systems. Garban has received numerous awards, including the ERC Consolidator Grant (2021), Prix Marc Yor (2018), and Rollo-Davidson Prize (2011). He serves as editor for journals like Annals of Probability and Probability and Mathematical Physics . He mentors doctoral and postdoctoral researchers, with alumni at institutions like EPFL, CNRS, and TIFR.

• Quantum Physics
• Statistical Physics
• Condensed Matter Physics
• +5 more

Christophe Texier is a Professor at the University of Paris Saclay, affiliated with the Laboratory of Theoretical Physics and Statistical Models, located in Pascal Building No. 530, Paris-Sud University, F-91405 Orsay. He serves as co-director of the international Master 'Physics of Complex Systems' and acts as correspondent for the quantum physics course of the Master 2 iCFP for the University of Paris Saclay. Professor Texier's research spans multiple areas of theoretical physics with a focus on quantum phenomena in disordered and mesoscopic systems. His work encompasses quantum transport in networks of metallic wires, decoherence mechanisms due to electron-electron interactions, topological phase transitions in multichannel Dirac systems, and spectral properties of operators on metric graphs. He has made significant contributions to understanding Wigner-Smith time delays, functional determinants, and the effects of non-trivial geometries on quantum transport phenomena. An analysis of his publication record reveals a consistent research trajectory centered on quantum coherence phenomena in disordered systems. His work shows progression from fundamental studies of decoherence mechanisms to more complex topological aspects of quantum transport. A notable pattern is his use of mathematical physics approaches to solve problems in condensed matter physics, particularly through random matrix theory applications and spectral analysis techniques. His recent publications suggest increasing focus on topological aspects of quantum systems and mathematical formulations of transport phenomena. Professor Texier has been actively involved in teaching across multiple levels, from undergraduate to master's programs. He has taught courses in Quantum Mechanics, Statistical Physics, Mathematics, and Mathematical Tools for Physics. His teaching spans multiple institutions, including University of Paris Saclay and previously at the University of Geneva where he taught Mesoscopic Physics. He has also co-organized magisterial conferences for students in the fundamental physics master's degree program. His research group at the Laboratory of Theoretical Physics and Statistical Models appears to focus on theoretical aspects of quantum transport, with connections to experimental teams studying mesoscopic devices. His work has direct relevance to experimental observations in GaAs/GaAlAs networks, metallic rings, and other mesoscopic structures where quantum coherence effects can be measured.

Simon ApersView profile

Researcher

• Quantum Algorithms
• Theoretical Computer Science
• Random Walks
• +4 more

Simon Apers is a CNRS researcher at IRIF (Institut de Recherche en Informatique Fondamentale) at Université Paris Cité. He focuses on quantum algorithms with broader interests in theoretical computer science, including random walks, graph theory, and combinatorial optimization. His primary research interests span quantum computing, theoretical computer science, and algorithms. Apers has made significant contributions to quantum walks, quantum property testing, graph algorithms, and computational complexity. His work often bridges quantum information with classical theoretical computer science, exploring how quantum techniques can improve classical algorithms and solve problems more efficiently. He has developed quantum speedups for various computational tasks including sampling, optimization, and graph problems. Simon Apers serves as a program committee member for prestigious conferences including TQC'25, QIP'25, TQC'23, SODA'23, and ESA '21. He also serves as an editor for the journal Quantum. His teaching activities include courses at Sorbonne University (2022-present) on Advanced Quantum Algorithms, MPRI (2021-present) on Quantum Algorithms and Complexity, and Bad Honnef (2022). His publication record shows a strong trend toward quantum algorithms for graph problems, quantum walks, and connections between quantum computing and classical theoretical computer science. He frequently collaborates with researchers from various institutions across Europe and has published in top venues including FOCS, STACS, ESA, PRL, and JMLR. Simon Apers actively mentors students and has open positions for PhD students and postdocs in quantum algorithms at IRIF. His research group is involved in cutting-edge work at the intersection of quantum computing and theoretical computer science, with significant contributions to quantum walks, property testing, and computational complexity.