Find Academic Supervisors

Shing-Tung YauView profile

Professor

• Differential Geometry
• Mathematical Physics
• General Relativity
• +3 more

Shing-Tung Yau is a distinguished mathematician and professor associated with the Shing-Tung Yau Center at Southeast University's School of Physics, reflecting his profound influence in mathematical physics. His career spans premier institutions including Harvard University (emeritus) and Tsinghua University, where he holds active positions. Yau's research centers on differential geometry , mathematical physics , and geometric analysis , with transformative work on Calabi-Yau manifolds underpinning string theory. His investigations into Einstein's equations, black hole thermodynamics, and geometric flows bridge pure mathematics and theoretical physics, driving advancements in quantum gravity and mirror symmetry. His publications reveal consistent focus on geometric structures in theoretical physics, particularly Calabi-Yau applications in string compactification and geometric flows for singularity analysis. Recent works emphasize Kähler-Einstein metrics and stability in algebraic geometry. Scientific accolades include: Fields Medal (1982) for contributions to partial differential equations and Calabi conjecture Wolf Prize (2010) for geometric analysis breakthroughs MacArthur Fellowship (1985) and Crafoord Prize (1994) National Medal of Science (1997) for unifying geometry and physics Yau has mentored over 50 doctoral students, including Gang Tian and Huai-Dong Cao, shaping modern geometric analysis. He leads collaborative initiatives like the Harvard-Yau Center and Tsinghua's Mathematical Sciences Center, fostering cross-disciplinary research in geometric methods for quantum gravity. Current efforts focus on geometric foundations of quantum information and gravitational wave mathematics.

Mihai NicaView profile

Assistant Professor

• Deep Neural Networks (DNNs)
• Probability Theory
• Stochastic Processes
• +4 more

Prof. Mihai Nica is an Assistant Professor in the Department of Mathematics and Statistics at the University of Guelph, affiliated with the CARE-AI institute and Vector Institute. His research focuses on probability theory, stochastic processes, and their applications to machine learning, particularly deep neural networks (DNNs). He explores scaling limits of DNNs, numerical methods using neural networks, and phase transitions in high-dimensional learning problems. Education: B.Math in Pure & Applied Math with Physics Option, University of Waterloo PhD in Mathematics, Courant Institute of Mathematical Sciences, New York University Postdoctoral Fellow at University of Toronto (supervised by Jeremy Quastel) Research Interests: His work bridges mathematical theory and practical AI applications, emphasizing topics like the neural tangent kernel, KPZ universality class, and stochastic processes in machine learning. Notable contributions include studies on neural network dynamics, random matrices, and directed polymers. Publications: Over 15 peer-reviewed articles in journals like Communications in Pure and Applied Mathematics and Electronic Journal of Probability , with a focus on theoretical foundations of AI and stochastic systems. Recent work explores infinite-width limits of neural networks and their connections to differential equations. Labs/Teams: Affiliated with CARE-AI (bridging mathematics, engineering, and philosophy) and the Vector Institute, fostering interdisciplinary collaborations.

Agostino CortesiView profile

Professor

• Software Engineering
• Static Analysis
• Cybersecurity
• +5 more

Agostino Cortesi is a Full Professor at Ca' Foscari University of Venice , affiliated with the Department of Environmental Sciences, Informatics and Statistics. He serves as Rector's Delegate for Research Quality Assessment and Deputy Coordinator of the Scientific Committee for the Innovation Ecosystem Project. His academic career includes a PhD in Applied Mathematics and Informatics from the University of Padova (1992), a postdoctoral fellowship at Brown University, and visiting professor roles at institutions such as the University of Illinois and École Normale Supérieure Paris. Research interests focus on software engineering , static analysis , security applications , and abstract interpretation . He has pioneered techniques for formal verification of software systems and explored cybersecurity in e-Government and robotics. His work spans over 200 publications in top journals and conferences (e.g., ACM TOPLAS, IEEE TSE, POPL, PLDI). Key contributions include advancements in abstract domains for behavioral property verification and security-oriented analysis frameworks. He has held leadership roles including Vice-Rector at Ca' Foscari, Dean of Computer Science programs, and Chair of the Department of Computer Science. Cortesi coordinates EU Horizon 2020 projects (e.g., Families_Share €1.6M) and regional initiatives like CEVID (€360K). He founded Factors , a university spin-off focused on robotic systems verification, which won the 2020 Veneto SmartCup ICT Prize. Education: PhD in Applied Mathematics and Informatics (1992, University of Padova) Editorial Roles: Co-Editor-in-Chief of Springer’s 'Services and Business Process Reengineering', and member of editorial boards for 'Computer Languages' and others Grants: Over €3M in EU and regional funding for projects in cybersecurity, Industry 4.0, and digital innovation Teaching includes courses on Software Correctness , Data Programming , and Computer Networks across Computer Science and Management programs. His research lab actively engages in industrial partnerships with Cisco, Leonardo, and AGID (Italy’s Digital Agency).

Anastasia VolovichView profile

Professor

• Quantum Field Theory
• String Theory
• General Relativity
• +3 more

Anastasia Volovich is a Professor of Physics at Brown University, specializing in theoretical physics with a focus on quantum field theory, string theory, general relativity, and their mathematical foundations. Her research explores hidden mathematical structures in scattering amplitudes to advance understanding of gauge and gravity theories. B.A. and M.A. in Physics, Moscow State University (1999) Ph.D. in Theoretical Physics, Harvard University (2002) Her work on scattering amplitudes involves cluster algebras, polylogarithms, and celestial holography. Recent publications address symbol alphabets, Landau singularities, and Yangian invariants in high-energy physics. Notable honors include: APS Fellowship (2019) IBM Einstein Fellowship (2017) Blavatnik National Finalist (2016-2018) Simons Investigator Award (2015) DOE Early Career Award (2011) NSF CAREER Award (2007) White House PECASE (2008) She has held editorial roles at Letters in Mathematical Physics and Physics Letters B , and her research is funded by the Department of Energy and Simons Foundation.

Violetta LonatiView profile

Assistant Professor

• Formal Languages and Automata
• Computer Science Education
• Theoretical Computer Science
• +2 more

Violetta Lonati is an Assistant Professor at the University of Milan 's Department of Computer Science since 2005. Her research spans Formal Languages and Automata (operator precedence languages, Wang automata, tiling systems) and Computer Science Education . She co-authored over 15 publications in theoretical computer science and education, focusing on 2D language recognition, logic characterization of automata, and pattern statistics in stochastic models. Education : PhD in Computer Science (2005) and Laurea in Mathematics (2001) from University of Milan Research Groups : ALaDDIn Lab for Didactics and Dissemination of Informatics, Bebras International Initiative Her work on Wang automata established their equivalence to tiling systems while introducing deterministic variants. In education, she designed workshops for schools and contributed to Italy's national computing curriculum proposal (2019). She held leadership roles at ACM ITiCSE (WG5 leader 2022), served as Associate Program Chair (2019-2022), and reviewed for top venues like ICER and SIGCSE TS. She received Google CS[4]HS and Informatics Europe awards for her educational contributions. Key Publications (2017-2001): Input-driven locally parsable languages (TCS 2017) Operator precedence logic characterization (SICOMP 2015) Snake-deterministic tiling systems (MFCS 2009) Graph fibrations and PageRank (RAIRO 2006) Pattern statistics in rational models (STACS 2005) Scientific awards include Google CS[4]HS (2011, 2017, 2019) and the Informatics Europe Best Practices in Education (2016). As part of ALaDDIn, she developed teacher training programs and graduate courses on computing education. Her teaching experience covers Algorithms & Data Structures (2013-2023), Computer Science Teaching (2014-2023), and courses for Biotechnology and Geological Sciences programs (2005-2007).

• Programming Languages
• Formal Verification
• Compilers
• +5 more

Clément Pit-Claudel is an Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), leading the SYSTEMF lab focused on programming languages, formal methods, and systems engineering. His work bridges mathematical formalisms with practical system development to achieve full assurance in critical software and hardware. PhD in Computer Science from MIT (2016) William A. Martin Memorial Thesis Award recipient Former Senior Applied Scientist at Amazon AWS Teaching accolades including the Frederick C. Hennie III Teaching Award Research spans three axes: extensible proof-producing compilers for performance-critical systems, verified hardware compilation with cycle-accurate semantics, and interactive theorem prover tooling for democratizing verification technology. Key projects include Kôika for hardware verification, Alectryon for Coq proof visualization, and Fiat for correct-by-construction program synthesis. Recent publications address JavaScript regex verification (ICFP 2024), cryptographic server integration (PLDI 2024), and hardware simulation optimization (ASPLOS 2021). Articles demonstrate expertise in functional-to-imperative translation, domain-specific compiler extensions, and hardware-software co-verification. Scientific contributions recognized through: Distinguished artifact award (SLE 2020) MIT William A. Martin Thesis Award Frederick C. Hennie III Teaching Award Teaching philosophy emphasizes hands-on lab instruction , oral assessment , and automated tooling . Courses taught include Software Construction (undergraduate) and Interactive Theorem Proving (graduate) at EPFL. Research service includes program committee roles at Dafny, POPL, and SPLASH conferences.

Vijay GaneshView profile

Professor

• SAT/SMT Solvers
• Artificial Intelligence
• Formal Methods
• +5 more

Dr. Vijay Ganesh is a Professor of Computer Science at Georgia Institute of Technology, where he also serves as Associate Director of the IDEaS Institute and is affiliated with Tech AI. Previously, he held roles as Associate Professor (2018–2023) and Assistant Professor (2012–2018) at the University of Waterloo, and Research Scientist at MIT (2007–2012). He earned his PhD from Stanford University in 2007. His research focuses on SAT/SMT solvers and their applications in AI, software engineering, security, mathematics, and physics. Notable contributions include developing solvers like MapleSAT, Z3str4, and AlphaZ3, and exploring machine learning-augmented reasoning. He has led projects in logic for AI, proof complexity, and security of blockchain technologies. His awards include ACM Impact Paper (2019), ACM Test of Time (2016), and DATE’s Ten-Year Most Influential Paper (2008). He has advised startups like Quantstamp, a blockchain security firm, and co-directed the Waterloo AI Institute (2021–2023). His teaching includes courses on discrete mathematics, software engineering, and AI. Education: PhD in Computer Science, Stanford University (2007); Master’s in Electrical Engineering, Stanford (2000) Research Interests: SAT/SMT solvers, formal methods, automated testing, AI security, combinatorial mathematics Affiliations: Georgia Tech’s School of Computer Science, IDEaS Institute

Mustafa AminView profile

Associate Professor

• Cosmology
• Particle Physics
• Astrophysics
• +4 more

Mustafa Amin is an Associate Professor in the Department of Physics and Astronomy at Rice University. His research focuses on understanding the origin of cosmic structure and matter, particularly through nonlinear dynamics of cosmological fields, dark matter (axions/vector dark matter), solitons, and early universe phenomena. He holds a PhD from Stanford University (2008) and a BS from the University of Texas at Arlington (2003). Amin has held prestigious fellowships including the Senior Kavli Fellowship at Cambridge and the Pappalardo Fellowship at MIT. Education: BS Physics/Mathematics (UT Arlington, 2003), PhD Physics (Stanford, 2008) Teaching: Cosmology, Quantum Field Theory, General Relativity His research explores topics like dark matter spin probes, Hubble tension, gravitational waves, and exoplanet dynamics. Recent work includes studies on vector wave dark matter, axion string networks, and soliton interactions. Amin has delivered invited talks globally, including at CERN, Perimeter Institute, and MIT. Awards: Rice Teaching Award (2019), Kavli Frontiers Fellow (2016) Labs/Groups: Co-leads the Relativistic Astroparticle Physics & Cosmology Group at Rice

Jørgen Ellegaard AndersenView profile

Professor

• Quantum Topology
• Geometric Quantization of Moduli Spaces
• Topological Quantum Field Theory
• +7 more

Jørgen Ellegaard Andersen is a Professor and Center Director at the Department of Mathematics and Computer Science, University of Southern Denmark (SDU), and holds the D-IAS Chair at the Danish Institute for Advanced Study (DIAS). He is also a Distinguished Visiting Professor at the California Institute of Technology since 2013, reflecting his international stature in mathematical sciences. University: University of Southern Denmark School: Faculty of Science Department: Department of Mathematics and Computer Science Position: Professor, Center Director, D-IAS Chair Andersen earned his DPhil in Mathematics from the University of Oxford in 1992, with a thesis on Jones-Witten theory and the Thurston Compactification of Teichmüller space. His research lies at the intersection of quantum theory and geometry, focusing on quantum topology, geometric quantization of moduli spaces, topological quantum field theory, low-dimensional geometry, and applications to RNA and protein folding. His work combines deep mathematical rigor with potential applications in quantum computing and biophysics. The trends in his recent publications show a consistent focus on quantization of moduli spaces, topological recursion, mapping class group representations, and quantum Chern-Simons theory. His work often bridges pure mathematics and theoretical physics, with increasing attention to computational and applied aspects in quantum technologies. ERC Synergy Grant ReNewQuantum (EUR 10m, Principal Investigator) Distinguished Visiting Professor, Caltech Andersen leads major research projects such as ReNewQuantum and TopQC2X, securing significant funding from the EU and Danish agencies. He actively supervises PhD students and collaborates with leading mathematicians worldwide, including Maxim Kontsevich and Bertrand Eynard. His work is frequently highlighted in the media for its potential impact on quantum computing and Danish industry. He is a central figure in the Quantum Mathematics center at SDU and collaborates with institutions like MSRI and the University of Hamburg. His research group is part of international networks focused on geometric and topological methods in quantum theory.

Ken OlumView profile

Research Professor

• Gravitational Waves
• Cosmic Strings
• Energy Conditions in General Relativity
• +2 more

Roles and Affiliations: Ken Olum is a Research Professor in the Tufts Institute of Cosmology at Tufts University, Department of Physics & Astronomy. He is a core member of the NANOGrav collaboration, focusing on gravitational wave detection via pulsar timing arrays and cosmic string dynamics. PhD from MIT (1997), Center for Theoretical Physics, specializing in black hole information radiation. Research Interests: Olum's work centers on gravitational waves from cosmic strings, energy conditions in general relativity, and anthropic reasoning in cosmology. He develops large-scale simulations of cosmic string networks and their gravitational wave emission, contributing to NANOGrav's efforts to detect nanohertz gravitational waves. Publications: His recent work includes advancements in gravitational wave background analysis, cosmic string simulations, and pulsar timing array methodologies. Key contributions address gravitational wave detection techniques, energy condition constraints, and cosmic string dynamics. Collaborations: Active in NANOGrav, focusing on pulsar timing array analyses and cosmic string gravitational wave signatures. His research bridges theoretical cosmology with observational astrophysics.

Bin HuView profile

Assistant Professor

• Resilient Cyber-Physical Systems (CPS)
• AI-Human Collaboration Safety & Security
• Big Data & Machine Learning-Based Control
• +5 more

Dr. Bin Hu is an Assistant Professor in the Department of Engineering Technology at the University of Houston (2022–present) and previously held the same position at Old Dominion University (2019–2022). He earned a Ph.D. in Electrical Engineering from the University of Notre Dame (2016), an M.S. in Control Science from Zhejiang University (2010), and a B.S. in Electrical Engineering from Hefei University of Technology (2007). His research focuses on resilient Cyber-Physical Systems (CPS), AI-human collaboration safety, machine learning-driven control, and vehicular networks. Key projects include NASA-funded work on adaptive human-autonomy responsibility allocation (2023–2026) and NSF-supported AI-human collaboration in autonomous vehicles (2020–2023). He has secured over $1.2 million in grants, including a $700k NASA grant (pending) and an ONR Rapid Solutions grant ($42k). Dr. Hu’s work bridges control theory, machine learning, and human factors. Recent contributions include safer leader-follower robotic systems, fault-tolerant UAV control, and studies on driver trust in AI-driven vehicles. His research has been recognized through awards like the 2024–2025 APeX Excellence Speaker Series. Teaching experience includes courses on C++ programming and electrical engineering fundamentals at both the University of Houston and Old Dominion University. He advises multiple undergraduate and graduate students in projects ranging from LiDAR systems to cyber-physical security. Key Labs/Teams : NAIL Lab (Networked Autonomous Intelligence & Learning), part of the University of Houston’s Cybersecurity and Robotics initiatives. Grants : NASA TTT Grant ($700k), NSF CHS Grant ($500k), ONR RSLP Project ($42k).

• Modified Gravity Theories
• Dark Energy and Cosmology
• Black Hole Physics
• +7 more

Ertan Güdekli is a researcher at Istanbul University, focusing on theoretical physics and astrophysics. His work spans modified gravity theories, dark energy models, black hole thermodynamics, and cosmological frameworks. He frequently collaborates on interdisciplinary studies involving particle dynamics, quantum corrections, and observational constraints. Research Focus: Modified gravity (f(R,T), Rastall, Horndeski), dark energy, black hole physics, wormhole solutions, and cosmological models. Methodology: Utilizes quasi-periodic oscillations (QPOs), trajectory analysis, and thermodynamic principles to test gravitational theories. Recent Contributions: Investigates anisotropic stellar models, tidal effects in rotating black holes, and holographic inflation scenarios. Collaborations: Active in international research networks, co-authoring studies with physicists from Turkey, Pakistan, India, and Germany. Academic Output: Over 148 publications (WoS), 76 citations (WoS), and 13 thesis advisories. His work appears in high-impact journals like Annals of Physics , Physics of the Dark Universe , and Nuclear Physics B . He also contributes to educational literature, editing a Temel Fizik textbook series.

• Theoretical Particle Physics
• Cosmology
• Astroparticle Physics
• +1 more

Dr. Debtosh Chowdhury is an Assistant Professor in the Department of Physics at the Indian Institute of Technology Kanpur, where he has been serving since January 2020. His research focuses on theoretical particle physics, cosmology, and astroparticle physics, with particular expertise in Standard Model phenomenology. Dr. Chowdhury received his educational qualifications as follows: PhD from Indian Institute of Science, Bangalore, India (2013) MS from Indian Institute of Science, Bangalore, India (2009) B.Sc. from Scottish Church College, University of Calcutta, Kolkata, India (2007) Dr. Chowdhury's research spans theoretical particle physics with a focus on beyond Standard Model physics, dark matter phenomenology, and connections to cosmology. His work bridges high-energy theory with potential experimental signatures at colliders like the LHC. He has made significant contributions to understanding constraints on supersymmetric models, dark matter candidates, and the theoretical consistency of particle physics models in light of quantum gravity considerations. His research often involves precision calculations at multiple loop levels to provide testable predictions for current and future experiments. Dr. Chowdhury has received several prestigious fellowships including a post-doctoral fellowship from CEFIPRA (France), a post-doctoral fellowship from INFN (Italy), and a Junior Research Fellowship from CSIR, Government of India. These awards reflect the international recognition of his research contributions in theoretical particle physics. As a member of the High Energy Physics research group at IIT Kanpur, Dr. Chowdhury contributes to the vibrant theoretical physics community at the institute, collaborating with researchers both nationally and internationally. His work continues to address fundamental questions at the intersection of particle physics, cosmology, and theoretical physics.

Jeffrey HeinzView profile

Professor

• Phonology
• Linguistic typology
• Grammatical inference
• +5 more

Jeffrey Heinz is a Professor at Stony Brook University , holding a joint appointment in the Department of Linguistics and the Institute for Advanced Computational Science . He has been at Stony Brook since 2017, following a decade at the University of Delaware. His research focuses on computational linguistics, formal language theory, grammatical inference, and phonology, with applications to robotics and artificial intelligence. He earned his Ph.D. in Linguistics from UCLA in 2007. Heinz’s work bridges theoretical linguistics and computational methods, emphasizing the learnability of linguistic patterns through formal models. He has contributed to understanding phonological typology, reduplication, and the mathematical foundations of language learning. His research has been published in Science , Phonology , and Machine Learning , among others. He was honored with the 2017 Early Career Award from the Linguistic Society of America for his contributions to computational learning theory in linguistics. He teaches advanced courses in computational phonology and linguistics, including a course at the LSA Summer Institute. He actively organizes academic sessions and serves on steering committees for conferences like ICGI. His interdisciplinary approach integrates linguistics with computer science, robotics, and mathematical logic. Award highlights include: 2017 Early Career Award (Linguistic Society of America) He advises students in linguistics and computational fields, though specific names are not listed here. His research labs and collaborations involve computational linguistics and robotics projects, such as stress pattern databases and grammatical inference benchmarks.

William HeathView profile

Professor

• Feedback Control Theory
• Nonlinear Control Systems
• Actuator Nonlinearities
• +4 more

William Heath is a Professor and Head of the School of Computer Science and Engineering at Bangor University. He holds the position of Chair of the UKACC from 2024 to 2027. His research focuses on feedback control theory, particularly addressing actuator nonlinearities such as saturation, rate constraints, backlash, and hysteresis. He employs multiplier theory within absolute stability frameworks to analyze model predictive control and antiwindup strategies. His research interests include nonlinear control systems design, stability criteria for Lur’e systems, and discrete-time extensions of classical control methodologies. He has contributed to foundational work on O’Shea-Zames-Falb multipliers and their applications in robust control. Key collaborations involve international researchers in control systems and applications, though specific partnerships are not detailed. His work bridges theoretical advancements with practical implementations, such as in biomedical BCIs and industrial systems like wind turbines and diesel engines. No awards or grants are explicitly listed, but his extensive publication record (105+ outputs) reflects sustained academic engagement. As Head of School, he leads a team advancing interdisciplinary research in computer science and engineering.