Quantum causality Professors and Supervisors | ApplySharif

Find Academic Supervisors

Find and connect with academic supervisors, professors, and scholars for your research journey.

Showing 1-15 of 516 supervisors

Profile data may be stale. It is sourced from public faculty pages.

Tommi JaakkolaView profile

Professor

Massachusetts Institute of TechnologyUnited States

Tommi Jaakkola is the Thomas Siebel Professor of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society at the Massachusetts Institute of Technology. He received his MSc in theoretical physics from Helsinki University of Technology in 1992 and his PhD from MIT in computational neuroscience in 1997. After completing a postdoctoral position in computational molecular biology as a DOE/Sloan fellow at UCSC, he joined the MIT EECS faculty in 1998. His research advances how machines can learn, predict or control, and do so at scale in an efficient, principled, and interpretable manner. His work in machine learning extends from foundational theory to modern applications, focusing especially on statistical inference and estimation tasks that lie at the heart of complex learning problems. He designs new methods, theory and algorithms to automate the use and generation of semi-structured data such as natural language text, images, molecules, or strategies. Jaakkola applies and develops algorithms to solve multi-faceted recommender, retrieval, or inferential tasks (particularly in biomedical contexts), design and optimize molecules or reactions for drug design, and model strategic, game theoretic interactions. His recent work heavily focuses on diffusion models, protein structure prediction, molecular design, and generative AI, with significant publications in top conferences including ICML, NeurIPS, and ICLR. His scientific contributions span multiple disciplines with significant impact in both theoretical machine learning and practical applications in computational biology and chemistry, including notable work on antibiotic discovery published in Cell. Current advisees: Julia Balla, Bowen Jing, Hannes Stärk, Peter Holderrieth, Chenyu Wang Recent graduates: Gabriele Corso (Boltz PBC), Ezra Erives (DE Shaw), Jason Yim (Xaira) Jaakkola maintains an active research program through MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Institute for Data, Systems, and Society (IDSS), with his office located in the Stata Center (32-G470). His work bridges theoretical machine learning with practical applications, making significant contributions to both the academic field and potential real-world impact in healthcare and drug discovery.

Official University Profile

Harvey ReallView profile

Professor

University of CambridgeUnited Kingdom

Harvey Reall is a Professor of Theoretical Physics at the University of Cambridge , affiliated with the Department of Applied Mathematics and Theoretical Physics (DAMTP) and a Fellow of Trinity College . His research focuses on General Relativity and Effective Field Theory , particularly in the context of black hole mechanics , higher-dimensional gravity , and cosmic censorship . He has held prestigious positions including a Royal Society University Research Fellowship from 2005 to 2013. Education: PhD from DAMTP, University of Cambridge. Previous Appointments: Lecturer at the University of Nottingham (2005-2007); Postdoctoral positions at the Kavli Institute (2003-2005), Queen Mary University of London (2000-2003), and University of California, Santa Barbara (2003-2005). Reall's work explores the uniqueness and stability of black holes , causality in gravitational theories , and effective field theory approaches to gravity . His recent publications address nonperturbative second law formulations , event horizon dynamics , and axisymmetry theorems in extended theories of gravity. He has supervised numerous researchers including Aidan McSharry (2025-) , Maxime Gadioux (2022-) , and Iain Davies (2020-24) , contributing to the training of the next generation of physicists. Scientific Awards: Royal Society University Research Fellow (2005-2013)

Official University Profile

Martin T. WellsView profile

Professor

Cornell UniversityUnited States

Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.

Official University Profile

Zhenman FangView profile

Associate Professor

Simon Fraser UniversityCanada

Dr. Zhenman Fang is an Associate Professor at the School of Engineering Science , Simon Fraser University (SFU) , where he founded and directs the HiAccel Lab . He also holds an associate membership in the School of Computing Science at SFU. His research focuses on customizable computing with software-defined hardware acceleration , addressing performance, energy-efficiency, and reliability in post-Moore’s law computing across domains like machine learning , big data analytics , quantum chemistry , and precision medicine . Education: Ph.D. in Computer Science from Fudan University (2014), with a visit to University of Minnesota during his studies. Postdoctoral Work: University of California, Los Angeles (UCLA) (2014-2017). Industry Experience: Staff Software Engineer at Xilinx (2017-2019). Dr. Fang’s research spans the entire computing stack , including application characterization , accelerator-rich architecture design , and programming/tool support . He has developed frameworks like HiSpMV , SyncNN , and SQL2FPGA , emphasizing FPGA acceleration for vision transformers , quantum chemistry , and spiking neural networks . His work has been recognized with 3 best paper awards (FPL 2024, TCAD 2019, MEMSYS 2017) and 3 best paper nominees (FCCM 2025, HPCA 2017, ISPASS 2018). Recent publications highlight trends in low-precision machine learning ( ShiftQuant , ESRU ), quantum chemistry acceleration ( SERI ), and vision transformer optimization ( Quasar-ViT ). His HiAccel Lab actively mentors PhD and MASc students , with notable graduates like Alec Lu (PhD 2024, now at Meta) and Philip Stachura (MASc, now with BC Graduate Scholarship). Scientific Awards: Inaugural SFU Research Excellence Award - Horizon Award (2025) FPL 2024 Stamatis Vassiliadis Best Paper NSERC Alliance Award (2020) CFI JELF Award (2019) Xilinx University Program Award (2019) IEEE Senior Member (2023) Grants: NSERC Discovery Grant (2019) CFI JELF Funding (2019) Huawei and Xilinx sponsorships Dr. Fang leads open-source initiatives like SyncNN , PASTA , and SQL2FPGA , and serves as General Chair for ASAP 2025 and Program Co-Chair for RAW 2025 . His lab collaborates globally with institutions such as UCLA , Northeastern University , and Xidian University .

Official University Profile

Kyle Bellucci JohansonView profile

Visiting Assistant Professor

Cornell UniversityUnited States

Kyle Bellucci Johanson serves as a Visiting Critic in Cornell University's College of Architecture, Art, and Planning, Department of Art. Holding an MFA from California Institute of the Arts and a BA in Art and Reconciliation Studies from Bethel University, he merges artistic practice with critical theory through performance architecture and collaborative media. Whitney Independent Study Program (2022–23) Founding fellow at land's edge free school (Los Angeles) Teaching experience at SAIC, UIC, CUNY, and Cooper Union His research investigates: Power structures through spatial interventions Critical theory applications in art practice Post-capitalist imaginaries Hauntology and historical materialism Transdisciplinary approaches to social critique Project trends reveal: Reinterpretation of Soviet design principles Investigation of worker identity in post-industrial contexts Temporal and spatial dislocation in artistic practice Monument critique through performative methods Quantum theory-inspired architectural concepts Reimagining of common spaces as political sites Scientific awards include: Creative Research Grant (2025) Whitney ISP participation (2022–23) Automata Studio Residency (2022) Artists Run Chicago Grant (2021) BOLT Residency (2020–21) Through projects like KLUB WRKR —a nomadic workers' club reimagined for the gig economy—and table (2018–2022), a Chicago-based experimental space for artistic practice, he interrogates institutional frameworks while fostering community through discursive meals and collaborative exhibitions.

Official University Profile

Yan LiuView profile

Professor

Brown UniversityUnited States

Yan Liu is a full professor in the Thomas Lord Department of Computer Science at the University of Southern California (USC), serving as Director of the USC Machine Learning Center within the Viterbi School of Engineering. He holds courtesy appointments in the Ming Hsieh Department of Electrical Engineering and the Quantitative and Computational Biology Department. Before joining USC in 2010, he was a research staff member at IBM's T.J. Watson Research Center. He earned his M.S. and Ph.D. from Carnegie Mellon University. His research focuses on machine learning for time series, physics-informed AI, and interpretable models, with applications in healthcare, sustainability, and social media. Notable projects include developing AI for surgical training, analyzing misinformation on social platforms, and predicting cancer treatment outcomes. He has held leadership roles in top conferences like ICLR and ACM KDD, and serves as Associate Editor-in-Chief of TPAMI and Board Member of ICLR. Education: Ph.D., Carnegie Mellon University Affiliations: USC Machine Learning Center, Viterbi School of Engineering Service: General Chair (ICLR 2023, ACM KDD 2020), Program Chair roles across multiple conferences His lab, the Melady Group, emphasizes foundational ML advancements and interdisciplinary applications. Recent work includes physics-aware neural networks and time-series foundation models.

Official University Profile

Fay DowkerView profile

Professor

Imperial College LondonUnited Kingdom

Professor Fay Dowker is a leading theoretical physicist at Imperial College London's Department of Physics, affiliated with the Faculty of Natural Sciences. Her research focuses on quantum gravity, causal set theory, and the nature of spacetime. She explores the granular structure of spacetime at Planck scales, emphasizing causal relationships and the interplay between relativity and quantum mechanics. Dowker's work addresses foundational questions such as the cosmological constant problem, the passage of time, and the relationship between spacetime discreteness and consciousness. Her contributions include seminal lectures like A Meditation on General Relativity and Spacetime Atoms and the Unity of Physics , as well as public debates on parallel universes and the hard problem of consciousness. She has held roles such as organizing events for Einstein's general relativity centenary and contributes to outreach via BBC Radio 4 and the Royal Institution. Her Orcid identifier is 0000-0002-6652-1058, and she is part of interdisciplinary teams like Physics of Universe and Quantum Engineering, Science, and Technology. Dowker’s research bridges physics and philosophy, tackling dichotomies such as continuity vs. atomicity, locality vs. non-locality, and objectivity vs. subjectivity. Her work on causal set theory challenges traditional views of spacetime and offers novel insights into quantum gravity and cosmology.

Official University Profile

Daniel A. SpielmanView profile

Professor

Yale UniversityUnited States

Daniel A. Spielman is a Sterling Professor of Computer Science, Statistics & Data Science, and Mathematics at Yale University. He serves as the inaugural James A. Attwood Director of the Institute for Foundations of Data Science (FDS) and was previously co-Director of the Yale Institute for Network Science (YINS). He is also a member of TILOS, the NSF Institute for Learning-Enabled Optimization at Scale. His research interests span Spectral Graph Theory, Algebraic Graph Theory, Laplacian Matrices, Expander Graphs, and Random Walks on Graphs. Spielman has made fundamental contributions to understanding the mathematical foundations of data science, including work on smoothed analysis of algorithms, spectral sparsification, and solutions to the Kadison-Singer problem. Spielman's publications demonstrate a consistent focus on developing efficient algorithms with strong theoretical foundations. His work bridges pure mathematics, theoretical computer science, and practical applications in network analysis and machine learning. His research has evolved from foundational work on smoothed analysis to recent contributions in experimental design using discrepancy theory. His scientific honors include: Nevanlinna Prize for contributions to mathematical aspects of computer science Two Gödel Prizes (2008 and 2015) for outstanding papers in theoretical computer science MacArthur Fellowship ('Genius Grant') Simons Investigator award Membership in the National Academy of Sciences and American Academy of Arts and Sciences Spielman has advised numerous PhD students who have gone on to prominent positions in academia and industry. His teaching includes advanced courses in Spectral Graph Theory and Computation and Optimization. He has developed important software packages like Laplacians.jl for solving Laplacian linear equations and related problems.

Official University Profile

Steven HoekstraView profile

Associate Professor

University of GroningenNetherlands

Prof. dr. Steven Hoekstra is an Associate Professor of Atomic and Molecular Physics at the University of Groningen's Faculty of Science and Engineering, within the Van Swinderen Institute. His research focuses on precision measurements using cold molecules to explore fundamental physics, including Stark deceleration, laser cooling, and searches for physics beyond the Standard Model. He leads the NL-eEDM program at Nikhef, investigating the electron's electric dipole moment. Hoekstra is also involved in educational innovation, having received the Teacher of the Year award (2020) and a Senior Teacher Qualification (2023). He has supervised over 11 PhD theses and currently mentors 5 students. His work combines experimental techniques with theoretical insights, addressing questions like symmetry violations and quantum dynamics. Key projects include manipulating BaF molecules with electrostatic fields and exploring levitated nanoparticles as sensors. Hoekstra has secured major grants, including NWO VICI (2022) and VIDI (2013), and collaborates internationally on projects like the European Strategy for particle physics. Recent articles highlight advancements in molecular beam control, spin-precession methods for EDM searches, and opportunities in radioactive molecules. He actively participates in the Physics Olympiad Netherlands as chair, contributing to science outreach and education.

Official University Profile

Wayne LukView profile

Professor

Imperial College LondonUnited Kingdom

Professor Wayne Luk is a Professor of Computer Engineering at the Department of Computing, Faculty of Engineering, Imperial College London. He leads the Programming Languages and Systems Section and the Custom Computing Research Group, and directs the EPSRC Centre for Doctoral Training in High-performance Embedded and Distributed Systems and the Centre for Advanced Financial Engineering. He previously served as a Visiting Professor at Stanford University from 2006 to 2009. His research spans FPGA acceleration, quantum computing, deep learning optimization, and algorithm-hardware co-design, with affiliations to the CRUK Convergence Science Centre and the Engineering Secure Software Systems group. His research interests include computational modeling for particle physics, causal discovery in agent-based systems, and high-throughput digital electronics. Notable contributions include FPGA-accelerated algorithms for neural networks, quantum circuit simulation, and Bayesian optimization frameworks. His work emphasizes practical applications of reconfigurable hardware in fields like medical imaging, high-energy physics, and financial systems. Professor Luk is a Fellow of the Royal Academy of Engineering, IEEE, and BCS. His publications focus on advancing hardware-aware machine learning, FPGA-based acceleration techniques, and scalable design methodologies. His research bridges theoretical computer science with applied engineering, addressing challenges in real-time systems, embedded computing, and next-generation computing architectures. His academic leadership includes directing interdisciplinary centers and training programs, fostering collaboration across computing, engineering, and physics. Current projects explore quantum computing tools, causal inference systems, and high-performance graph neural networks for particle physics applications.

Official University Profile

Carlo RovelliView profile

Professor

Western UniversityCanada

Carlo Rovelli is a Professeur de classe exceptionnelle in the Department of Physics at Aix-Marseille University, holding adjunct roles at Western University's Department of Philosophy and a Distinguished Visiting Research Chair at the Perimeter Institute. He founded the quantum gravity group at the Centre de Physique Théorique (CPT) and is an associate member of the Rotman Institute of Philosophy. His research focuses on loop quantum gravity, relational quantum mechanics, and the history/philosophy of science. He authored influential popular science books including Seven Brief Lessons on Physics (41 languages, 1M+ copies sold) and Helgoland: Making Sense of the Quantum Revolution . Rovelli's work bridges theoretical physics with philosophical inquiry, exploring foundational questions in quantum mechanics, spacetime structure, and the interpretation of physical theories. His recent publications address topics like quantum information theory, gauge symmetries, black hole evaporation, and cosmological implications of quantum gravity.

Official University Profile

Rui Soares BarbosaView profile

Researcher

International Iberian Nanotechnology LaboratoryPortugal

Rui Soares Barbosa is a Staff Researcher at the Quantum and Linear-Optical Computation group at the International Iberian Nanotechnology Laboratory (INL). He holds a BSc in Computer Science from Universidade do Minho (2009), an MSc in Mathematics and Foundations of Computer Science from the University of Oxford (2010), and a DPhil in Computer Science from Oxford (2015) with a thesis on Contextuality in quantum mechanics and beyond. Prior to joining INL, he held post-doctoral positions at Oxford (2015–2019) and the University of Edinburgh (2019–2020), and a Research Fellowship at the Simons Institute for the Theory of Computing, UC Berkeley (2017). Barbosa's research lies at the intersection of Computer Science, Physics, and Mathematics, focusing on quantum foundations, quantum computer science, and the mathematics of quantum theory. His work emphasizes logical, structural, and compositional aspects, particularly investigating non-locality and contextuality - phenomena that distinguish quantum theory from classical physics and have been linked to quantum informatic advantage. He employs mathematical tools from category theory, logic, probability, algebraic topology, and operator algebras to achieve a structural understanding of quantum systems' non-classical features. His recent publications demonstrate a strong focus on contextuality as a quantum resource, exploring its connections to causality, computational advantage, and logical structures. The research spans theoretical foundations to practical quantum computing applications, with particular attention to mathematical frameworks like sheaf theory that elegantly express quantum contextuality. His work often involves collaborations with leading researchers in quantum foundations and theoretical computer science. Barbosa actively advises multiple PhD and MSc students including Angelos Bampounis, Rafael Wagner, Nico Witrock, and others. His research group at INL, the Quantum and Linear-Optical Computation group, conducts cutting-edge research at the intersection of quantum theory and computer science, regularly presenting findings at major conferences like the International Conference on Quantum Physics and Logic (QPL).

Official University Profile

Bilal FarooqView profile

Associate Professor

Toronto Metropolitan UniversityCanada

Bilal Farooq is an Associate Professor and Program Director for the Master of Engineering in Interdisciplinary Engineering (MEIE) at Toronto Metropolitan University, holding the Canada Research Chair in Disruptive Transportation Technologies and Services within the Department of Civil Engineering. His educational background includes a PhD from the University of Toronto (2011), MASc from Lahore University of Management Sciences (2004), and BSc from the University of Engineering and Technology (2001). Dr. Farooq's research pioneers disruptive transportation solutions through cyber-physical systems, AI/machine learning applications, behavioral modeling, and optimization techniques. His work specifically targets on-demand multimodal systems, sustainable urban transportation, urban air mobility, automated vehicles, and extended reality applications, addressing critical urban mobility challenges with human-centered approaches. Analysis of his recent publications reveals a strong trend toward quantum-enhanced computational methods, privacy-preserving federated learning frameworks, and sustainability-focused decarbonization strategies across transportation domains, with increasing emphasis on human factors and real-world implementation. Notable scientific awards include: Ontario Early Researcher Award (2018) Canada Research Chair (2017) MassMotion Academic Pedestrian Modelling Project of the Year (2016) Québec Early Researcher Award (2014) Dr. Farooq actively supervises graduate students and secures significant research funding through his Canada Research Chair position and Early Researcher Awards. He directs the Laboratory of Innovations in Transportation (LiTrans), which develops interdisciplinary solutions integrating mathematics, engineering, computer science, and economics to address emerging transportation challenges. LiTrans focuses on disruptive transportation technologies, complete streets design, cyber-physical systems, pedestrian dynamics, resilience, and climate change impacts, collaborating with industry and government partners to translate research into practical urban mobility innovations for smart cities worldwide.

Official University Profile

Valter MorettiView profile

Professor

University of TrentoItaly

Valter Moretti is a Full Professor in the Department of Mathematics at the University of Trento. His academic career spans roles from Research Fellow to Full Professor, focusing on Mathematical Physics and Quantum Field Theory (QFT) in curved spacetime. He earned an MSc in Physics from Genova University and a PhD in Theoretical Physics from Trento University. Research Interests : Algebraic QFT, General Relativity, Quantum Mechanics, Operator Algebras, and Spectral Theory. His work bridges mathematical rigor with physical applications, particularly in quantum localization, entanglement, and curved spacetime phenomena. Publications : Authored 15+ recent papers on topics like quantum particle localization, entanglement certification, and QFT on curved backgrounds. Collaborated on a 2022 patent for generating entangled photon states. Awards : Holds a patent for a quantum-certified random number generator (2022). Supervision : Advised 8 PhD students, including N. Pinamonti, L. Franceschini, and C. van de Ven. Coordinated national and international research projects (e.g., H2020-MSCA-COFUND-2015). Labs & Collaborations : Affiliated with INFN, TIFPA-INFN, and Q@TN (Quantum@Trento). Organized conferences like Quantum Physics and Geometry (2014) and Quantum Machine Learning (2023). Teaching : Lectures on Analytical Mechanics, Quantum Relativistic Theories, and Special Relativity. Authored textbooks on Spectral Theory and Quantum Mechanics.

Official University Profile

Sean CarrollView profile

Professor

University of Texas at DallasUnited States

Sean Carroll serves as the Homewood Professor of Natural Philosophy at Johns Hopkins University and holds External Faculty status at the Santa Fe Institute. His research bridges cosmology, quantum mechanics, and philosophy, focusing on foundational questions about spacetime emergence, quantum interpretation, and complexity across cosmic scales. Carroll earned his Ph.D. from Harvard University in 1993. His academic trajectory reflects deep engagement with theoretical physics and philosophical inquiry, culminating in his current named professorship at Johns Hopkins. Carroll's research centers on the intersection of physics and philosophy, with significant contributions to quantum foundations, cosmology, and the nature of emergence. He is a leading proponent of the many-worlds interpretation of quantum mechanics and has pioneered work on the thermodynamic arrow of time, quantum decoherence, and the fine-tuning of initial cosmic conditions. His recent investigations explore discretized quantum systems, holographic principles in gravity, and the philosophical implications of quantum gravity. Analysis of his 2022-2025 publications reveals a pronounced shift toward computational approaches in quantum gravity, with increasing emphasis on finite-dimensional Hilbert spaces and GPU-accelerated modeling. His work consistently integrates quantum information theory with cosmological questions, particularly examining how spacetime geometry emerges from quantum entanglement and how complexity evolves in closed systems. Carroll's scientific recognition includes: National Science Foundation Fellowship NASA Fellowship Sloan Research Fellowship Packard Fellowship Fellow of the American Physical Society American Institute of Physics Award Fellow of the Royal Society Guggenheim Fellowship Fellow of the American Association for the Advancement of Science His research has been sustained through major fellowships from NSF, NASA, Sloan, and Packard foundations, enabling interdisciplinary collaborations across physics and philosophy. Carroll actively mentors graduate students at Johns Hopkins and contributes to public discourse through his popular science books (including the Biggest Ideas in the Universe series) and the weekly Mindscape podcast. As Fractal Faculty at the Santa Fe Institute, Carroll participates in cross-disciplinary research on complex systems, exploring how emergent phenomena arise from fundamental physical laws. His work bridges theoretical physics with broader questions about complexity in biological, cognitive, and social systems.

Official University Profile