Find Academic Supervisors

Julia CramerView profile

Assistant Professor

• Quantum Science
• Quantum Technology
• Science Communication
• +7 more

Julia Cramer is an Assistant Professor in the Department of Science Communication and Society at the Institute of Biology Leiden (IBL), Leiden University, with a joint affiliation at the Leiden Institute of Physics (LION). Her research focuses on the intersection of quantum science and technology with society, particularly through the lens of science communication, public engagement, and societal readiness. She leads the Quantum and Society research group and is actively involved in national and European initiatives on the Ethical, Legal, and Societal Aspects (ELSA) of quantum technology. PhD in Applied Physics, Delft University of Technology Member of the Dutch Physics Association (NNV) Co-founder of Women in Quantum Development (WIQD) Chair of the Young Academy Leiden (from 2023) Former member of the CBS communicatie-adviesraad Member of the Physics Scientific Advisory Board of the Lorentz Center Julia Cramer's research interests lie at the intersection of quantum technology and society. She investigates how quantum science is communicated to the public, how societal groups perceive quantum technologies, and how to foster inclusive and responsible innovation. Her work emphasizes broadening youth participation in STEM and enhancing diversity in quantum fields. She is passionate about making quantum accessible to non-expert audiences and ensuring that technological development aligns with societal values. Her recent publications reflect a strong trend in science communication, public perception, and societal integration of quantum technologies. Themes include measuring public attitudes, designing effective outreach interventions, promoting diversity, and addressing ethical implications. The research combines qualitative and quantitative methods to assess communication strategies and societal impacts. Casimir Prize (during PhD) Recognized as one of the Faces of Science by KNAW Julia Cramer supervises several PhD candidates and is involved in mentoring early-career researchers. She has led initiatives such as the Women in Quantum Development (WIQD) and contributes to national science policy through advisory roles. Her research is supported by collaborations with Quantum Delta NL and other European networks focused on responsible quantum innovation. She leads the Quantum and Society research group, which focuses on content analysis of quantum communication, developing attitude measurement tools, and evaluating the impact of public engagement interventions. The group collaborates with physicists, social scientists, educators, and policymakers to ensure a multidisciplinary approach to quantum-society integration.

• Cryptography
• Post-Quantum Cryptography
• Network Security
• +3 more

Douglas Stebila is an Associate Professor in the Department of Combinatorics and Optimization at the University of Waterloo, Faculty of Mathematics. His research focuses on cryptographic protocols, with an emphasis on post-quantum cryptography, TLS protocol security, and key exchange mechanisms. He has contributed to the design and analysis of cryptographic systems resilient to quantum computing threats, including work on hybrid key exchange methods and post-quantum TLS implementations. Stebila is involved in standards projects such as the Open Quantum Safe initiative, aiming to transition existing infrastructure to quantum-resistant algorithms. His recent work addresses security models for cryptographic protocols, including formal verification of key establishment schemes and analysis of real-world protocols like Signal and TLS. His research spans theoretical cryptography, applied protocol analysis, and implementation security. Key contributions include studies on obfuscated key exchange, verifiable decapsulation of post-quantum KEMs, and optimization of TLS handshake efficiency (e.g., TurboTLS). He also explores challenges in cryptographic protocol design, such as preventing double authentication and ensuring resistance against side-channel attacks. His work frequently bridges academic research with practical applications, emphasizing the transition of cryptographic innovations into real-world systems. Stebila collaborates with industry and academic partners on projects like the Open Quantum Safe initiative, which develops libraries for post-quantum cryptography integration. His publications often address security analyses of emerging protocols and their vulnerability to both classical and quantum adversaries. He has co-authored conference proceedings for major venues like CRYPTO and SAC, and contributed to standards documentation for protocols such as TLS and SSH.

Pierre F BaldiView profile

Professor

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +10 more

Pierre Baldi is a Distinguished Professor at the University of California, Irvine (UCI), holding appointments in the School of Information and Computer Sciences (ICS), the Institute for Genomics and Bioinformatics (IGB), and the Center for Machine Learning and Intelligent Systems (CML). His research focuses on AI, machine learning, and their applications in natural sciences, including physics, chemistry, and biology. He leads projects on neural networks, probabilistic modeling, and bioinformatics. Key roles include Director of the IGB and AI in Science Institute. Awards include the Dennis Gabor Award and Fellowships from AAAI, AAAS, and IEEE. His work spans interdisciplinary collaborations, such as the DUNE neutrino experiment and AI-driven drug discovery. Teaches courses like Probabilistic Modeling of Biological Data and Neural Networks. Active in conferences, including workshops on deep learning and its implications in science.

Tom WooView profile

Professor

• Theoretical Chemistry
• Physical Chemistry
• Catalysis
• +6 more

Tom Woo is a Professor in the Department of Chemistry at the University of Ottawa's Faculty of Science. His research focuses on computational quantum chemistry, catalysis, and energy-related systems. Using advanced molecular simulations, his group explores microscopic chemical processes and develops novel methods for energy storage, pharmaceutical catalysis, and material design. Key projects include studying catalytic systems for energy conversion and pharmaceutical synthesis, leveraging computational tools to uncover reaction mechanisms inaccessible via experiments. Research interests span computational chemistry, quantum chemistry, molecular dynamics, and nanotechnology. The Woo Group applies these methods to design metal-organic frameworks (MOFs) for CO2 capture, hydrogen storage, and other energy applications. Their work bridges theoretical models with experimental validation, emphasizing high-throughput screening and machine learning. Publications highlight breakthroughs in MOF design, computational validation of material databases, and carbon capture technologies. Collaborations focus on interdisciplinary challenges in energy sustainability and pharmaceutical catalysis.

Fakher AssaadView profile

Professor

• Quantum Many-Body Systems
• Condensed Matter Physics
• Quantum Phase Transitions
• +4 more

Prof. Fakher Assaad is a Professor of Theoretical Physics I at Julius-Maximilians-Universität Würzburg. His research focuses on quantum many-body systems, with expertise in numerical methods like quantum Monte Carlo simulations. He investigates metal-insulator transitions, heavy fermion compounds, and correlated electron systems. His work spans topics including Hubbard models, graphene physics, and topological quantum phases. Assaad leads the Theoretical Physics I team and collaborates with postdocs and students such as Dr. Marcin Raczkowski and Jonas Schwab. Research interests include quantum phase transitions, strongly correlated systems, and emergent phenomena in condensed matter. His studies often address challenges like sign problems in fermionic simulations and the interplay between magnetism and topology. Recent publications highlight advancements in quantum criticality, lattice models, and topological defects. His work bridges theoretical frameworks with computational methods to explore novel materials and quantum phenomena. Advising includes supervision of PhD and master’s students in theoretical physics. His group is part of the Wilhelm Wien Institute and contributes to the FOR1807 research network. The team is based at the M1 Computer Science/Physics building in Würzburg.

Garg VikasView profile

Assistant Professor

• Quantum Computing
• Artificial Intelligence
• Machine Learning
• +8 more

Professor Garg Vikas holds the position of Assistant Professor in the Department of Computer Science at the School of Science. His research spans quantum computing, artificial intelligence, and machine learning with applications in computational biology, healthcare, and drug design. He leads the HEALED/Garg project focused on human-steered machine learning for drug discovery and collaborates with institutions like MIT and industry partners. He co-founded YaiYai Oy, providing AI/ML solutions to global sectors. Education: PhD from MIT CSAIL under Tommi Jaakkola, with postdoctoral and industry experience at Amazon, Microsoft, and IBM. His work aligns with UN SDGs, particularly in healthcare and sustainable energy. Research interests include graph neural networks, generative models, and quantum AI. Recent projects involve climate modeling via physics-informed neural ODEs and optimizing quantum circuits using graph autoencoders. Key collaborations include MIT’s MLPDS Consortium and the Finnish Center for Artificial Intelligence. He supervises doctoral researchers like Yogesh Verma and postdocs such as Kogkalidis.

Xu FangView profile

Lecturer

• Metasurfaces
• Nanophotonics
• Optical Sensing
• +4 more

Dr. Xu Fang is a Lecturer (Assistant Professor) in the School of Electronics and Computer Science at the University of Southampton. His research focuses on metasurfaces and nanophotonics, with applications in automotive sensing and healthcare. He earned a bachelor's degree in Materials Science and Engineering from Tsinghua University (2004) and a Ph.D. in Condensed Matter Physics from the Chinese Academy of Sciences (2009). Before joining Southampton in 2012, he held a RIKEN research fellowship in Japan, where he also gained fluency in Japanese. Dr. Fang's work includes groundbreaking contributions to metasurface technologies, such as metamaterial thin-film logic gates and excitation-selective spectroscopy. He has received five grants from the Royal Society, EPSRC, and Daiwa Anglo-Japanese Foundation as Principal Investigator. His group collaborates with institutions like MIT and the Tokyo University of Agriculture and Technology, hosting visiting scholars and supervising numerous PhD students. Notable achievements include the 2019 Academic Award from the University of Southampton Student Union for teaching excellence. His research group actively explores topics such as tunable metalenses, surface wave generation for THz sensing, and quantum behavior mimicking with classical optics.

Dimitra GeorgiadouView profile

Associate Professor

• Flexible Nanoelectronics
• Green Manufacturing
• Neuromorphic Computing
• +3 more

Dr Dimitra Georgiadou is an Associate Professor at the University of Southampton's School of Electronics and Computer Science, leading the Flexible Nanoelectronics Lab. She is a UKRI Future Leaders Fellow and serves as Deputy Impact Champion in the UKRI Centre for Doctoral Training in Machine Intelligence for Nanoelectronic Devices and Systems (MINDS-CDT). Her research focuses on green manufacturing of flexible nanoelectronics, photonic synapses for neuromorphic computing, and solution-processed non-toxic materials. Key projects include developing Pb-free perovskite photoelectric memristors and radiofrequency Schottky diodes for IoT applications. Education: PhD in Chemical Engineering/Organic Electronics from the National Technical University of Athens (NTUA). Prior roles include Industrial Fellow at Imperial College London and Marie Skłodowska-Curie Fellow. Research spans nanoscale optoelectronic devices, energy harvesting, and flexible substrates. Publications highlight advancements in photodetectors, memristors, and neuromorphic systems, with recent work on self-powered organic photodetectors and γ-ray-induced memristor effects. She has over 40 peer-reviewed articles, including in Laser & Photonics Reviews , Optica , and Advanced Electronic Materials . External roles include editorial positions at Frontiers in Nanotechnology and IEEE Sensors Letters , and membership in the EPSRC Peer Review College. She actively participates in conferences, delivering invited talks on nanosciences, flexible electronics, and neuromorphic devices.

• Quantum Photonics
• Cavity Quantum Electrodynamics
• Quantum Technology
• +3 more

Hadiseh Alaeian is an Assistant Professor jointly appointed in the Departments of Electrical and Computer Engineering and Physics and Astronomy at Purdue University. She holds a Ph.D. in Electrical Engineering from Stanford University and previously served as a Postdoctoral Scholar/Group Leader at the University of Stuttgart in Germany. Education: Ph.D., Electrical Engineering, Stanford University Her research focuses on experimental and theoretical investigations in quantum photonics and cavity quantum electrodynamics (cavity QED). This work bridges fundamental quantum optics principles with applied photonics systems, exploring phenomena such as light-matter interactions at the quantum level. No specific awards, grants, or articles are listed in the provided text. For further details, consult her full profile or publications database.

Giulia SemeghiniView profile

Assistant Professor

• Quantum Computing
• Quantum Information Science
• Condensed Matter Physics
• +3 more

Giulia Semeghini is an Assistant Professor of Applied Physics at Harvard University's School of Engineering and Applied Sciences (SEAS) . Her research focuses on experimental investigations of highly-entangled phases of matter and quantum information processing using programmable atom arrays. The Semeghini Lab, part of the Harvard Quantum Initiative (HQI) and the Center for Ultracold Atoms (CUA), explores intersections between condensed matter physics, high-energy physics, and quantum chemistry. Key achievements include assembling an ultra-high vacuum chamber for atom arrays in 2024 and relocating to the Goel building (HQI's new home) in April 2024. The lab actively recruits students and researchers for open positions at all levels. Research themes span quantum simulation, topological qubits, entanglement engineering, and scalable quantum architectures. Publications emphasize quantum gate implementations, hybrid atom systems, and variational Monte Carlo enhancements. No scientific awards are explicitly listed, but contributions to quantum hardware and algorithms are notable. The lab collaborates widely, aiming to bridge theory and experiment in quantum technologies.

Prabhanjan AnanthView profile

Assistant Professor

• Cryptography
• Theoretical Computer Science
• Post-Quantum Cryptography
• +3 more

Prabhanjan Ananth is an Assistant Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), holding the Glen and Susanne Culler Endowed Chair in Computer Science. He earned his Ph.D. from UCLA in 2017, followed by a postdoctoral fellowship at MIT's CSAIL. His research focuses on cryptography, particularly in classical and post-quantum cryptography, with emphasis on unclonable primitives, pseudorandomness, and cryptographic protocols. Education: Ph.D. in Computer Science from UCLA (2013–2017), postdoctoral research at MIT (2017–2019). Research Interests: His work spans theoretical computer science and cryptography, including post-quantum security, quantum-resistant systems, and unclonable cryptographic primitives. He explores topics like pseudorandomness in quantum models, revocable encryption, and cryptographic protocols for multi-user environments. Recent Publications: His 2025 work advances revocable encryption and pseudorandom unitaries in quantum models. He also contributes to unclonable secret sharing and modular cryptographic design. His research often bridges theoretical foundations with practical applications in quantum-safe systems. Awards: Glen and Susanne Culler Endowed Chair in Computer Science (UCSB). Advising: Current Ph.D. advisees include Aditya Gulati, Yao-Ting Lin, and Divyanshu Bhardwaj. Past students have secured roles at institutions like JPMorgan Chase and EPFL. Teaching: Teaches courses on automata theory (CS 138) and cryptography (CS 178), emphasizing rigorous mathematical proofs and foundational concepts.

Roozbeh Razavi-FarView profile

Assistant Professor

• Machine Learning
• Cybersecurity
• Federated Learning
• +5 more

Roozbeh Razavi-Far is an Assistant Professor at the Faculty of Computer Science and the Canadian Institute for Cybersecurity at the University of New Brunswick. His research focuses on machine learning, big data analytics, and cybersecurity of cyber-physical systems and IoT devices. He has authored/co-authored over 150 publications and is listed by Stanford as among the top 2% of most cited researchers (2022). His work spans federated learning, transfer learning, quantum machine learning, and dependable AI systems. He serves as an Associate Editor for Neurocomputing, Machine Learning with Applications, and IEEE Transactions on Industrial Cyber-Physical Systems, among others. As an IEEE Senior Member, he chairs IEEE Computational Intelligence and Systems, Man, and Cybernetics Societies. Previously, he directed the Learning System and Cybernetics Group at the University of Windsor (2016–2022). His research interests emphasize security in non-stationary environments, adversarial machine learning defenses, and real-time analytics for smart grids. Awards include NSERC-DG, NSERC-ECR, and USRG grants. He has mentored students who received NSERC Alexander G. Bell, MITACS, and Ontario Graduate Scholarships. His recent publications highlight advancements in privacy-preserving split learning, blockchain-based federated learning security, and graph-based malware detection. He also explores quantum computing applications in AI and cybersecurity frameworks for cyber-physical systems.

Charles KaneView profile

Professor

• Condensed Matter Physics
• Quantum Electronics
• Topological Insulators
• +3 more

Charles Kane is the Christopher H. Browne Distinguished Professor of Physics at the University of Pennsylvania's School of Arts & Sciences, Department of Physics and Astronomy. His research focuses on quantum electronic phenomena in solids, particularly topological insulators, quantum spin Hall effects, graphene, and carbon nanotubes. He holds numerous academic chairs and fellowships, including the Class of 1965 Endowed Term Chair and IBM Predoctoral Fellowship. His honors include the Benjamin Franklin Medal, National Academy of Sciences membership, and the Oliver Buckley Condensed Matter Prize. Education: Ph.D. in Physics from MIT (1989) and B.S. in Physics from the University of Chicago (1985). Research Interests: His work integrates quantum field theory and numerical simulations to explore topological phases of matter. Key areas include the theory of topological insulators, quantum spin Hall effects, and nanoscale electronic systems. He emphasizes experimental collaboration to bridge theoretical and applied physics, with a focus on materials like graphene and carbon nanotubes. Articles Trends: Recent publications highlight advancements in topological density correlations, Fermi sea topology, and topological superconductivity. His work often addresses symmetry-enriched phases, quantum transport, and novel electronic states in low-dimensional systems. Awards: Benjamin Franklin Medal (2015) Elected to National Academy of Sciences (2014) Lindback Award for Distinguished Teaching (2014) Physics Frontiers Prize (2013) Grants & Advising: Recipient of Simons Investigator grant (2012) and Oliver Buckley Prize (2012). His research group advises on topological materials and quantum phenomena, though specific student names are not listed in the text. Labs & Teams: Leads research in Penn's Department of Physics, contributing to advancements in condensed matter theory and topological quantum computing.

Jayadev AcharyaView profile

Associate Professor

• Information Theory
• Statistical Inference
• Machine Learning
• +7 more

Jayadev Acharya is an Associate Professor in the School of Electrical and Computer Engineering at Cornell University, with graduate field memberships in Computer Science and Operations Research and Information Engineering. His research focuses on the intersection of information theory, statistical inference, algorithms, and machine learning. He explores trade-offs between data, memory, time, and robustness in learning problems, including quantum information and machine unlearning. Education: B.Tech in Electronics and Communication Engineering from Indian Institute of Technology, Kharagpur (2007) M.S. in Electrical and Computer Engineering from University of California, San Diego (2009) Ph.D. in Electrical and Computer Engineering from University of California, San Diego (2014) Research Trends: His recent work (2020-2022) emphasizes information-constrained inference, differential privacy, quantum entropy estimation, and distributed learning. Key subfields include communication complexity, local privacy, and adaptive gradient processing. His publications span NeurIPS, ICML, COLT, and IEEE Transactions on Information Theory. Awards: Kenneth A. Goldman ’71 Excellence in Teaching Award (Cornell, 2022) MIT Energy Initiative Fellowship (2014) Shannon Graduate Fellowship (UCSD, 2012) Jack Keil Wolf Student Paper Award (ISIT, 2010) Advising and Grants: He advises Sourabh Bhadane, Saravanan Kandasamy, Yuhan Liu, Ziteng Sun, and Huanyu Zhang. Research funded by NSF-CAREER, NSF-CRII, NSF-CIF small grants, and Google Faculty Research Award.

Kyle LuhView profile

Assistant Professor

• Probability
• Random Matrix Theory
• Randomized Algorithms
• +2 more

Kyle Luh is an Assistant Professor at the University of Colorado Boulder in the Department of Mathematics, part of the College of Arts and Sciences. His research focuses on probability, random matrix theory, and randomized algorithms. Education: Ph.D. in Mathematics from Yale University (2017) His recent work explores eigenvalue gaps in random matrices, controllability of non-Hermitian systems, and applications to sparse reconstruction. Publications span topics like circular law for block band matrices, Littlewood–Offord inequalities, and stability analysis in quantum walks. Key trends in his research include spectral analysis of random graphs, robustness in learning algorithms, and combinatorial aspects of matrix theory. His articles highlight intersections between pure probability and applied computational methods.