Find Academic Supervisors

• Neuromorphic Computing
• Neural Networks
• Machine Learning
• +4 more

Dr. Denis Kleyko is a Visiting Research Fellow at La Trobe University's Business Analytics department. His work focuses on neuromorphic computing, hyperdimensional computing, and neuro-inspired algorithms. He has contributed to frameworks like NeuroBench for benchmarking neuromorphic systems and authored comprehensive surveys on vector symbolic architectures. Key research interests include neuromorphic reservoir computing, sparse randomized embeddings, and cognitive mapping through neural circuits. His publications span journals such as Nature Communications and IEEE Transactions, emphasizing interdisciplinary approaches in machine learning and neuroscience. Collaborations include international teams addressing challenges in seizure prediction, compositional learning, and high-dimensional data processing. Notable outputs include foundational work on HyperSEED and efficient optimization using Ising machines.

Noah Stephens-DavidowitzView profile

Assistant Professor

• Lattices
• Theoretical Computer Science
• Cryptography
• +3 more

Noah Stephens-Davidowitz is an Assistant Professor in the Department of Computer Science at Cornell University, with affiliations to the Applied Mathematics and Mathematics fields. He holds a Ph.D. from New York University (2017), advised by Oded Regev and Yevgeniy Dodis. His research focuses on lattices, theoretical computer science, cryptography, and geometry. Previously, he was a Simons Institute fellow, a postdoc at MIT and Princeton, and a visiting researcher at the Institute for Advanced Study. Education: Ph.D. in Computer Science from New York University (2017). Affiliated colleges at Cornell include the Ann S. Bowers College of Computing and Information Science, College of Arts and Sciences, and College of Engineering. Research Interests: Lattice-based cryptography, algorithmic complexity, geometric algorithms, and cryptographic hardness assumptions. His work bridges theoretical foundations and practical applications, including secure messaging protocols, cryptographic protocol design, and lattice reduction techniques. Notable Contributions: Developed reverse Minkowski theorems, advanced lattice reduction algorithms, and analyzed computational hardness of lattice problems. His work on secure messaging with reverse firewalls and time-space tradeoffs for function inversion has been influential in cryptography. Advising: Supervises four PhD students: Yael Eisenberg, Kyle Fridberg, Surendra Ghentiyala, and Spencer Peters. Active in program committees for conferences like CRYPTO, FOCS, and STOC. Labs/Teams: Involved in the Simons Collaboration on Algorithms and Geometry, and contributes to lattice-based cryptography research initiatives at Cornell's College of Computing and Information Science.

Elhadj BenkhelifaView profile

Professor

• Cloud/Edge Computing
• Bio-Inspired Computing
• Cybersecurity
• +7 more

Elhadj Benkhelifa is a full Professor of Computer Science and Digital Innovations at Staffordshire University, leading the Head of Professoriate role to advance university strategies. He founded the Smart Systems, AI and Cybersecurity Research Centre (SSAICS), directing 15 staff and 23 PhD students. Previously, he held roles at Cranfield University and the University of the West of England. His interdisciplinary research focuses on cybersecurity, cloud/edge computing, bio-inspired systems, and AI applications in healthcare and digital transformation. He is a Visiting Professor at Universities of Suffolk, Lyon3, and Paris 8, and chairs the IEEE UK&I Section's Education & STEM office. Education includes a PhD in Artificial-Life (Bio Inspired Evolvable and Self-Healing Systems) from UWE Bristol Robotics Lab, alongside postgraduate certifications in research supervision and higher education. His work bridges academia and industry, addressing challenges in cybersecurity, IoT, and healthcare through applied research. Research interests span cloud computing paradigms, semantic technologies, and AI ethics, with over 150 publications. His recent articles emphasize AI-driven cybersecurity solutions, quantum computing applications, and medical diagnostics using deep learning. He actively contributes to open-access publishing and advises on national cybersecurity strategies. Awarded Fellow of the UK Higher Education Academy, he leads impactful projects including malware detection systems, semantic knowledge graphs for public health, and blockchain-based authentication frameworks. His teaching spans undergraduate to PhD levels, with over 100 supervised projects. He also serves on advisory boards for cybersecurity initiatives and Staffordshire Police's evidence-based practices.

• Machine Learning
• Computer Vision
• Biomedical Data Science
• +3 more

René Vidal is the Rachleff & Penn Integrates Knowledge (PIK) University Professor of Electrical and Systems Engineering & Radiology at the University of Pennsylvania and Director of the Center for Innovation in Data Engineering and Science (IDEAS). He holds secondary appointments in Computer and Information Science and Statistics and Data Science. His research focuses on the foundations of deep learning, trustworthy AI, and their applications in computer vision and biomedical data science. Education: B.S. (Electrical Engineering, valedictorian) from Pontificia Universidad Católica de Chile (1997), M.S. and Ph.D. (Electrical Engineering and Computer Sciences) from UC Berkeley (2000 and 2003). Prior roles include Professor at Johns Hopkins University (2004–2022) and leadership roles in institutions like MINDS and THEORINET. Research spans machine learning (mathematics of deep learning, manifold learning), computer vision (activity recognition, medical imaging), biomedical data science (cardiac MRI analysis, autism diagnosis), and dynamical systems. Awards include IEEE Fellow (2014), IAPR Fellow (2016), ACM Fellow, and the IEEE Edward J. McCluskey Technical Achievement Award (2021). Current lab members include 15+ graduate students and postdocs working on topics like adversarial robustness, optimization theory, and biomedical applications. His work is supported by grants from the Department of Defense and collaborations with organizations like Amazon and NORCE. Labs/Teams: Director of IDEAS Center, MINDS, and THEORINET. Active in editorial roles for journals like TPAMI and CVIU, and program chair for ICCV 2015 and CVPR 2014.

Ersoy SubasiView profile

Associate Professor

• Stochastic Programming
• Financial Mathematics
• Data Mining
• +5 more

Ersoy Subasi is an Associate Professor and Doctoral Program Coordinator at the College of Aeronautics, Florida Institute of Technology. His research focuses on stochastic programming, financial mathematics, and data mining, with interdisciplinary applications in biomedical engineering, genomics, and quantum computing. He emphasizes collaborative research and industry partnerships to solve complex real-world challenges. Subasi has published extensively in journals and conference proceedings, addressing topics like blood pressure monitoring, chronic kidney disease analysis, and machine learning-driven risk estimation. His work integrates mathematical rigor with computational methods, spanning optimization theory, genomic data interpretation, and quantum technologies. Despite his prolific output, there are no listed academic awards or formal advisees in the provided profile. Subasi’s contributions highlight the intersection of operations research with healthcare technology and financial modeling. Key areas of exploration include: Non-invasive biomedical monitoring systems High-dimensional genomic data analysis Quantum-based algorithms for random number generation Discrete moment problems with shape constraints He is accessible at esubasi@fit.edu and maintains active profiles on ORCID and Google Scholar.

• Cryptography
• Cybersecurity
• Blockchain Technology
• +3 more

Elena Andreeva is a tenure-track Assistant Professor in the Security and Privacy department at TU Wien. Her research focuses on symmetric cryptography, including authenticated encryption, block ciphers, hash functions, privacy-friendly protocols, and blockchain technologies. She coordinates the Double-Degree Program in IT Security and actively participates in the Faculty Council. Her work emphasizes both theoretical foundations and practical cryptographic solutions for secure data communication and storage. Research interests include designing and analyzing cryptographic algorithms with applications in IoT-to-cloud secure computation, lightweight encryption schemes, and quantum-resistant primitives. Her projects, such as SFB SPyCoDe (2023–2026), explore efficient compression functions and expanding PRFs for arithmetization-oriented hashing. Articles Overview : Recent publications emphasize authenticated encryption schemes (e.g., COLM), pseudorandom number generators (TPRF-based), and novel cryptographic designs like Forkcipher. These contributions address both theoretical security models and practical efficiency in resource-constrained environments. She advises students on master/bachelor theses and internships, fostering the next generation of cybersecurity researchers. Her involvement in curriculum development and interdisciplinary programs underscores her commitment to advancing both academic and applied cryptography.

Brent NelsonView profile

Associate Professor

• Free Probability
• Operator Algebras
• Von Neumann Algebras
• +3 more

Brent Nelson is an Associate Professor in the Department of Mathematics at Michigan State University (MSU). He holds a PhD in Mathematics from the University of California, Los Angeles (UCLA), under the supervision of Dimitri Shlyakhtenko, and a BS in Mathematics from the University of Illinois at Urbana-Champaign (UIUC). His research focuses on free probability, non-tracial von Neumann algebras, free transport, subfactor planar algebras, and bi-free probability. He has held postdoctoral positions at Vanderbilt University and the University of California, Berkeley, and has been recognized with awards including the Pacific Journal of Mathematics Dissertation Prize (2015) and the Distinguished Teaching Award (2018). Key research interests include the structure of von Neumann algebras, free monotone transport, and applications to quantum graphs and operator algebras. He has authored numerous publications in top-tier journals and presented at international conferences such as the Canadian Operator Symposium and the Banff International Research Station workshops. His teaching includes advanced courses on functional analysis, operator algebras, and real/complex analysis at MSU and other institutions. Grants include NSF funding for projects on non-tracial derivations and distributions, and he has organized conferences like the Groundwork for Operator Algebras Lecture Series (2020). His work bridges abstract operator algebra theory with applications in quantum probability and ergodic theory.

Marc BaldoView profile

Professor

• High efficiency solar cells
• solid-state lighting
• optoelectronics
• +9 more

Marc Baldo is the Dugald C. Jackson Professor of Electrical Engineering and the Director of the Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT), where he has been a faculty member since 2002. His work spans multiple departments and research centers within MIT's School of Engineering, with primary affiliation in the Department of Electrical Engineering and Computer Science (EECS). Dr. Baldo's educational background includes: B. Eng. (Electrical Engineering) from the University of Sydney in 1995 with first class honors and university medal M.A. from Princeton University in 1998 Ph.D. from Princeton University in 2001 Professor Baldo's research focuses on the intersection of materials science, electrical engineering, and quantum physics, with particular emphasis on optoelectronics , spintronics , and sensing technologies . His work on high efficiency solar cells and solid-state lighting has pushed the boundaries of organic electronics and photonics. The Spin and Excitonic Engineering Group he leads develops stable blue organic light-emitting devices and improves silicon solar cells beyond the Shockley-Queisser limit. His research also explores applications of spintronics to computation and the development of low-cost, high-speed gas sensors. Professor Baldo's work on exciton fission and fusion represents a significant contribution to the field of photovoltaics, potentially enabling solar cells with efficiencies beyond traditional limits. His most recent publications reveal a strong focus on advancing organic electroluminescent devices, photon upconversion technologies, and spintronic applications for artificial intelligence. The research trends show progression from fundamental exciton physics toward practical applications in energy conversion and computing technologies, with increasing integration of machine learning approaches in materials design and device optimization. Dr. Baldo's scientific recognition includes: Jan Rajchman Prize from the Society for Information Display (2013) for contributions to modern phosphorescent organic light emitting displays Membership in the U.S. National Academy of Engineering Leadership of the Center for Excitonics, a Department of Energy Energy Frontier Research Center (2009-2019) As Director of the Research Laboratory of Electronics since 2017, Professor Baldo oversees one of MIT's largest interdisciplinary research laboratories, managing substantial research funding and guiding numerous federally and industry-sponsored projects. His leadership extends to significant MIT Energy Initiative Seed Fund grants and collaborations with national laboratories, including involvement in National Quantum Information Science Research Centers. His administrative role complements his active research program, demonstrating a successful balance between scientific innovation and research management. Professor Baldo leads the Spin and Excitonic Engineering Group, which operates within the Research Laboratory of Electronics framework. The group maintains strong connections with the Organic and Nanostructured Electronics Laboratory and the former Center for Excitonics. This collaborative environment fosters interdisciplinary research across materials science, electrical engineering, and quantum physics, with facilities supporting advanced materials synthesis, device fabrication, and optical characterization.

Máté FarkasView profile

Lecturer

• Quantum Information Theory
• Bell Non-locality
• Device-Independent Quantum Cryptography
• +2 more

Dr Máté Farkas is a Lecturer in Mathematics and Quantum Technologies at the Department of Mathematics, University of York, appointed in 2023. His research focuses on the mathematical foundations of quantum information processing, specializing in device-independent protocols and quantum nonlocality phenomena. His educational background includes: MSc in Physics from Budapest University of Technology and Economics (supervised by Péter Vrana) PhD in Physics from University of Gdansk/National Quantum Information Centre (supervised by Marcin Pawłowski) Postdoctoral research at ICFO, Barcelona, including a Marie Skłodowska-Curie COFUND PROBIST Fellowship Research interests center on quantum phenomena with no classical counterparts, including Bell non-locality, contextuality, and measurement incompatibility. His work develops mathematical frameworks for quantum advantage in information processing, with applications in device-independent quantum key distribution, certified random number generation, and quantum device certification using observable measurement statistics. Recent publications demonstrate trends toward high-dimensional quantum systems, loophole-free nonlocality demonstrations, and practical implementations of device-independent protocols. Key themes include optimizing quantum key rates from minimal nonlocality, characterizing intrinsic quantum randomness, and developing convex optimization tools for quantum information. Scientific recognition includes: Marie Skłodowska-Curie COFUND PROBIST Postdoctoral Fellowship Dr Farkas actively contributes to the quantum research community through invited talks at international conferences on topics including quantum randomness generation, self-testing protocols, and device-independent security. He supervises PhD projects in Bell inequalities, quantum key distribution, and high-dimensional quantum measurements within York's Mathematical Physics and Quantum Information Research Group.

Thomas HebdigeView profile

Research Fellow

• Quantum Information Theory
• Theoretical Physics
• Quantum Computing
• +5 more

Thomas Hebdige is a Research Fellow at the University of York, affiliated with the Mathematical Physics and Quantum Information Research Group . His work focuses on theoretical models for quantum random number generators and their certification, collaborating with the National Physical Laboratory as part of the EPSRC Quantum Communications Hub . Education includes an MSci in Physics with Theoretical Physics (Imperial College London) and a PhD in Controlled Quantum Dynamics , supervised by Dr. David Jennings at Imperial College London's Centre for Doctoral Training. Contact: Office G/N/104, University of York (+44 1904 32 3079).

Roger ColbeckView profile

Professor

• Quantum Cryptography
• Quantum Foundations
• Device-Independent Protocols
• +3 more

Professor Roger Colbeck is a faculty member in the Department of Mathematics at the University of York, where he serves as Head of Section for Applied Mathematics. His research focuses on quantum information theory and foundational questions in quantum mechanics. He holds a PhD from the University of Cambridge and has held positions at ETH Zurich, the Perimeter Institute for Theoretical Physics, and as a Junior Research Fellow at Homerton College, Cambridge. His research explores interdisciplinary areas including device-independent quantum cryptography, quantum random number generation, uncertainty relations, and causal models in quantum theory. He investigates the implications of quantum mechanics for information processing, such as secure computations and protocols leveraging relativistic principles. Professor Colbeck has contributed to projects like the EPSRC Quantum Communications Hub and collaborates internationally. His work often bridges theoretical foundations with practical applications, such as improving cryptographic security through device-independent approaches. He advises three doctoral students and offers PhD projects in quantum cryptography, random number generation, or quantum foundations. His research has been published in top journals, including Physical Review Letters , and he frequently presents at conferences and seminars on topics like nonlocality and causal structures.

Maryna ViazovskaView profile

Professor

• Sphere packing
• Fourier analysis
• Automorphic forms
• +3 more

Maryna Viazovska is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), renowned for solving the sphere packing problem in dimensions 8 and 24. She holds a PhD from the Max Planck Institute for Mathematics and the University of Bonn (2013), with earlier degrees from Technical University Kaiserslautern (M.Sc., 2007) and Kyiv National Taras Shevchenko University (B.Sc., 2005). Her research focuses on sphere packing, optimal point configurations, Fourier analysis, automorphic forms, and number theory. Notable achievements include proving the E8 lattice's optimality in 8 dimensions and the Leech lattice in 24 dimensions, leveraging modular forms and interpolation techniques. Key awards include the Fields Medal (2022), Fermat Prize (2020), and Salem Prize (2016). She has held positions at Humboldt University of Berlin (BMS Dirichlet Postdoc), Institut des Hautes Études Scientifiques, and Princeton University. Her publications span top journals like Annals of Mathematics and address interdisciplinary topics such as superconductivity and combinatorial geometry. Viazovska’s work bridges pure mathematics with applications in coding theory and physics.

Yanhua HongView profile

Academic

• Semiconductor Lasers
• Nonlinear Dynamics
• Chaos Theory
• +3 more

Dr. Yanhua Hong is a Reader in the School of Computing and Engineering at Bangor University. His research focuses on nonlinear dynamics of semiconductor lasers, chaos theory, and their applications in optical communications and microwave photonics. He leads projects such as 'Microwave Photonics Generation Using Low-Cost VCSELs' and has published extensively in journals like Optics Express and Photonics. Key areas of expertise include semiconductor laser dynamics under optical feedback, secure communication systems leveraging chaotic signals, and the design of photonic microwave generation systems. Hong collaborates internationally with institutions like Southwest University (China) and the Universitat Politècnica de Catalunya (Spain). He actively supervises PhD students and examines external theses. Recent work highlights include high-speed secure stream ciphers using synchronized chaos, optimization of multimode fiber imaging systems, and analysis of intermittent laser dynamics via reservoir computing. His contributions bridge fundamental research with applied photonics, contributing to advancements in optical security, signal processing, and next-generation communication networks.

Selçuk KöseView profile

Professor

• Hardware Security
• On-Chip Power Delivery
• Cryogenic Electronics
• +3 more

Selçuk Köse is a Full Professor in the Department of Electrical and Computer Engineering at the University of Rochester. Previously, he held positions at the University of South Florida as an Assistant Professor (2012-2018) and Associate Professor (2018-2019). He earned his B.Sc. from Bilkent University (2006), M.S. and Ph.D. from the University of Rochester (2008 and 2012, respectively). His research focuses on hardware security (side-channel attacks, fault injection, PUFs), on-chip power delivery, cryogenic electronics, graphene nanoribbon transistors, and nature-inspired computing (e.g., Ising machines). He has received prestigious awards including the NSF CAREER Award (2014) and Cisco Research Awards (2015–2017). His recent work emphasizes security in quantum computing interfaces, power delivery networks, and covert channel mitigation. Research funding comes from NSF, DARPA, DoE, and industry partners. He serves as an associate editor for IEEE and Springer journals.

Isaak D. MayergoyzView profile

Professor

• Electrostatic (Plasmon) Resonances
• Spintronics
• Nonlinear Magnetization Dynamics
• +7 more

Prof. Isaak D. Mayergoyz is a Distinguished University Professor and Alford L. Ward Professor at the University of Maryland's Department of Electrical and Computer Engineering. He has held his position since 1980, following his immigration from the former Soviet Union, where he worked as a senior research scientist at the Institute of Cybernetics. He co-founded the electric power engineering curriculum at UMD and has authored/coauthored 17 books and over 400 papers. His research spans electrostatic/plasmon resonances, spintronics, nonlinear magnetization dynamics, quantum mechanics, and economic hysteresis modeling. He has served as an IEEE Distinguished Lecturer, holds IEEE Fellow status, and received the IEEE Magnetics Society Achievement Award (2009) and Distinguished Scholar-Teacher Award (1995-96). Education: Master's and Ph.D. from the former Soviet Union (institutions unspecified). Affiliations: Former GE Research and Development Center visiting fellow; editorial roles at IEEE Transactions on Magnetics and Academic Press-Elsevier Electromagnetism series. His research focuses on nanoscale systems, including magnetic resonance, spintronic devices, and hysteresis phenomena. Notable contributions include work on scanning tunneling microscopy for surface spin analysis, optimal PWM techniques for power electronics, and macroeconomic hysteresis modeling. His publications span interdisciplinary areas like nanomagnetism, quantum materials, and energy systems. Grants/Consultancies: $50K Business Competition winner (2006); extensive industry collaboration with GE on MRI systems. Labs/Teams: Active in collaborative research with ECE alumni and industry partners, focusing on experimental and computational electromagnetics.