Find Academic Supervisors

• Materials Science
• Nanotechnology
• Neuromorphic Computing
• +5 more

Feng Xiong is an Associate Professor at the Swanson School of Engineering, University of Pittsburgh. His research focuses on materials science, nanotechnology, and neuromorphic computing, with contributions to thermoelectrics, biomedical sensors, and semiconductor devices. He holds a postdoctoral fellowship from Stanford (2014–2016) and has received prestigious awards such as the Materials Research Society’s Gold Award (2014) and the Chinese Government Overseas Scholarship (2012). Education: Not explicitly listed in provided text, but includes notable fellowships at UIUC and National University of Singapore. Research Interests: Xiong’s work spans interdisciplinary areas including phase-change materials, bio-inspired neuromorphic systems, and energy-efficient electronics. His innovations in DNA-based doping and thermoelectric cooling aim to advance semiconductor and biomedical technologies. Awards and Honors: Nano- and Quantum Science Postdoctoral Fellowship, Stanford Materials Research Society Gold Award Hong, McCully, and Allen Fellowship, UIUC Multiple academic recognitions from China and Taiwan Advising & Grants: No student advisees listed. Research supported through institutional and industrial collaborations. Labs/Teams: Active in University of Pittsburgh’s nanotechnology and materials engineering research groups.

• Coding Theory
• Algebraic Geometry Codes
• Finite Fields
• +7 more

Hans Olav Geil is a Professor and Pro-dean at the Faculty of Engineering and Science , Aalborg University , Denmark, affiliated with the Department of Mathematical Sciences . He is actively engaged in research, academic leadership, and educational innovation, particularly in coding theory and engineering education. University: Aalborg University School: Faculty of Engineering and Science Department: Department of Mathematical Sciences Email: prodekan-eng-udd@aau.dk ORCID: 0000-0002-9666-3399 Website: http://people.math.aau.dk/~olav Geil's research centers on algebraic coding theory , with significant contributions to affine variety codes , quantum codes , network coding , and finite fields . His work bridges theoretical mathematics and practical applications in data transmission and cryptography. He has developed methods for code construction, decoding, and performance bounds, particularly using Gröbner bases and algebraic geometry. His recent publications (2020–2023) show a dual focus: (1) advanced coding techniques like Steane-enlargement of quantum codes and nested code pairs, and (2) educational research on project-based learning (PBL) , digital transformation, and microcredentials at Aalborg University. This reflects his leadership in both technical research and pedagogical innovation. The body of his work, including over 79 publications, demonstrates consistent contributions to IEEE Transactions on Information Theory , Designs, Codes and Cryptography , and Finite Fields and Their Applications . His research often involves collaborations with experts in coding and cryptography. Geil has supervised several PhD students and is involved in multiple research projects. Though no specific awards are listed in the text, his editorial roles and sustained publication record indicate recognition in the academic community. He leads initiatives like the Vision-in-Practice Project , aiming to transform engineering education through structured frameworks and continuous improvement. His work supports interdisciplinary, problem-based learning models central to Aalborg University’s educational philosophy.

Vladimir KolesnikovView profile

Professor

• Cryptography
• Secure Computation
• Homomorphic Encryption
• +3 more

Vladimir Kolesnikov is a Professor and Senior Associate Chair at the Georgia Institute of Technology, jointly affiliated with the School of Computer Science and the School of Cybersecurity and Privacy. He holds a Ph.D. in Computer Science from the University of Toronto (2006) and previously worked at Bell Labs. His research focuses on cryptography and secure computation, with a particular emphasis on practical and foundational aspects of two-party computation, garbled circuits, homomorphic encryption, and secure systems. He has contributed to projects like SCALES (Secure Computation with Ephemeral Servers) and has authored numerous papers and patents. His work also spans Smart Grid security, wireless authentication, and standards development (e.g., WiMAX). He serves as a PI on grants from IARPA and the Office of Naval Research, and his research bridges theory and practical applications in privacy-preserving technologies. Education Ph.D. in Computer Science, University of Toronto, 2006 Research Interests Dr. Kolesnikov’s work revolves around advancing cryptographic techniques for secure computation, including optimizing garbled circuits, exploring zero-knowledge proofs, and developing frameworks for privacy-preserving systems. His interests also extend to key exchange protocols, biometric authentication, and secure network design. He emphasizes both theoretical underpinnings and practical implementations, often addressing scalability and real-world applicability. Grants & Projects Principal Investigator (PI) on IARPA and ONR projects focused on cryptographic systems and secure computation Contributions to SCALES, a framework enabling secure computation with small clients and ephemeral servers Labs & Teams His research is conducted in collaboration with interdisciplinary teams at Georgia Tech, focusing on cryptographic implementations, secure hardware-software co-design, and privacy-preserving technologies.

• Quantum Information Science
• Semiconductor Physics
• Theoretical Physics
• +3 more

Álvaro Perales Eceiza is an Associate Professor at the Department of Automática, Universidad Autónoma de Madrid. He holds a Doctorate from Universidad Carlos III de Madrid (2004) with a thesis on semiconductor superlattice dynamics under Dr. Luis Francisco López Bonilla's supervision. His research interests span quantum information science, semiconductor physics, and interdisciplinary topics like socio-economic systems and space electronics. He is affiliated with the Cognitive Science Research Group (CSRG-UAH) and the Computer Architecture and Technology area. Key research focuses include quantum computation encoding in Ising lattices, radiation effects on space electronics, and undecidability in physics. His work bridges theoretical physics with practical applications, as seen in studies on active learning methods and banking systems' climate impact. Recent publications (2022-2025) highlight advancements in space component qualification and computational complexity reviews. He has contributed to over 15 peer-reviewed articles since 2001, with notable work on entanglement dynamics (2008) and semiconductor superlattice transport (2004). His research often addresses interdisciplinary challenges, combining mathematical modeling with experimental insights.

• Particle Physics
• Signal Processing
• Space Technology
• +5 more

Alberto Regadío Carretero is a Lecturer in the Department of Automática at the University of Alcalá, affiliated with the Space Research Group (SRG-UAH). His research focuses on signal processing for particle detection, cosmic ray physics, and the integration of advanced computing techniques like neural networks and IoT technologies into experimental instrumentation. He holds a PhD in Digital Signal Processing applied to particle detection, awarded in 2014. Education: PhD in Digital Signal Processing, University of Alcalá (2014) Thesis: Procesamiento digital de señal aplicado a la detección de partículas energéticas , supervised by Dr. Sebastián Sánchez Prieto and Dr. Jesús Tabero Godino Research Interests: His work bridges particle physics, space technology, and computational methods. Key areas include: Design of radiation detectors and data acquisition systems using FPGAs and IoT Analysis of cosmic ray spectra and atmospheric effects Application of machine learning (e.g., GANs, reservoir computing) to pulse detection and unfolding Hardware optimization for precision signal processing in space and high-energy environments Key Contributions: Recent work includes: Quantum computing approaches for exoplanet discovery Development of neutron monitors and trajectory tracking systems (e.g., MITO) Unfolding techniques for particle spectra using deep learning Awards & Grants: No specific awards or grants are mentioned in the text, but his involvement in projects like ORCA and the Space Research Group suggests active grant-based research. Lab & Team: He is part of the SRG-UAH Space Research Group, collaborating on projects such as the Antarctic Cosmic Ray Observatory (ORCA) and FPGA-based instrument development.

Hooshyar AssadullahiView profile

Professor

• Early Universe Cosmology
• Non-Gaussianity
• Gravitational Waves
• +3 more

Dr. Hooshyar Assadullahi is a Professor in the School of Mathematics & Physics at the University of Portsmouth, affiliated with the Institute of Cosmology & Gravitation and the Faculty of Technology. He currently serves as Associate Head (Curriculum - Physics). His research focuses on early universe cosmology, particularly non-linear cosmological perturbations and their observational implications. Key interests include non-Gaussianity, gravitational waves, primordial black holes, and stochastic inflation models. He teaches courses such as Space Science and Applications of Physics, Waves and Optics, and Solid State Physics and Detectors. His work bridges theoretical cosmology with observational data, aiming to elucidate early universe processes and their implications for modern cosmological puzzles like dark energy. Notable contributions include studies on stochastic inflation beyond slow-roll dynamics, numerical simulations using importance sampling, and the interplay between inflationary models and primordial black hole formation. He collaborates on projects like 'Cosmology, Gravitation and Astrophysics at Portsmouth' and has contributed to datasets on inflationary field content and stochastic processes. His recent publications explore topics such as noise modeling in stochastic inflation, sudden transitions during inflation, and observational constraints on interacting vacuum energy. He actively supervises research students and engages in interdisciplinary projects, including thin film development through plasma sputtering techniques.

• Positron Physics
• Materials Science
• Solid-State Physics
• +3 more

Prof. Dr. Christoph Hugenschmidt is an Associate Professor of Experimental Physics at the Technical University of Munich (TUM), affiliated with the Heinz Maier-Leibnitz Research Neutron Source (FRM II). His work focuses on positron physics, including the development of advanced positron beam techniques and novel measurement methods for analyzing surfaces, crystal defects, and fundamental leptonic systems. Education: Studied physics at the Universities of Freiburg and Bonn, completed his doctorate in 1997. Since joining TUM, he has led the Positron Physics Research Group and pioneered the NEPOMUC intense positron source. Research stays included the Institut Laue-Langevin (Grenoble) and institutions in Japan. Research Interests: Positron-based defect analysis, 3D defect imaging, spin-resolved electronic structure studies, and antimatter experiments. His group develops state-of-the-art tools like scanning positron microbeams and buffer-gas traps for precision measurements. Key Achievements: EU Erasmus+ Fellowship (2020), JSPS Research Award (2014), TUM Silver Badge (2013). Recent publications emphasize positron annihilation spectroscopy, plasma confinement, and defect characterization in materials like tungsten, lithium titanate, and diamond. Grants & Advising: Supervised numerous TUM scholarship holders. Active in international collaborations such as the APEX experiment for electron-positron pair plasmas. Involved in facility upgrades at FRM II and NEPOMUC. Labs/Teams: Leads the Positron Physics Research Group at TUM, collaborating with global institutions on projects like the NEPOMUC beamline and magnetic trapping systems.

Andreas KronfeldView profile

Researcher

• Quantum Chromodynamics (QCD)
• Lattice Gauge Theory
• Particle Physics
• +3 more

Andreas Kronfeld is a Senior Fellow at the Technical University of Munich's Institute for Advanced Study (TUM-IAS) since 2014, with a primary affiliation at Fermi National Accelerator Laboratory (Fermilab) since 1988. He holds a PhD in Physics from Cornell University (1985) and has been pivotal in advancing lattice gauge theory to interpret particle physics experiments. His research focuses on Quantum Chromodynamics (QCD), leveraging high-performance computing to study hadron properties and inform searches for physics beyond the Standard Model. Key contributions include calculations of meson decay constants and form factors critical for precision experiments. Education & Career: PhD (Cornell, 1985), Postdoc at DESY (1985–1988), Fermilab staff since 1989. Active in evaluating future accelerator projects like the ILC and Project X. Research Interests: Lattice QCD applications, hadron spectroscopy, high-energy physics, and computational methods for QCD simulations. His work bridges theoretical frameworks and experimental validation. Awards: Fellow of AAAS (2013) Fermilab Exceptional Performance Award (2013) Fellow of APS (2002) Grants & Collaborations: Leads lattice QCD collaborations involving multi-institutional teams, focusing on precision calculations for B- and D-meson decays. His work supports global efforts in particle physics experiments and theory. Labs/Teams: Part of Fermilab's Theoretical Physics Department and TUM-IAS's Physics with Effective Field Theories focus group, collaborating with Nora Brambilla and international teams.

Frank Kagan GürkaynakView profile

Researcher

• Energy-Efficient Microelectronics
• Cryptographic Hardware Security
• Digital Integrated Circuit Design
• +4 more

Frank Kagan Gürkaynak is Director of the Microelectronics Design Center (DZ) and a Researcher at ETH Zurich's Department of Information Technology and Electrical Engineering (D-ITET). He leads the PULP open-source hardware project and works closely with Prof. Luca Benini in the Integrated Systems Laboratory (IIS). His academic journey includes BSc/MSc from Istanbul Technical University and a PhD from ETH Zurich. Roles: Microelectronics Design Center Director, Senior Scientist in IIS, VLSI course lecturer Research focuses on energy-efficient digital circuits, cryptographic hardware security, and open-source processor architectures. Key projects include EU-funded initiatives like European Processor Initiative (EPI), Convolve, and NeuroSoC, along with SNSF grants Tiny Trainer and PEDESITE. Active in teaching VLSI design, embedded systems, and essential engineering skills. Publications emphasize secure cryptographic accelerators, low-power processor clusters, and GALS system design methodologies. Contributions include energy-efficient ASICs for IoT to HPC domains and pioneering work in side-channel attack-resistant hardware.

• Semiconductor Lasers
• Photonics
• Ring Lasers
• +5 more

Guy Verschaffelt is a Professor in the Department of Applied Physics and Photonics at Vrije Universiteit Brussel (VUB), with a research career spanning over 25 years. His work centers on advanced photonics systems, particularly semiconductor and ring lasers, with significant contributions to optical computing and Ising machine implementations. Current affiliations include leadership roles in the FWOEOS20 Photonic Ising Machines project and the VLAOO9 Baekeland Mandate for multi-beam LIDAR development. His research interests focus on semiconductor laser dynamics , optical feedback systems , and photonic computing architectures . Key areas include wavelength tuning in ring lasers, speckle pattern recognition for fiber optics, and adiabatic annealing techniques for optical Ising machines. Recent work explores hybrid systems combining photonic reservoirs with deep neural networks to enhance computational performance, demonstrating strong interdisciplinary connections between photonics, quantum computing, and machine learning. Notable scientific achievements include: Barco Prijs voor Afstudeerwerken (1996) Price of Barco N.V. for Master thesis (1997) h-index of 31 with 2,857 citations Leadership in 20 major research projects since 2003 His publication trends reveal a strategic shift toward photonic computing since 2018, with 60% of recent articles (2023-2025) focused on Ising machines, optical annealing, and neural network integration. This reflects broader field movements toward optical solutions for NP-hard optimization problems. Current projects like FWOEOS20 demonstrate sustained funding success, including Tier 1 compute grants through 2025. Media coverage of his 2009 speckle reduction research for laser projections highlights real-world impact in display technology.

Charles L. BrooksView profile

Professor

• Biophysics
• Computational Chemistry
• Molecular Dynamics Simulations
• +6 more

Charles L. Brooks is the Cyrus Levinthal Distinguished University Professor of Chemistry and Biophysics at the University of Michigan, Ann Arbor. He also serves as Director of the Biophysics Program and holds the Warner-Lambert/Parke-Davis Professorship in Chemistry. Brooks earned his Ph.D. from Purdue University and completed postdoctoral research at Harvard University. His research focuses on computational biophysics, molecular simulations, and drug discovery. Key areas include protein folding, enzyme catalysis, and the development of computational tools like the CHARMM software suite. Brooks' group investigates complex biological systems such as viruses, ribosomes, and molecular machines, leveraging high-performance computing and GPU-accelerated methods. Develops novel methods in statistical mechanics and quantum chemistry Leads projects in drug design, pH-dependent molecular processes, and enzyme engineering Pioneers machine learning approaches for protein design and ancestral sequence reconstruction Brooks has authored over 300 publications and holds numerous awards, including the Hans Neurath Award and fellowships from the Biophysical Society and AAAS. His lab manages a computing cluster with 5,000 CPU cores and 300 GPUs. Recent work includes studies on SARS-CoV-2 inhibitors, protein aggregation mechanisms, and the structural basis of enzyme catalysis. His team collaborates with experimentalists to bridge computational predictions with biochemical validation.

• Neuromorphic Computing
• Reservoir Computing
• Reinforcement Learning
• +3 more

Prof. Abigail Morrison is a Professor and Group Leader of the Computation in Neural Circuits group at the Institute for Advanced Simulation (IAS-6), part of Forschungszentrum Jülich. Her work focuses on advancing neuromorphic computing, reservoir computing, and spiking neural network simulations. She leads development of the NEST simulator and NESTML modeling language, tools critical for large-scale brain modeling. Key research areas include: Neuromorphic hardware-software co-design Biophysically plausible neural network models GPU-accelerated simulation frameworks Multi-scale brain co-simulation techniques Applications in embodied AI and neuroscience Her lab contributes to the European EBRAINS infrastructure and has pioneered methods for parallel GPU-based network construction. Recent work explores topographic neural circuit architectures for signal processing and reinforcement learning in neuromorphic systems. Notable achievements include: Development of NESTML (v8.0+) ODE-toolbox for ODE solver selection Co-design of HNC neuromorphic compute nodes Advances in dendritic computation modeling Current efforts emphasize exascale computing readiness, neuromorphic system validation, and bridging biological plausibility with computational efficiency in neural network simulations.

Claude DionView profile

Associate Professor

• Atomic Physics
• Molecular Physics
• Computational Physics
• +7 more

Claude Dion is an Associate Professor at the Department of Physics, Umeå University, and serves as Director of International Studies. His research focuses on atomic and molecular physics, computational physics, and quantum phenomena. He investigates ultracold atoms/molecules in optical lattices, laser control of molecular systems, and combustion dynamics in confined geometries. Recent work includes studies on flame extinction/acceleration mechanisms in narrow channels and magnetic deflagration in nanomagnet crystals. His academic contributions span over 50 peer-reviewed articles in journals like Physical Review Letters , Computer Physics Communications , and Molecular Physics . Research emphasizes numerical simulations of quantum systems and combustion phenomena, with a focus on interdisciplinary applications. Teaching responsibilities include courses in Statistical Physics, Quantum Mechanics II, Atomic/Molecular Physics, and Numerical Methods in Physics. He has developed computational tools for wave-packet dynamics and contributed to laser cooling experiments in optical lattice systems. His work bridges theoretical and applied physics, addressing fundamental questions in quantum trapping, spin dynamics, and combustion instability while maintaining strong ties to experimental methods.

• Quantum simulations
• Quantum computing
• Quantum resource theories
• +4 more

Dr. Qi Zhao is a Tenure-Track Assistant Professor in the Department of Computer Science at the University of Hong Kong (HKU). His research focuses on quantum information science, including quantum simulations, quantum computing, quantum resource theories, and self-testing quantum information. He holds a PhD from Tsinghua University (2018) and postdoctoral experience at the University of Science and Technology of China and the University of Maryland's QuICS as a Hartree Fellow. His work bridges theoretical advancements and experimental applications, with contributions to quantum algorithms, entanglement detection, and device-independent protocols. Key research interests include Hamiltonian simulation optimizations, quantum resource theory frameworks, and robust self-testing methodologies. Notable achievements include the 'Innovators Under 35 Asia Pacific 2024' recognition by MIT Technology Review and significant grants such as the 2030 National Science and Technology Major Project of China. His team explores quantum differential equation solvers, entanglement acceleration in simulations, and practical quantum algorithm implementations. Dr. Zhao advises a growing team of PhD and MPhil students, focusing on quantum computing and information theory. His research has led to publications in top journals like Nature Physics , Physical Review Letters , and Communications in Mathematical Physics . Current projects include developing efficient quantum algorithms for scientific computation and exploring the theoretical limits of quantum simulation techniques.

Bernd DammannView profile

Associate Professor

• High-Performance Computing
• Scientific GPU Computing
• Parallel Programming
• +3 more

Bernd Dammann is an Associate Professor in Scientific Computing at the Technical University of Denmark (DTU) , Department of Applied Mathematics and Computer Science. In parallel he serves as Scientific Lead & Architect in the DTU Computing Center (DCC) and co-founded DTU’s GPUlab in 2007, giving him dual roles in both academic research and institutional HPC services. Education Dipl.Phys. in Statistical Physics, University of Mainz, 1992 PhD in Physical Chemistry, DTU, 1996 Research interests Over almost three decades Dammann has focused on computational methods for large-scale scientific problems. His core expertise lies in: High-Performance Computing and parallel programming paradigms (OpenMP, MPI, GPU) Scientific GPU computing and many-core architectures Application tuning and performance optimization for heterogeneous systems Uncertainty quantification, Monte-Carlo methods, and real-time control applications in biomedicine (diabetes technology) Ultrasound beamforming and advanced imaging techniques Publication trends His 34 publications (1996-2025) trace a clear evolution from theoretical physics and surface-science simulations to GPU-accelerated engineering and biomedical systems. Recent work clusters around real-time biomedical control (artificial pancreas, virtual clinical trials) and high-resolution ultrasound imaging, all leveraging GPU acceleration and high-performance computing to achieve real-time performance. Scientific awards & recognition Contributor to 1 patent family and widely downloaded technical reports (>10 k downloads for OpenCL tutorial) Consistently high citation counts on key optimization and control papers (e.g., 93 citations for 2014 Management Science article) Teaching, supervision & grants He teaches or co-teaches multiple DTU courses: High-Performance Computing , Large-scale Computations , Python & HPC , Mathematical Software , and HPC with FORTRAN . While individual students are not named, his role in GPUlab and DCC implies ongoing PhD and MSc supervision, and his projects list six active collaborations including EU and national HPC infrastructure grants. Labs & teams Dammann co-founded GPUlab (2007) and presently leads the HPC architecture team in the DTU Computing Center , a central facility supplying cluster resources to the entire university.