جست‌وجوی استاد و پژوهشگر

Ullrich Mönichمشاهده پروفایل

پژوهشگر

• Signal Processing
• Wireless Communications
• Machine Learning
• +۷ مورد دیگر

Dr.-Ing. Ullrich Mönich is a Senior Researcher and Lecturer at the Technical University of Munich (TUM) , affiliated with the Chair of Theoretical Information Technology and leading research activities at the Advanced Communication Systems and Embedded Security Lab (ACES Lab) . Since 2019, he has been instrumental in shaping experimental and theoretical research in 6G communications, physical layer security, and signal processing. Education: Dr.-Ing. in Electrical Engineering, Technische Universität München (2011) – supervised by Prof. Holger Boche Previous affiliations include MIT (2012–2015) and TU Berlin Research Focus: His research spans signal processing, wireless communications, machine learning, and sampling theory , with a strong emphasis on physical layer security , computability in signal processing , and 6G communications . He explores theoretical foundations and practical implementations, including neuromorphic computing, digital twinning, and secure modular coding schemes. Publications & Trends: His recent publications (2023–2025) are heavily concentrated in 6G communications , integrated sensing and communications (ISAC) , semantic physical layer security , and digital twinning . These works often combine theoretical analysis with experimental validation using 5G/6G testbeds and neuromorphic hardware. Teaching & Supervision: Regularly teaches "Foundations of Analog, Digital, and Quantum Computers" (tutorials since 2018) Previously taught "Applied Functional Analysis" and "Advanced Signal Theory" Involved in practical courses like "Software Defined Radio Laboratory" Labs & Teams: He leads the ACES Lab at TUM, which focuses on experimental validation of advanced communication systems, including physical layer security, neuromorphic computing, and 6G testbeds. The lab collaborates with national and international partners, including MIT, and is supported by major funding bodies such as the German Federal Ministry of Education and Research (BMBF) and the German Research Foundation (DFG).

Sadegh Talebiمشاهده پروفایل

استادیار

• Reinforcement Learning
• Markov Decision Processes
• Online Learning
• +۲ مورد دیگر

Sadegh Talebi is a Tenure Track Assistant Professor in the Machine Learning Section at the Department of Computer Science, University of Copenhagen . His research focuses on theoretical aspects of reinforcement learning, Markov decision processes, online learning, stochastic multi-armed bandit problems, and resource allocation in networks. Education BSc in Electrical Engineering (minor: Electronics) from Iran University of Science and Technology (IUST) (2004) MSc in Electrical Engineering (minor: Communication Systems) from Sharif University of Technology (2006) PhD in Electrical Engineering from the Department of Automatic Control at KTH Royal Institute of Technology (supervised by Alexandre Proutiere and Mikael Johansson) Research Specializes in theoretical foundations of reinforcement learning and online learning Key contributions in stochastic optimization, MDPs, and bandit algorithms Collaborates on applications in resource allocation and quantum computing Publications include high-impact work on offline RL, differentially private exploration, and scalable MDP solutions in journals like Neural Processing Letters and conferences such as NeurIPS and UAI.

Robert Polliceمشاهده پروفایل

مدرس

• Computational Chemistry
• Quantum Chemistry
• Machine Learning
• +۶ مورد دیگر

Robert Pollice is a Lecturer at the Faculty of Science and Engineering , University of Groningen , specializing in Homogeneous Catalysis . His research integrates computational chemistry , machine learning , and automated experimentation to accelerate molecular design and catalyst development . Research Interests focus on homogeneous catalysis , quantum chemistry , and machine learning applications. His work addresses challenges in reaction mechanism modeling , noncovalent interactions , and inverse molecular design , leveraging closed-loop optimization and large language models for chemical data analysis . Publications span quantum chemical simulations , solvation energy calculations , excited state engineering , and automated catalyst discovery . His recent studies explore inverted singlet-triplet gaps , machine learning for reaction modeling , and SELFIES for molecular string representations . Peer-review Contributions include evaluations for journals like Organic Process Research & Development , Materials Advances , and Chem , reflecting his expertise in catalysis , quantum chemistry , and AI-driven chemical discovery .

Thomas Brunoldمشاهده پروفایل

استاد

• Inorganic Chemistry
• Biochemistry
• Computational Chemistry
• +۵ مورد دیگر

Thomas Brunold is a Professor of Chemistry at the University of Wisconsin–Madison, focusing on the geometric and electronic properties of metal centers in proteins and cofactors . His work integrates spectroscopic techniques (electronic absorption, circular dichroism, magnetic circular dichroism, resonance Raman, electron paramagnetic resonance) with density functional theory (DFT) and quantum mechanics/molecular mechanics (QM/MM) calculations to validate bonding descriptions and explore catalytic intermediates. Bio-organometallic cofactors (adenosylcobalamin, methylcobalamin, NiF430) Metal-dependent superoxide dismutases (Ni-, Fe-, Mn-SODs) Polynuclear NiFeS enzymes (ACS, CODH) His research spans vitamin B12 chemistry , metalloenzyme specificity , and redox-active clusters , with a focus on resolving substrate-bound intermediates and mechanistic debates in catalytic cycles. Recent publications emphasize ligand dynamics , second-sphere residue effects , and metal-cofactor interactions . Scientific awards include the Taylor Teaching Award (2024) , Kellett Mid-Career Award (2020) , and NSF-CAREER Award (2003) . He mentors students in the Brunold Lab, including Ryan Hall , Laura Elmendorf , and Maddy Rodemeier (co-advised with Andrew Buller), with multiple Outstanding TA Awards to lab members.

• Machine Learning
• Quantum Computing
• Medical Data Analysis
• +۷ مورد دیگر

Luka Radic is a Researcher in the Machine Learning Section at the Department of Computer Science, University of Copenhagen. His work bridges theoretical and applied research in machine learning, with a focus on quantum machine learning , large language models , and fairness in AI systems.

• Beyond the Standard Model
• Supersymmetry
• String Theory
• +۳ مورد دیگر

Professor Steve Abel is a Professor in the Department of Mathematical Sciences and the Department of Physics at Durham University, with additional affiliation to the Institute for Particle Physics Phenomenology. His research spans theoretical physics with a strong focus on string theory, particle physics phenomenology, and emerging applications of quantum computing. Professor Abel's research interests include: Beyond the Standard Model physics Supersymmetry and string model building Applications of quantum computing to particle physics Genetic algorithms in theoretical physics Non-supersymmetric string vacua Analysis of Professor Abel's recent publications reveals a significant shift toward interdisciplinary research combining traditional theoretical physics with cutting-edge computational techniques. His work increasingly focuses on applying quantum computing and machine learning methods to solve complex problems in string theory and particle physics. Many recent papers explore quantum simulation of field theories, quantum annealing for string model building, and genetic algorithms for solving physics problems. This represents a convergence of theoretical physics with computational science that is transforming how fundamental physics research is conducted. Professor Abel has received recognition for his work, most notably a Cern Theory 6 month Scientific Associateship. His research collaborations span international institutions across Europe and North America, reflecting the global nature of theoretical physics research. Professor Abel actively supervises graduate students, including Puya Mirkarimi. His research program likely involves collaboration with various research groups at Durham University working on theoretical particle physics, quantum computing applications, and computational methods for theoretical physics problems.

Richard Giulianottiمشاهده پروفایل

استاد

• Sociology of Sport
• Globalization and Sport
• Sport for Development and Peace
• +۳ مورد دیگر

Richard Giulianotti is a Professor of Sociology and UNESCO Chair in Sport, Physical Activity and Education for Development at Loughborough University. He holds affiliations with Harvard University's Global Sports Initiative and has served on UNESCO’s Intergovernmental Committee for Physical Education and Sport. His career includes roles at Durham University as Head of Sociology and Head of the School of Applied Social Sciences before joining Loughborough in 2011. Giulianotti earned his MA (First Class), MLitt, and PhD in Sociology from the University of Aberdeen, followed by academic posts there from 1990. He has been a visiting professor at institutions including Harvard, Seoul National University, and the University of Warsaw. His research focuses on sport sociology, globalization, soft power dynamics, and sport-for-development initiatives. Key themes include global sport mega-events’ societal impacts, refugee integration through sport, and alcohol consumption in football cultures. He critiques sport’s role in soft power strategies, notably analyzing Qatar’s World Cup 2022 and China’s international football policies. Giulianotti’s work spans 30+ years, producing over 150 peer-reviewed articles and books. Notable contributions include Global Sport (2018) and Routledge Handbook of Sport for Development and Peace (2018). His awards include Fellowship in the Academy of Social Sciences and Royal Society of Arts. Grants & Partnerships : Active in multi-institutional SDP projects, particularly in refugee integration and climate impact mitigation Advisory Roles : REF2021 sub-panel member (Sport Sciences), policy advisor for UNESCO and UK government He leads the UNESCO Chair’s initiatives promoting education through sport in marginalized communities, emphasizing sustainability and global equity. Current projects explore migrant coaches’ identity challenges and decarbonizing sport.

Jie Xiongمشاهده پروفایل

دانشیار

• Wireless Sensing
• Mobile Health
• Wireless Networking
• +۳ مورد دیگر

Jie Xiong is an Associate Professor at the University of Massachusetts Amherst, affiliated with the Department of Computer Science within the College of Information and Computer Sciences. He holds a PhD from University College London (2015) and has been a faculty member since 2018. His research focuses on wireless sensing, mobile health, and IoT, with notable contributions to sensor-free systems and long-range sensing. He leads the Center for Smart and Connected Society and has been recognized with awards like the SIGMOBILE Test-of-Time Award (2024) and MobiCom Best Paper Award (2024). Education: PhD in Computer Science, University College London (2015) Research Interests: His work spans wireless sensing (e.g., acoustic, RF, LoRa), mobile health monitoring, and IoT applications. He explores sensor-free techniques, long-range through-wall sensing, and leveraging ambient signals for novel applications. Grants & Awards: NSF CAREER Award NIH R01 Grant (Smart and Connected Health) Google European Doctoral Fellowship BCS Distinguished Dissertation Award (Runner-Up) MobiCom '22 Best Paper Award (Runner-Up) Advising & Students: Supervises PhD students including Minhao Cui, Yuda Feng, Binbin Xie, and Dong Li. His students have received accolades like the Google Ph.D. Fellowship (Binbin Xie, 2022). Labs & Teams: Leads research in the Center for Smart and Connected Society, focusing on wireless systems and health applications. Collaborates with industry and academia on projects like EVLeSen (in-vehicle sensing) and SoilCares (agricultural monitoring).

Michael Choiمشاهده پروفایل

استادیار

• Markov Chains
• Stochastic Algorithms
• Statistical Physics
• +۶ مورد دیگر

Michael Choi is an Assistant Professor in the Department of Statistics and Data Science at the National University of Singapore (NUS), affiliated with the Institute of Operations Research and Analytics (IORA). Previously, he held a joint appointment with Yale-NUS College (2022–2025) and worked at the School of Data Science (SDS) at the Chinese University of Hong Kong, Shenzhen. He earned his PhD from Cornell University’s School of Operations Research and Information Engineering (ORIE), advised by Prof. Pierre Patie, and holds an undergraduate degree in Actuarial Science from the University of Hong Kong. His research focuses on Markov chains and processes, stochastic algorithms (e.g., MCMC, simulated annealing, Langevin dynamics), and their applications in statistical physics, optimization, Bayesian statistics, information theory, game theory, and theoretical computer science. He explores interdisciplinary connections with quantum computation, control theory, and computational chemistry. Choi actively contributes to the academic community, serving as an Associate Editor of Statistics and Computing since August 2023. He has presented at numerous international conferences and workshops, including the IMS APRM 2026 (Hong Kong), INFORMS International Meeting 2025 (Singapore), and BayesComp 2025 (Singapore). His work bridges theoretical foundations with practical computational methods in stochastic systems.

• Materials Science
• Computational Chemistry
• Density Functional Theory
• +۳ مورد دیگر

Michael Herbst is an Assistant Professor (tenure-track) at EPFL, holding a joint appointment in the School of Basic Sciences (SB) and the School of Engineering (STI). He leads the Mathematics for Materials Modelling (MatMat) research group, focusing on error control in atomistic simulations, density-functional theory (DFT), and interdisciplinary computational methods. His work bridges mathematics, materials science, and computer science, emphasizing robust algorithms and Julia-based software development. Herbst holds a PhD from Heidelberg University and has held postdoctoral positions at RWTH Aachen and Inria Paris. He is a core member of the MARVEL and CESMIX research centers. Education: 2018: Dr. rer. nat. (magna cum laude), Heidelberg University 2009–2013: BA and MSci (1st class) in Natural Sciences, University of Cambridge 2008–2009: Studies in Mathematics/Physics, TU Kaiserslautern Research Interests : Herbst's research centers on developing reliable computational methods for materials modeling, including error estimation in DFT, black-box SCF algorithms, and Julia-based tools like the Density-Functional Toolkit (DFTK). His work addresses challenges in high-throughput simulations, numerical stability, and interdisciplinary collaboration across mathematics, physics, and computer science. Grants & Projects : MARVEL Center for Computational Design (EPFL) CESMIX Center for Extreme-Scale Simulations (MIT) EMC² Project (Sorbonne/Inria/École des Ponts) Awards : HGS MathComp PostDoc Fellowship (2018–2021) DAAD Travel Funding (2018) Exploratory Research Space Fund (RWTH Aachen, 2022) Labs & Teams : Head of the MatMat group at EPFL, focusing on error-controlled simulations and open-source software development.

Sarah Cartmellمشاهده پروفایل

استاد

• Biomaterials Engineering
• Tissue Engineering
• Regenerative Medicine
• +۳ مورد دیگر

Sarah Cartmell is a Professor of Bioengineering and Head of the Department of Materials at The University of Manchester. She holds senior roles in the School of Natural Sciences, including Senate membership and leadership in advanced materials initiatives like the Royce Institute. Her research focuses on biomaterials for regenerative medicine, including tendon repair, stem cell differentiation, and bioreactor design. Cartmell has secured over £34.7 million in grants, authored 70+ publications, and serves on editorial and review boards for journals like Science and Technology of Advanced Materials . Her work contributes to UN Sustainable Development Goals in health and innovation. Education : B.Eng (Materials Science with Clinical Engineering, University of Liverpool, 1996), Ph.D. (Clinical Engineering, University of Liverpool, 2000), Postdoc at GeorgiaTech, and academic roles at Keele University. Research Interests : Translation of novel tissue repair products, mechanical force effects on stem cells, and advanced biomaterials for bone and cartilage regeneration. Grants & Funding : £12.7M as lead PI and £22M as PI/Co-I across 22 sources (government, industry, charities). Awards : President of UK Tissue and Cell Engineering Society, IOM3 Fellow, and TERMIS EU council member. Leadership : Led the Royce Institute’s biomedical materials initiative, coordinating 200+ stakeholders, and chairs major international conferences in biomaterials and tissue engineering. Projects : Includes AMFaces (3D-printed facial prosthetics), biomaterials for regenerative medicine, and bioelectronics networks. Labs/Teams : Biomaterials Research Group, Manchester Bioelectronics Network, and advanced materials in medicine initiatives. Her research bridges clinical and industrial applications, emphasizing translational solutions for musculoskeletal disorders and regenerative therapies.

Aryan Kaushikمشاهده پروفایل

دانشیار

• Signal Processing
• 5G/6G Wireless Communications
• Integrated Sensing and Communications
• +۷ مورد دیگر

Dr. Aryan Kaushik is an Associate Professor at Manchester Metropolitan University (Manchester Met), UK, since 2024, affiliated with the Department of Computing and Mathematics. He also serves as Chief Advisor at RakFort, Ireland, since 2025. Previously, he was an Assistant Professor (senior grade) at the University of Sussex, UK, from 2021-24, and held roles as Recruitment and Admissions Tutor and Academic Advisor there. His academic journey includes a Research Fellow position at University College London (2020-21), and a PhD in Communications Engineering from the University of Edinburgh (2019). He holds an MSc in Telecommunications from the Hong Kong University of Science and Technology (2015). Education: PhD in Communications Engineering, University of Edinburgh (2019) MSc in Telecommunications, Hong Kong University of Science and Technology (2015) Professional Roles: Chair of IEEE ComSoc ETI on Electromagnetic Signal and Information Theory (since 2024) Core Member of IEEE P1955 Standard on 6G-Empowering Robotics Editorial roles across multiple IEEE journals and conferences His research focuses on 5G/6G wireless communications , integrated sensing and communications , reconfigurable holographic surfaces , non-terrestrial networks , and AI-driven network optimization . He has led UKRI-funded projects on topics like AI-assisted ISAC and Net Zero 6G, and collaborates globally with institutions like IIIT-Delhi, University of Bologna, and Imperial College London. Dr. Kaushik has received awards including the Top Editor Award 2025 (IEEE IoT Magazine), Best Editor Awards 2023-2024 (IEEE Open Journal), and was shortlisted for teaching excellence awards at Sussex. He actively contributes to standardization, serves on over 14 IEEE conference committees, and has delivered 110+ keynote/tutorial talks worldwide. His leadership extends to roles like TPC Co-Chair at IEEE ICC 2025 and Chair of Special Interest Groups on AI-driven Non-Terrestrial Networks and Fluid Antenna Systems.

Fow-Sen Choaمشاهده پروفایل

استاد

• Neural Engineering
• Photonics
• Quantum Technologies
• +۶ مورد دیگر

Dr. Fow-Sen Choa is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). His research focuses on neural engineering, photonics, and biomedical applications, including deep transcranial magnetic stimulation (TMS), EEG brain network analysis, and mid-infrared technologies for chemical sensing. He is a Fellow of the Optical Society of America and has over 250 referred publications. Education: Ph.D. (Electrical Engineering, SUNY Buffalo, 1988), M.S. (SUNY Buffalo, 1985), B.S. (National Taiwan University, 1980). His research interests include opto-electronics, quantum cascade lasers, photoacoustic sensing, and non-invasive neural modulation for treating neural disorders. He collaborates with institutions like the NIH, CBE department, and the University of Maryland, Baltimore (UMB). His lab develops semiconductor lasers and detectors, and he advises UMBC's IEEE student branch. Recent projects involve acoustic beam forming, real-time brainwave systems, and prosthetic robotics. Awards: Fellow of the Optical Society of America. Dr. Choa mentors undergraduate researchers, leading to awards such as the Undergraduate Research Awards for projects on standoff explosive detection and bio-electronic robotics. He co-founded UMBC's Bio Electronics and Bio Photonics laboratory course. Labs/Teams: MOCVD Lab, Mid-Infrared Technologies for Health and the Environment (MIRTHE) consortium.

Kursat Karaمشاهده پروفایل

استادیار

• Fluid Dynamics
• Aerodynamics
• Computational Fluid Dynamics (CFD)
• +۹ مورد دیگر

Kursat Kara is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at Oklahoma State University (OSU), leading the Kara Aerodynamics Research Laboratory. He holds a Ph.D. in Aerospace Engineering from Old Dominion University (2008), and has held academic positions including Assistant Professor at Khalifa University (2010–2018), where he received the President’s Faculty Excellence Award for Teaching (2015). His research focuses on fluid dynamics, computational aerodynamics, hypersonic flows, quantum computing, and flow separation control using techniques like CFD and miniPIV. He has advised numerous graduate and undergraduate students, and collaborates on projects such as hypersonic boundary-layer stability, quantum computing for fluid dynamics, and urban wind field modeling for UAS navigation. Dr. Kara’s expertise spans experimental and numerical fluid dynamics, including work on sweeping jet actuators, boundary-layer transition, and aerodynamic design optimization. He is a member of AIAA (Senior), APS, and ASME, and has contributed to facilities like the $3.5M Khalifa University Low-Speed Wind Tunnel. His teaching includes courses on computational fluid dynamics, quantum computing, and unsteady aerodynamics. Recent research highlights include applications of machine learning in wind field prediction and interdisciplinary projects like interface learning for multiphysics systems. Scientific achievements include publications on hypersonic flow stabilization, quantum solvers for Burgers’ equation, and reduced-order models for urban wind simulation. His lab engages students from high school to PhD levels, emphasizing project-based learning and computational tools. Key collaborations involve NASA, the DOD, and industry partners like Sikorsky Aircraft Corp.

Katerina Sotirakiمشاهده پروفایل

استادیار

• Theoretical Cryptography
• Post-Quantum Cryptography
• Complexity Theory
• +۴ مورد دیگر

Katerina Sotiraki is an Assistant Professor in the Department of Computer Science at Yale University, associated with the Archimedes AI research group. Her work focuses on theoretical cryptography, post-quantum cryptography, complexity theory, and secure computation. She holds a Ph.D. (2020) and M.S. (2016) in Computer Science from MIT, and a B.S. in Applied Mathematics (2013) from the National Technical University of Athens. Prior to Yale, she was a postdoc at UC Berkeley working with Raluca Ada Popa and Alessandro Chiesa, under the guidance of Vinod Vaikuntanathan at MIT. Research Interests : Design and analysis of cryptographic protocols resilient to quantum computing Efficient zero-knowledge proofs and succinct arguments Algorithmic game theory and fair division problems Lattice-based cryptography and post-quantum security Awards & Honors : Winner of 7th iDASH Competition (Track 3) - 2018 Chateaubriand Fellowship - 2018 Paris C. Kanellakis Fellowship (MIT EECS) - 2013 Key Contributions : Developed HOLMES - a system for secure collaborative learning Pioneered lattice-based succinct arguments with polylogarithmic verification Advanced understanding of modulo-p arguments through topological methods Labs & Teams : Active member of the Archimedes AI group at Yale, focusing on secure computation and cryptographic protocols.