Find Academic Supervisors

Jeffrey S. ChaseView profile

Professor

• Distributed Systems
• Operating Systems
• Cloud Computing
• +7 more

Jeffrey S. Chase is a Professor of Computer Science at Duke University in the Department of Computer Science within Trinity College of Arts & Sciences. He has held this position since 2006 and currently serves as Director of Graduate Studies. His academic career spans decades with significant contributions to distributed systems research. Chase's research focuses on operating systems and distributed systems, with particular emphasis on cloud infrastructure services, trust management and security in cloud environments, energy-aware computing, and network storage. His work has evolved to center on integrity and trust: where it comes from, how we represent it, how we reason about it in software, and how we build software systems worthy of trust. His research group has developed notable systems including ExoGENI, Silver, and ADAMANT. His recent publications demonstrate his continued focus on secure data sharing architectures, networking for multi-tenant data centers, and federated authorization systems. These works collectively address fundamental challenges in distributed computing related to security, privacy, and network performance in cloud environments. Chase has received significant research funding including the CC*Data: ImPACT project (2017-2022), Collaborative Research: CICI: Secure and Resilient Architecture (2016-2020), and TWC: Frontier: Collaborative: Rethinking Security in the Era of Cloud Computing (2013-2019). He has taught advanced courses including CPS 512: Advanced Distributed Systems, CPS 310: Operating Systems, and CPS 510: Advanced Operating Systems. His teaching philosophy emphasizes deep understanding of core distributed systems concepts with practical applications to modern cloud infrastructure.

• Embedded Systems
• Hardware-Software Co-Design
• Invasive Computing
• +7 more

Prof. Dr.-Ing. Jürgen Teich is a full Professor and Chair for Hardware-Software Co-Design at the Department of Computer Science, Friedrich Alexander University Erlangen-Nuremberg (FAU). He serves as Head of Department Computer Science and Vice Dean of the Technical Faculty since August 2024, and has been Speaker of the FAU Research Center Embedded System Initiative (FAU ESI) since 2023. His educational background includes: Diploma degree in Electrical Engineering, University of Kaiserslautern (1989) Dr.-Ing. degree in Electrical Engineering, University of Saarland (1993) Habilitation (PD Dr.-Ing.) entitled "Synthesis and Optimization of Digital Hardware/Software Systems" (1996) Prof. Teich's research focuses on Embedded Systems , Invasive Computing , Hardware-Software Co-Design , and Reconfigurable Computing . His work spans from theoretical foundations to practical implementations, with particular emphasis on resource-constrained systems, many-core architectures, and energy-efficient computing. He has pioneered research in invasive computing paradigms that enable more efficient use of many-core processors by allowing applications to dynamically claim resources. His recent publications reveal a strong trend toward energy-efficient AI deployment on embedded devices , security of embedded systems , and novel memory technologies . There's a clear focus on practical implementations of machine learning on microcontrollers (TinyML), hardware acceleration for data processing, and innovative approaches to power management in self-powered systems. Among his notable scientific awards are: IEEE Fellow (since 2018) Member of Academia Europaea, Section Informatics (since 2011) Member of the National Academy of Science and Engineering (acatech) (since 2018) Member of the German Society of Humboldtians (since 2021) Prof. Teich has been Principal Investigator for numerous DFG-funded projects including SFB/Transregio 89 "Invasive Computing" (2010-2022), SFB 694, and multiple priority programs. He has coordinated large collaborative research efforts across Germany and internationally, with significant funding from DFG and other sources. His research group has produced influential work in embedded systems design and co-design methodologies. He leads the Hardware-Software Co-Design research group at FAU, which focuses on innovative approaches to embedded system design, invasive computing architectures, and efficient implementation of machine learning on resource-constrained devices. The group maintains strong collaborations with industry partners including Intel, Xilinx, and automotive companies.

Mohamed El MoursiView profile

Professor

• Renewable Energy Integration
• Energy Storage Systems
• Smart Grid Operation and Control
• +6 more

Prof. Mohamed El Moursi is a Professor in the Electrical Engineering Department at Khalifa University, Abu Dhabi, UAE. He serves as Director of the Advanced Power and Energy Center (APEC) and Theme Director for renewable energy Integration at the Virtual Research Institute (VRI) for Sustainable Energy Production, Storage, and Utilization (funded by ASPIRE). An IEEE Fellow (Class of 2024) and Distinguished Lecturer of IEEE Power and Energy Society, he holds leadership roles in UAE's scientific community including membership in the MOHAMED BIN RASHID Scientists Council. His academic credentials include: BSc in Electrical Power Engineering from Mansoura University, Egypt (1997) MSc in Electrical Power Engineering from Mansoura University, Egypt (2002) PhD in Electrical Engineering (Power Systems/Power Electronics) from University of New Brunswick, Canada (2005) El Moursi's research pioneers renewable energy integration in modern power systems, focusing on hybrid AC/DC grid stability, AI-driven grid management, and transportation electrification. His work bridges theoretical innovation with industrial applications, particularly in grid stability assessment for high-renewable penetration systems. Key contributions include developing operational platforms like the SAVE software for UAE's national grid and REMS tools for international energy management. He has secured $27,027,129 in research funding from global sources including Europe, North America, GCC nations, and South Korea. Major projects encompass the ASPIRE-funded Virtual Research Institute, TRANSCO/Manitoba Hydro's SAVE Tool, and MIT-collaborative initiatives on grid resilience. To date, he has graduated 10 PhD and 35 MSc students, many receiving national thesis awards. His distinguished recognition includes: IEEE Fellow (2024) Khalifa Award for Education (2022) UAE Ministry of Energy R&D Award (2023) Mission Innovation Champion (2019) Abu Dhabi Technology Development Committee Gold Medal (2015) Multiple editorial awards from IEEE Transactions As APEC Director, El Moursi leads a multidisciplinary team developing cutting-edge solutions for grid modernization. His center maintains strategic partnerships with TRANSCO, ELIA GRID International, and Dubai Electricity and Water Authority, translating research into real-world grid stability and energy management systems through tools like SAVE and REMS.

• Digital Circuits
• Digital Signal Processing
• Machine Learning
• +10 more

Maurizio Martina is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino. He is a member of the Interdepartmental Center PEIC - Power Electronics Innovation Center and serves as an Associate Editor for the IEEE Transactions on Circuits and Systems I (2018-2023). His research focuses include: Digital circuits and signal processing Machine learning hardware architectures RISC-V extensions and post-quantum cryptography VLSI design for edge computing and IoT Recent publications emphasize cryptographic hardware implementations (CHIMERA, Keccak co-processors), RISC-V integration methodologies, and privacy-preserving neural network frameworks. His work spans VLSI architectures for video processing, bio-inspired electronics, and error correcting codes, with applications in cybersecurity, robotics, and biomedical systems. Scientific Recognition : Premio Nazionale Innovazione (2013) Premio dei Premi (2014) He supervises 12 PhD students across cycles 35-40 in Electrical, Electronics and Communications Engineering, including: Valeria Piscopo (2024-in progress) Alessandra Dolmeta (2022-in progress) Luigi Giuffrida (2022-in progress) Walid Walid (2019-2023) As part of the VLSILAB Group , his research explores hardware accelerators for machine learning, post-quantum cryptography on RISC-V, and bio-inspired embedded systems. Teaching activities include courses on Integrated Systems Architecture and Hardware & Wireless Security at Politecnico di Torino and Università di Pavia.

George C TsengView profile

Professor

• Genomics
• Bioinformatics
• Statistical Learning
• +9 more

Dr. George C Tseng serves as Professor and Vice Chair for Research in the Department of Biostatistics at the University of Pittsburgh School of Public Health, with secondary appointments in Human Genetics and Computational and Systems Biology. His educational background includes a BS (1997) and MS (1999) in Mathematics from National Taiwan University and an ScD (2003) in Biostatistics from Harvard School of Public Health. Dr. Tseng's research focuses on developing statistical methodologies for genomic and bioinformatic applications to advance precision medicine. His work spans multiple high-impact areas including multi-omics data integration, machine learning for high-dimensional data, cluster analysis for disease subtyping, and statistical methods for experimental design in omics studies. His approach emphasizes close collaboration with biological and clinical researchers to ensure methodological relevance to real-world problems. His publication record demonstrates consistent contributions to top statistical and bioinformatics journals, with recent work focusing on congruence analysis between animal models and humans, outcome-guided clustering methods, and high-dimensional causal mediation analysis. Elected Fellow, American Statistical Association (2017) Statistician of the Year, ASA Pittsburgh Chapter (2017) Provost's Award for Excellence in PhD Mentoring, University of Pittsburgh (2019) Clinical Research Scholar (K12) Award, NIH (2007-2009) Elected Member, International Statistical Institute (2012) Dr. Tseng has successfully mentored over 25 PhD students who have secured positions in academia, industry, and government agencies. His laboratory has maintained continuous NIH funding as principal investigator since 2012, including current grants R01CA285337 (2025-2030) and R01LM014142 (2023-2026). The Tseng Lab operates as a collaborative research environment focused on translating statistical innovations into practical solutions for biological and medical challenges, with strong connections to multiple research centers and clinical departments at the University of Pittsburgh.

Quan Quan TanView profile

Research Fellow

• Cryptography
• Symmetric-key Cryptanalysis
• Automated Cryptanalysis
• +2 more

Quan Quan Tan is a Research Fellow at Nanyang Technological University (NTU), Singapore, specializing in symmetric-key cryptanalysis and automation tools. He previously served as a Cybersecurity Engineer at CSIT, Singapore for nearly two years. His educational background includes: Ph.D. in Mathematical Sciences from NTU (2023) under Prof. Thomas Peyrin. Thesis: "Cryptanalysis of Lightweight Symmetric-Key Cryptographic Algorithms" M.Sc. in Mathematical Sciences from NTU, with research on optimization techniques for block cipher hardware implementations B.Sc. in Mathematical Sciences from NTU Dr. Tan's research focuses on automation in cryptographic design and analysis, emphasizing secure symmetric-key primitives and advanced cryptanalysis tools. His work bridges theoretical cryptography with practical security engineering through algorithm development and vulnerability assessment. Analysis of his 2020-2025 publications reveals dominant themes in symmetric-key cryptanalysis, including innovative meet-in-the-middle attacks, differential cryptanalysis frameworks, and automated verification systems. His contributions span attack methodologies (e.g., higher-order differential-linear techniques), tool development (Trail-Estimator), and novel cipher design (uKNIT-BC), demonstrating consistent advancement in lightweight and low-latency cryptographic systems.

Christopher RycroftView profile

Professor

• Mathematical Modeling
• Scientific Computation
• Numerical Methods
• +5 more

Christopher Rycroft is a Professor and Associate Chair in the Department of Mathematics at the University of Wisconsin–Madison. He leads the Rycroft Group, which focuses on mathematical modeling and scientific computation for interdisciplinary applications in science and engineering. Prior to joining UW-Madison in summer 2022, he was a professor at Harvard University's School of Engineering and Applied Sciences from 2014-2022, and before that a Morrey Assistant Professor at UC Berkeley from 2010-2013. Professor Rycroft's research spans three main areas: numerical methods for material mechanics, data-driven discovery, and computational geometry. His group develops new computational methods while working directly with domain scientists. Key achievements include the development of the reference map technique for fluid-structure interaction, Voro++ software library for Voronoi tessellation, and novel approaches to understanding crumpling physics. His work combines traditional analysis and modeling with machine learning methods to extract scientific insights from complex data. The Rycroft Group's publication record demonstrates a strong trajectory of interdisciplinary research bridging mathematics, physics, materials science, and biology. Recent work has focused on fluid-structure interaction, computational geometry applications, mechanical metamaterials, and biological fluid dynamics. The group develops both theoretical frameworks and practical software tools that have found applications across diverse scientific domains from materials science to virology. Everett Mendelsohn Award for Excellence in Mentorship (2021) Professor Rycroft has advised numerous PhD and master's students who have gone on to postdoctoral positions at institutions including MIT, EPFL, and Cornell. His teaching includes advanced scientific computing courses that have quadrupled in enrollment during his tenure. He has secured research funding supporting his group's work on computational methods and interdisciplinary applications. The Rycroft Group consists of graduate students, postdocs, and collaborators with diverse backgrounds in applied mathematics, physics, engineering, and computer science. The group maintains active collaborations with researchers across multiple institutions and participates in centers such as the Harvard Quantitative Biology Initiative.

Dominique DevrieseView profile

Professor

• Functional Programming
• Object Capabilities
• Secure Compilation
• +5 more

Dominique Devriese is a professor at the Department of Computer Science, KU Leuven, and a member of the DistriNet research group. His work bridges computer security, programming languages, and formal verification. Research interests: Functional Programming, Object Capabilities, Secure Compilation, Dependently-typed Programming, Modal Type Theory Teaching: Formal Systems, Object-Oriented Programming, CyberSecurity, Secure Software His research focuses on rigorous software systems security through capability machines and secure compilation techniques. He actively contributes to formal verification using Agda and Haskell, with recent work on multimode type theory and effect parametricity. Key publication trends include: multimode/presheaf type theory, capability-based security models, formal verification of hardware/software abstractions, and parametricity applications in programming languages. Contact: Email: dominique.devriese@kuleuven.be ORCID: 0000-0002-3862-6856

Flavio EspositoView profile

Associate Professor

• Cyber-physical Systems
• Networked Systems
• Network Virtualization
• +5 more

Flavio Esposito is an Associate Professor in the Computer Science Department at Saint Louis University's School of Engineering. He also serves as a Research Institute Fellow and CS Graduate Coordinator. His office is located in ISE 234D at 3450 Lindell Blvd, St. Louis, MO. Dr. Esposito's research focuses on cyber-physical systems and networked systems, including network virtualization, network management, Software-Defined Networks (SDN), network architectures, and wireless networks. He has a strong interest in interdisciplinary applications of these technologies to medicine and agriculture. His work bridges theoretical networking concepts with practical implementations. His publications span key areas in networking research, with recent work focusing on congestion control algorithms, virtual network embedding, recursive network architectures, and edge computing applications. The research trends show a progression from foundational networking protocols toward more sophisticated applications integrating machine learning, edge computing, and cyber-physical systems, with increasing emphasis on real-world applications in diverse domains. Outstanding Graduate Mentoring Faculty Award from the School of Engineering (2021) Finalist for the Undergraduate Mentoring Award in the College of Arts and Sciences Multiple NSF research awards including US Ignite, ICE-T, CNS Core, CC* Integration, CPS:TTP, and ModernCARE projects COMCAST Innovation Fund Award (January 2020) International Center for Responsible Gaming (ICRG) Award ($150K) Dr. Esposito actively mentors PhD and MS students, with numerous current and past students who have gone on to positions at major tech companies, universities, and research institutions. He has been a Principal Investigator on multiple significant research grants totaling millions of dollars. He co-founded Spaghetti Code Labs with former PhD student Alessandro Sangiorgi, whose cybersecurity educational app WeeNet has achieved 5.7M+ downloads. He leads several research labs and teams focused on cyber-physical systems, with current openings for PhD students, visiting researchers, and postdocs working on networks, learning, edge computing, and applications to medicine and agriculture. His teams have developed numerous software systems including Software Mutant, Neighborhood Method Prototype, VINEA, ProtoRINA, and BUtorrent.

Bernhard von StengelView profile

Professor

• Game Theory
• Algorithmic Game Theory
• Computational Complexity
• +2 more

Bernhard von Stengel is a Professor of Mathematics at the Department of Mathematics, London School of Economics and Political Science . His work bridges game theory, computational complexity , and mathematical economics , with a focus on equilibrium computation and algorithmic aspects. Developed Game Theory Explorer , open-source software for analyzing strategic and extensive-form games. Organized major workshops like What is Strategic Information? (2024) and Game Theory and Machine Learning (2023). Authored the textbook Game Theory Basics (Cambridge University Press, 2021). His research spans zero-sum games , correlated equilibrium , inspection games , and communication over noisy channels . Recent work includes characterizing the Condorcet dimension of metric spaces (2024) and stable-set bounds for Nash equilibria in bimatrix games. He has collaborated with institutions like the Game Theory Society and contributed to public discourse via talks on algorithms' societal impact (2021) and game theory in politics (2020).

• Regulation of Emerging Technologies
• Governance of Responsible Innovation
• Cybersecurity
• +7 more

Irina Brass is a Professor of Science, Technology and Regulation at University College London’s Department of Science, Technology, Engineering and Public Policy (STEaPP). Her research focuses on anticipatory and adaptive regulatory frameworks for emerging technologies, particularly IoT, AI, and advanced biotherapeutics. She leads projects like the REG-MEDTECH initiative and collaborates with government agencies, standards bodies, and interdisciplinary teams. Current Role: Professor at UCL STEaPP Leadership: Chair of BSI’s IoT/1 Technical Committee (2017-2021), member of Standards Policy and Strategy Committee (2020–) Her research spans: Regulation of connected medical devices and cybersecurity Governance of AI and algorithmic systems Standardization challenges for IoT and biotherapeutics Adaptive policy frameworks for disruptive technologies She leads the MPA in Digital Technologies and Policy and teaches courses on digital technology dilemmas and risk governance. Her accolades include the BSI Standards-Makers Award (2019) and UCL Provost’s Education Award (2020) .

Yanan GuoView profile

Assistant Professor

• Computer Architecture
• Cybersecurity
• GPU Computing
• +4 more

Yanan Guo is an Assistant Professor in the Department of Computer Science at the University of Rochester, specializing in computer architecture and cybersecurity. Her research focuses on GPU memory safety, side-channel attacks, quantum computing, and machine learning security, with recent projects exploring cross-VM side-channel vulnerabilities and quantum circuit simulation. PhD, University of Pittsburgh (advisor: Dr. Jun Yang) Her work bridges hardware and software security, addressing issues like GPU cache eviction mechanisms, memory corruption attacks, and adversarial threats in neural networks. She actively collaborates with researchers like Youtao Zhang and Jun Yang, with publications in top venues including USENIX Security, MICRO, and ICML. Recent publications highlight trends in GPU security (memory safety, side-channel attacks), quantum computing optimizations, and adversarial machine learning. Her team’s projects have received recognition such as the NSF OAC grant for AI workflow security and features in IEEE Transactions on Computers. Featured Paper in IEEE Transactions on Computers (02/22 issue) Shortlisted for Top Picks in Hardware and Embedded Security 2023 Dr. Guo mentors PhD students and offers weekly office hours for undergraduates, emphasizing career paths, graduate applications, and research guidance. She serves on program committees for conferences like USENIX Security and ASPLOS.

Angshuman KarmakarView profile

Assistant Professor

• Post-Quantum Cryptography
• Computation On Encrypted Data
• Side-Channel Analysis
• +4 more

Angshuman Karmakar is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur, India. His research focuses primarily on Post-Quantum Cryptography (PQC) and Computation On Encrypted Data (COED), which are critical areas in modern cryptography and computer security. Dr. Karmakar received his Ph.D. from Katholieke Universiteit Leuven (KU Leuven), Belgium, where he worked under Prof. Ingrid Verbauwhede in the COSIC research group. He was awarded the prestigious Erasmus Mundus fellowship for his doctoral studies and the FWO (Fonds voor Wetenschappelijk Onderzoek – Vlaanderen) fellowship for his post-doctoral research at KU Leuven. His research spans theoretical development of cryptographic schemes, implementation algorithms, side-channel and fault attack analysis, and countermeasure development. Dr. Karmakar has established extensive international collaborations with researchers and engineers worldwide to address complex challenges in cryptography and security. Recent publications demonstrate a strong focus on practical post-quantum cryptographic implementations with particular attention to hardware and software efficiency, side-channel resistance, and novel attack methodologies. His work bridges theoretical cryptography with real-world implementation challenges across diverse platforms from IoT devices to high-performance computing systems. Erasmus Mundus fellowship for doctoral studies at KU Leuven FWO fellowship for post-doctoral study at KU Leuven Google India Research Award for work on practical transition to post-quantum cryptography Dr. Karmakar is actively seeking graduate students and postdoctoral researchers to collaborate on cutting-edge research in cryptography and computer security. His work has significant implications for securing future communication systems against quantum computing threats, with applications spanning blockchain technologies, IoT security, and general-purpose computing systems.

Amir BahadoriView profile

Professor

• Radiation Protection
• Radiation Transport
• Radiation Dosimetry
• +5 more

Amir Bahadori serves as Professor and Nuclear Engineering Program Director in the Department of Mechanical and Nuclear Engineering at Kansas State University's Carl R. Ice College of Engineering, holding the Hal and Mary Siegele Professorship in Engineering. He directs the Radiological Engineering Analysis Laboratory (REAL) and established the Institute for Radiation Health Studies (IRHS) in 2024, focusing on radiation protection, space radiation environments, and radiation health effects. His educational background includes: Ph.D. in Biomedical Engineering, University of Florida (2012) M.S. in Nuclear Engineering Sciences, University of Florida (2010) B.S. in Mechanical Engineering and Mathematics, Kansas State University (2008) Bahadori's research spans radiation transport modeling, dosimetry, and risk assessment with applications in space exploration, medical physics, and radiation epidemiology. He develops computational frameworks for radiation exposure scenarios and biological response prediction, emphasizing space radiation protection for Artemis missions and chronic exposure studies through the Million Person Study collaboration. Analysis of his recent publications reveals dominant themes in space radiation measurement (Artemis missions), radiation epidemiology (Million Person Study innovations), and advanced detection systems (miniaturized neutron spectrometers). His work increasingly integrates big data approaches for radiation risk assessment and electrostatic shielding concepts for deep-space exploration. His scientific recognition includes: NASA Graduate Student Research Fellowship (2009) Certified Health Physicist designation Big 12 faculty fellowship (2022-2023) NCRP council election (2024) Two USPTO patents Bahadori secures substantial research funding from NASA for space radiation instrumentation, Department of Energy projects via the Kansas City National Security Campus, and collaborative epidemiological studies. He mentors nuclear engineering graduate students while leading interdisciplinary teams developing radiation protection solutions for aerospace and medical applications. His laboratory infrastructure includes the REAL with Beocat high-performance computing resources, radiation detectors, and a 3D printer, plus the IRHS with a Precision X-ray XRad320 irradiator and radon chamber. These facilities support collaborations across K-State colleges and external organizations for radiation health effect studies.

• Business Process Management
• Process Mining
• Complex Event Processing
• +5 more

Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data