Find Academic Supervisors

Frans KaashoekView profile

Professor

• Computer Security
• Operating Systems
• Distributed Systems
• +4 more

Frans Kaashoek is the Charles Piper Professor in MIT's Department of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). He leads the Parallel and Distributed Operating Systems (PDOS) group, focusing on secure systems, formal verification, and distributed computing. His work emphasizes crash-safe systems, concurrent programming, and cryptographic security. Education: PhD in Computer Science from Vrije Universiteit Amsterdam (1992), thesis on group communication in distributed systems under Andy Tanenbaum. Research interests include operating systems, networking, programming languages, and computer architecture. Notable projects: FSCQ (verified crash-safe file system), Perennial (framework for verifying concurrent systems), and Noria (high-performance web backend). Awards: ACM SIGOPS Mark Weiser Award (2001), ACM Prize in Computing (2010), National Academy of Engineering membership (2006), and American Academy of Arts and Sciences membership (2012). Publications: Over 150 papers on systems software, verification, and security. Authored textbooks like Principles of Computer System Design: An Introduction and xv6 commentary.

Jiong TangView profile

Professor

• System Dynamics
• Control
• Sensing and Automation
• +7 more

Jiong Tang is a Pratt & Whitney Chair Professor in Design and Manufacturing at the University of Connecticut , where he also serves as Co-Director of the Management and Engineering for Manufacturing Program . He received his B.S. and M.S. in Applied Mechanics from Fudan University, China (1989 and 1992), and his Ph.D. in Mechanical Engineering from Pennsylvania State University (2001). Prior to joining UConn, he worked at the GE Research Center as a research engineer. Research Interests : System dynamics, control theory, smart materials, vibration suppression, uncertainty propagation, computational intelligence, and multi-physics system modeling. Current Projects : Digital twin development for aerospace materials, physics-informed machine learning in manufacturing, adaptive metasurface design, and optimization of cooperative robotics. Methodological Focus : Combines Bayesian deep learning , Gaussian process metamodeling , transformer-based architectures , and multi-fidelity data fusion for industrial applications. His work emphasizes smart sensing , electromechanical integration , and uncertainty-robust inverse analysis . Collaboration : Research funded by federal agencies and industrial partners , with particular emphasis on aerospace and manufacturing technologies. His recent publications highlight generative adversarial networks for defect detection , piezoelectric metamaterials , and physics-guided neural network architectures across mechanical, structural, and composite systems.

Gregor SneltingView profile

Professor

• Programming Languages
• Compiler Construction
• Program Analysis
• +7 more

Gregor Snelting is a Professor and head of the Chair of Programming Paradigms at the Karlsruhe Institute of Technology (KIT), Faculty of Computer Science, Institute for Programming Languages and Compiler Construction. His research focuses on compiler construction, program analysis, software security, and verification. His primary research interests include programming languages, compiler design, program analysis, software security, information flow control, formal verification, object-oriented and concurrent programming, and software reengineering using concept analysis. His work aims to provide solid theoretical foundations and empirical validation. The research output, particularly the 15 most recent articles, shows a strong emphasis on software security and program analysis, with a focus on information flow control in Java using the JOANA tool. There is also a significant thread on invasive computing and resource-aware parallel programming. The work combines deep theoretical contributions, such as formal semantics and correctness proofs, with practical tool development and empirical validation. Faculty Teaching Award for the course 'Practice in Software Development' Snelting leads a research group that has developed several significant tools, including JOANA for security analysis, the Praktomat system for automated grading of programming assignments, and contributions to the libFirm compiler framework. His group is a key participant in major research initiatives like the DFG Collaborative Research Center InvasIC and the DFG Priority Program RS3. He advises students and supervises theses, fostering research in programming paradigms and software security. The group is involved in several key research projects: JOANA for information flow control in Java, InvasIC for invasive computing and dynamic parallelism, Quis-Custodiet for machine-checked correctness proofs of security analyses, and the development of the libFirm compiler framework.

Nima HonarmandView profile

Assistant Professor

• Computer Architecture
• Parallel Computing
• Operating Systems
• +3 more

Nima Honarmand is an Assistant Professor in the Department of Computer Science at Stony Brook University, where he co-directs the Computer Architecture Stony Brook (COMPAS) Lab . His research focuses on computer system design , particularly parallel computer architecture and operating systems . Education : Ph.D. in Computer Science from University of Illinois at Urbana-Champaign under Josep Torrellas. His work addresses challenges in deterministic replay of parallel programs to simplify debugging on multi-processor systems. Current research explores memory fencing, consistency models, and architectural extensions for reproducibility. Recent publications span conferences like ASPLOS, ISCA, PACT, and POPL, with emphasis on parallelism constraints , memory hierarchy optimization , and fault-tolerant systems . Awards include Best Paper at PACT 2011 and Best Paper Candidate at VTS 2007 . Teaching : Courses include Computer Architecture (CSE 502) and Operating Systems (CSE 306/CSE 506). Email : nhonarmand@cs.stonybrook.edu

Sebastian ForsterView profile

Professor

• Algorithms
• Graph Theory
• Network Science
• +4 more

Sebastian Forster is a Professor at the University of Salzburg , affiliated with the Faculty of Digital & Analytical Sciences and the Department of Computer Science . He leads the Big Data Algorithms Group and holds administrative roles as Vice Dean, Local Coordinator of CIVIS Hub 5, and coordinator of the supplementary study programme "Informatikkompetenz für alle." His research focuses on algorithms for big and fast data, particularly distributed and dynamic algorithms applied to graphs, networks, and complexity theory. Education: Ph.D. in Computer Science (University of Vienna, 2011–2015) M.Sc. in Computational Intelligence (Vienna University of Technology, 2008–2011) B.Sc. in Computer Science (University of Passau, 2005–2008) Research Agenda: Forster's work addresses the theoretical and mathematical challenges of prior-free algorithms in the post-Moore's Law era. His key contributions include advancements in graph algorithms , fine-grained complexity , and network science . Recent publications span distributed Laplacian methods , dynamic graph sparsifiers , and approximate shortest path solutions , reflecting a blend of algorithmic design and hardness analysis. Scientific Awards: Heinz Zemanek Award (OCG) Award of Excellence (BMWFW) Academic Service: He has served on program committees for ICALP 2025, STACS 2024, FOCS 2023 , and other major conferences. He actively reviews for journals like Journal of the ACM and funding bodies such as BSF and ISF . Co-organized the Dagstuhl Seminar 22461 on Dynamic Graph Algorithms.

Michael EichbergView profile

Professor

• Software Engineering
• Static Analysis
• Software Development Tools
• +3 more

Michael Eichberg is a Professor at Technische Universität Darmstadt, Germany, where his work centers on software engineering, static analysis, programming languages, and secure software development tools. He is the principal architect of the OPAL framework for Java bytecode analysis and has an extensive publication record spanning PLDI, ICSE, ESEC/FSE, ISSTA, ASE, FSE, SOAP, and other premier venues. Research Interests: Static program analysis and its scalability to real-world code bases Software security, particularly cryptographic API misuse and Android app repackaging detection Concurrent and parallel programming models, including deterministic concurrency in Scala Software architecture conformance, drift and erosion detection, and rule reuse Development of open extensible tools and frameworks (OPAL, LectureDoc, QScope, Sextant, XIRC, IRC) Publication Trends: His recent work (2015-2022) demonstrates a strong focus on empirical evaluation of static analysis techniques, modular composition of analyses, and security-related program understanding. Key themes include unsoundness in call graph construction, purity and immutability analyses, parallelization of static analyses, and large-scale studies of cryptographic API misuse. Tools & Frameworks: OPAL – A flexible Java bytecode analysis and manipulation framework (core developer until 2019) LectureDoc 2 – Web-based lecture material authoring and presentation system QScope – Open extensible metrics framework for modern software projects Sextant – Eclipse-integrated software exploration tool XIRC/IRC – Frameworks for enforcing system-wide properties and architectural constraints

Mary Elizabeth KurzView profile

Associate Professor

• Scheduling
• Metaheuristics
• Industrial Engineering
• +5 more

Mary Elizabeth Kurz is an Associate Professor in the Department of Industrial Engineering at Clemson University's College of Engineering, Computing and Applied Sciences. Her research focuses on scheduling optimization, metaheuristics, and assembly line balancing for complex manufacturing systems. Education: B.S., Systems Engineering, University of Arizona (1995) M.S., Systems Engineering, University of Arizona (1997) Ph.D., Systems and Industrial Engineering, University of Arizona (2001) Research interests include: Development of heuristics and metaheuristics for scheduling Assembly line balancing with ergonomic constraints Flexible flowline scheduling with sequence-dependent setups Application of genetic algorithms and particle swarm optimization Recent work trends show applications in opioid crisis modeling, photolithography scheduling, and automotive configuration management. She has presented at INFORMS and IISE conferences, with special emphasis on multi-objective optimization and real-world industrial constraints. Scientific awards: Third Place Best Paper, ASME Manufacturing Engineering Division (2014) As an INFORMS member and Institute of Industrial Engineers Senior member, she has taught courses in operations research, decision support systems, and metaheuristics. Her work spans both theoretical and applied domains, with a strong focus on manufacturing system efficiency.

• Artificial Intelligence and Data Science
• Data Management & Mining
• Machine Learning & Intelligence
• +3 more

ZHENG Baihua serves as Professor of Computer Science at Singapore Management University's School of Computing and Information Systems (SCIS), concurrently holding leadership roles as Associate Dean for SCIS Post-Graduate Research Programmes and Director of the Master of Science in Computing programme. Currently on leave but maintaining full-time faculty status, his academic career spans over two decades with foundational training from Hong Kong University of Science and Technology. Professor Zheng's research program integrates artificial intelligence, data science, and urban computing to solve critical challenges in mobility and sustainability. His expertise centers on trajectory data management, social network analysis, and spatio-temporal modeling, with significant contributions to trajectory compression algorithms, influence minimization in social networks, and real-time traffic prediction systems. His work bridges theoretical database innovations with practical applications in smart city infrastructure and public health interventions. Analysis of recent publications (2024-2025) reveals a dominant focus on physics-informed trajectory processing, GPU-accelerated indexing for high-dimensional data, and transformer-based models for urban mobility prediction. Key trends include the fusion of graph neural networks with spatio-temporal dynamics, novel approaches to contact tracing through timeline graphs, and differentiable search techniques for structured data discovery. These works consistently target real-world deployment in transportation systems and epidemic control. No scientific awards are documented in available institutional records. Information regarding student supervision, research grants, laboratory facilities, or collaborative teams remains unspecified in current public profiles.

Ningning XieView profile

Researcher

• Functional Programming
• Type Systems
• Logics
• +3 more

Ningning Xie is a researcher affiliated with the University of Toronto, specializing in functional programming, type systems, and logics. Their work spans applications in compilers, code generation, and machine learning, with a focus on compositional programming and effect handling. Research interests include: Functional programming Type systems Logics Compiler design Multi-stage programming Effect handlers Recent publications demonstrate expertise in type-level programming, staged compilation, and effect systems. Key areas include distributive disjoint polymorphism, parallel algebraic effect handlers, and macro systems for OCaml and Haskell. Their work bridges theoretical formalisms with practical language implementations. Contributions to academic service include organizing and reviewing for conferences like POPL, PLDI, ICFP, and Haskell workshops. Notable roles include Publicity Chair for POPL 2026 and Co-chair for PLMW and Artifact Evaluation committees.

• System-on-Chip (SoC) Design
• FPGA-Based High-Level Synthesis
• Real-Time Embedded Systems
• +5 more

Timo Hämäläinen is a Professor of Computer Engineering at Tampere University, leading the Unit of Computing Sciences within the Faculty of Information Technology and Communication Sciences. He is a core member of the System-on-Chip research group and the Computer Engineering Team, actively contributing to the System-on-Chip Hub initiative. His research focuses on System-on-Chip (SoC) design methodologies, FPGA-based high-level synthesis, real-time embedded systems, and open-source hardware-software co-design frameworks like RISC-V and HEVC encoding. He has pioneered work on agile SoC development processes and validation techniques for large-scale hardware systems. Key research areas include: High-level synthesis (HLS) optimization for FPGAs Real-time processor architectures and context-switching latency reduction Formal verification of IP-XACT-compliant SoC designs Resilient RISC-V MPSoC implementations Hardware-accelerated algorithms for signal processing and networking His recent publications (2023-2025) emphasize agile SoC development frameworks, hardware-software co-design for real-time systems, and validation methodologies for large-scale embedded systems. He has contributed to open-source projects like Kvazaar HEVC encoder and the Kactus2 IP-XACT toolchain. Academic advising includes students such as Santéri Mäki-Äijö (formal verification), Arto Oinonen (RISC-V tooling), and Sakari Lahti (processor modeling). His work integrates academic research with industrial collaboration through frameworks like the Fault-slip-Through quality assessment methodology.

Jürgen BrehmView profile

Adjunct Professor

• Computer Architecture
• Parallel Processing
• E-Learning
• +6 more

Jürgen Brehm is an Adjunct Professor at the Faculty of Electrical Engineering and Computer Science of Leibniz University Hannover . He holds a venia legendi in Computer Engineering after completing his habilitation in 2000. Education: Diploma in Computer Science (1986), Doctorate in Engineering (1991), Habilitation (2000) Research interests span computer architecture , parallel processing , performance analysis , and e-learning . His work explores ubiquitous computing , communication architectures , and optimization algorithms . Recent publications highlight trends in parallel computing , optimization , and interactive systems , including works on swarm intelligence , particle swarm optimization , and open content integration. Scientific award : Feodor Lynen Fellowship (1994) Teaching includes core courses like Basics of Computer Architecture , Operating Systems , and Parallel Processing . He also designed two multimedia-equipped computer science lecture halls and managed large-scale DFG projects for e-learning and HPC computing.

Luis-Miguel CHEVINView profile

Researcher

• Adaptive Evolution
• Phenotypic Plasticity
• Eco-evolutionary Dynamics
• +11 more

Luis-Miguel CHEVIN is a CNRS Research Director at the Centre d'Écologie Fonctionnelle et Évolutive (CEFE) in Montpellier, France, where he leads research in evolutionary and behavioral ecology, focusing on adaptation to changing environments. He is affiliated with the Genetics and Evolutionary Ecology group within the Department of Evolutionary and Behavioral Ecology. His work integrates theoretical modeling, experimental evolution using the microalga Dunaliella salina , and analysis of natural populations. His research interests include adaptive evolution, phenotypic plasticity, eco-evolutionary dynamics, evolutionary rescue, and the genetics of adaptation. He investigates how organisms adapt to fluctuating environments, combining quantitative genetics, population modeling, and empirical studies. His work spans molecular, physiological, and population levels, with a strong emphasis on predicting evolutionary responses under environmental change. The recent publications highlight a consistent focus on phenotypic plasticity, environmental predictability, experimental evolution, and the demographic consequences of adaptation. Themes include multi-level plasticity, programmed cell death in unicellular organisms, fluctuating selection, and genotype-phenotype mapping. His work increasingly integrates omics data with evolutionary theory. ERC Starting Grant (FluctEvol, 2016–2021) Newton International Fellow, Imperial College London (2009–2011) Selected by Faculty of 1000 (2010, 2013, 2016) He advises multiple postdoctoral researchers and students, and leads or participates in funded projects such as ComplexAdapt (2022–2024), InterAdapt (2021–2022), and previously ContempEvol (2011–2015) and EvolMarin (2015–2018). He is also the head of the French network GDR PlasPhen (2019–2023) and served as Associate Editor for Evolution (2016–2018). His lab combines theoretical and experimental approaches to study adaptation in real and simulated environments.

• Chemical Process Control
• Biodiesel Production
• Distillation Modeling
• +4 more

Adel Mhamdi is a Professor at RWTH Aachen University's Department of Chemical Engineering within the Faculty of Mechanical Engineering. His research focuses on process systems engineering with emphasis on nonlinear model predictive control, hybrid modeling, and sustainable process design for chemical and biochemical systems. He leads research in electrified biodiesel production, distillation optimization, and polymerization process control. His research interests span chemical process control, biodiesel production optimization, distillation modeling, hybrid mechanistic-data-driven approaches, polymerization processes, and heat transfer optimization. Mhamdi develops advanced control strategies including economic NMPC, distributed control architectures, and chance-constrained optimization to address challenges in flexible operation of energy-intensive processes. His work integrates computational fluid dynamics with process modeling for reactor design and optimization. Analysis of his recent publications reveals strong trends in electrification of chemical processes, particularly biodiesel production with heat integration. His research increasingly incorporates machine learning for hybrid modeling and employs advanced computational techniques like Bayesian optimization for reactor geometry design. Key application areas include renewable energy systems, polymer manufacturing, and separation processes. Mhamdi actively supervises doctoral researchers including M. El Wajeh, J.M. Faust, and P.J. Joy who appear as first authors on multiple publications. His research group collaborates extensively with the Mitsos group at RWTH Aachen, securing publications in top journals including Industrial & Engineering Chemistry Research and Computers & Chemical Engineering . Current projects focus on real-time optimization of electrified processes and development of open-source modeling platforms like HybridML.

Fritz HengleinView profile

Professor

• Programming Languages
• Functional Programming
• Domain-Specific Languages (DSLs)
• +6 more

Fritz Henglein is a Professor at the Department of Computer Science, University of Copenhagen (DIKU), with affiliations also at Deon Digital. His career spans over three decades, with notable roles including Head of the Algorithms and Programming Languages (TOPPS) research group and Director of the HIPERFIT research center. Research interests include Programming languages and type systems Functional programming and DSLs High-performance computing Contracts and distributed ledger technology Algorithmic logic and formal semantics His work often bridges theoretical rigor with practical applications, particularly in financial information technology and compiler design. Collaborations include leadership in conferences like POPL, ICFP, and PEPM, with a focus on mentoring through academic events and community-building initiatives.

• Computer Science Education
• Parallel Programming
• System Software
• +3 more

Celina Berg is an Associate Teaching Professor in the Department of Computer Science at the University of Victoria, affiliated with the Faculty of Engineering and Computer Science. She also serves as Outreach, Recruitment, and Retention Coordinator, focusing on enhancing student engagement and diversity in computer science education. Her research interests span parallel programming, system software design, aspect-oriented programming, and educational tool development. Dr. Berg’s work emphasizes bridging gaps between theoretical concepts and practical implementation, particularly in improving accessibility to complex computer science topics for undergraduate students. She has contributed to frameworks such as Ice for binary analysis, eMOTE for online collaboration, and visualization tools like HiLPR for pattern representation. Her publications (2004–2011) explore concurrency solutions, abstraction layers, and educational innovations. Notable areas include parallel pattern languages, virtual machine architecture, and automation strategies in system design. While no specific awards are listed, her contributions to teaching and infrastructure software reflect impactful academic engagement. In outreach, she coordinates initiatives like SPARCS (Supporting Sustainable and Integrated Outreach Activities) to inspire young minds in STEM fields. Her advising and grant activities are not explicitly detailed in available records.