Find Academic Supervisors

George T. HeinemanView profile

Associate Professor

• Software Engineering
• Component-Based Software Engineering
• Software Architecture
• +3 more

George T. Heineman is an Associate Professor of Computer Science at Worcester Polytechnic Institute (WPI). He holds a BS from Dartmouth College (1989), an MS (1990), and a PhD (1996) from Columbia University. His research focuses on software engineering, component-based systems, and modularity, with notable contributions to type-safe modular software evolution through the CoCo design pattern. Heineman emphasizes professional software engineering practices in teaching, challenging students with industry-relevant projects to foster best practices. His work has been published in leading venues like ECOOP, with a 2021 paper on CoCo gaining attention for its impact on Java language design. He received the WPI Trustees' Award for Outstanding Teaching in 2022, reflecting his dedication to education. His research spans algorithm design, system architecture, and cybersecurity, with publications ranging from foundational theory to practical applications in automated assessment and network security. Education: BS in Computer Science, Dartmouth College, 1989 MS in Computer Science, Columbia University, 1990 PhD in Computer Science, Columbia University, 1996 Research interests include software evolution, design patterns, and modular software systems. His recent work addresses challenges in maintaining stable APIs and enabling cohesive extensions in object-oriented systems. Collaborations with institutions like the University of Copenhagen and TU Dortmund highlight his international academic engagement. Beyond research, Heineman contributes to curriculum development, including WPI's new graduate programs in computing and workforce development initiatives.

Bruce JacobView profile

Professor

• Memory Systems
• Computer Architecture
• Memory Devices
• +7 more

Bruce Jacob is a Professor in the Cyber Science Department within the School of Engineering, Computing, and Weapons at the United States Naval Academy, where he joined in Fall 2022. Prior to USNA, he served as a professor of Electrical & Computer Engineering at the University of Maryland for 25 years, establishing himself as a leading expert in memory systems and computer architecture. Dr. Jacob received his A.B. in Mathematics from Harvard in 1988 and his Ph.D. in Computer Science & Engineering from The University of Michigan in 1997. Before graduate school, he worked in Boston start-ups as a software engineer at Boston Technology and later as chief engineer and system architect at Priority Call Management, which was successfully acquired in the late 1990s. His research focuses on memory systems, computer architecture, and memory devices, with significant contributions to memory system design across industry and government sectors. Jacob has designed computer-system architectures and memory-system architectures for major organizations including Micron (Hybrid Memory Cube DRAM architecture), Cray (Black Widow memory system), Northrop Grumman (experimental ultra-low-power datacenter), and the European Commission (1024-core Teraflux chip). His work spans resistive memory systems, non-volatile memory, memory simulation, and hardware security. His publication record demonstrates consistent leadership in memory systems research, with recent work focusing on ReRAM development, trusted execution environments for in-storage computing, and advanced memory simulation techniques. His research shows a clear trajectory toward monolithic memory integration, 3D stacking, and addressing the semantic gap between software and memory systems. Fellow of the IEEE Patent in memory-systems design Three patents in electric guitar circuit design Featured in Washington Post, Los Angeles Times, Chronicle of Higher Education, and NPR for guitar-related innovations Jacob has written two textbooks on computer memory systems and numerous articles spanning memory systems, computer design, embedded systems, operating system design, and even ventured into astrophysics and algorithmic composition. His DRAMsim memory simulator has become an industry standard tool. His practical industry experience complements his academic work, having consulted for major technology companies on memory system design challenges.

Djamel E. KhelladiView profile

Researcher

• Software Engineering
• Model-Driven Engineering
• Software Evolution
• +6 more

Djamel E. Khelladi is a CNRS researcher affiliated with the IRISA research lab and the DIVERSE team at University of Rennes 1 , France. Previously, he held postdoctoral and PhD positions at Johannes Kepler University (JKU) Linz, Austria, and Université Pierre et Marie Curie (UPMC), France. Research interests include: Model-Driven Engineering Software Evolution & Co-evolution AI and Generative AI Applications Polyglot Programming Digital Twins Recent article trends focus on integrating Large Language Models (LLMs) for code-metamodel co-evolution, polyglot programming challenges, incremental build optimization in configurable systems, and empirical studies on software evolution. His work often bridges theoretical modeling with practical implementation in industrial contexts. Academic service roles include: Proceedings Co-Chair @MODELS 2025 Co-Organizer of Models and Evolution (ME) workshops (2023-2025) Co-Editor for special issue on Model Driven Engineering for Digital Twins (SoSym 2024/25) PC member in top venues: ICSE , ASE , MODELS , ECMFA , MSR , FSE

• Computer Science
• Software Engineering
• Formal Methods
• +6 more

Thomas Henzinger is a Professor at the Institute of Science and Technology Austria (IST Austria) since 2009, serving as its President from 2009 to 2022. He holds honorary doctorates from Fourier University and Masaryk University. His research focuses on formal methods for improving software reliability in concurrent and embedded systems, with contributions to quantitative verification, quantum computing, and algorithmic fairness. He leads the Henzinger Group , which addresses challenges in software correctness, safety-critical systems, and AI ethics. Education: PhD from Stanford University (1991), followed by postdoctoral work at Université Joseph Fourier (1991). Research Interests: Concurrent and embedded systems, formal methods, quantum algorithms, fairness in AI, and runtime verification. His team develops mathematical foundations and tools to ensure software robustness in complex systems. Recent Trends in Publications: Focus on advancing formal verification techniques for neural networks, quantum computing, and ethical AI. Key contributions include fairness shields for decision systems and middleware for third-party monitoring (VAMOS). Awards: Royal Society Fellow (2024), US National Academy of Sciences Member (2020), Wittgenstein Award (2012), and numerous test-of-time awards. Advising & Grants: Advised over 20 PhD students. Secured ERC Advanced Grants (VAMOS, QUAREM) and FWF grants (Wittgenstein Award). Labs/Teams: Leads the Henzinger Group , collaborating on projects like SPyCoDe (semantic security) and VAMOS (third-party monitoring middleware).

David KargerView profile

Professor

• Algorithms
• Information Retrieval
• Human-Computer Interaction
• +3 more

David Karger is a Professor of Computer Science at MIT, affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds a B.A. from Harvard University and a Ph.D. from Stanford University. His research spans algorithms, information retrieval, human-computer interaction, and theory of computation. He leads the Haystack group, focusing on information management systems and collaborative tools. Notable contributions include the Scatter/Gather browsing system, the Mavo web application framework, and projects like Wikum and Squadbox for online collaboration and harassment prevention. Education: A.B. Summa cum Laude in Computer Science, Harvard University (1989) Ph.D. in Computer Science, Stanford University (1994) Research Interests: Karger’s work integrates algorithmic theory with practical systems, emphasizing human-centered design. Current projects address misinformation detection, social interaction systems, and educational tools. His research bridges theoretical computer science and applied domains such as web technologies and healthcare informatics. Awards: ACM Doctoral Dissertation Award (1994) Mathematical Programming Society Tucker Prize (1997) National Academy of Sciences Award for Initiative in Research (2004) Advising & Grants: Karger has advised over 30 students, many of whom have gone on to leadership roles in academia and industry. His work has been supported by grants from the MIT Schwarzman College of Computing and collaborations with companies like Akamai and Google. Labs & Teams: He leads the Haystack Group within CSAIL, collaborating with interdisciplinary teams on projects such as Mavo, Wikum, and Eyebrowse. His research also intersects with the Theory of Computation and Algorithms groups at MIT.

• Electronic Design Automation (EDA)
• Computer Architecture
• Embedded Systems
• +5 more

Prof. Wolfgang Ecker is a Professor at the Technical University of Munich (TUM), affiliated with the Chair of Design Automation within the TUM School of Computation, Information and Technology . His research focuses on Electronic Design Automation (EDA), RISC-V processor architectures, and hardware-software co-design. He leads projects advancing EDA tools for embedded systems, neural network acceleration, and formal verification methodologies. Ecker's work bridges machine learning techniques with traditional EDA challenges, addressing topics like energy-efficient AI inference and automated documentation generation. His contributions span compiler optimization, FPGA implementations, and fault analysis in digital systems. Recent research highlights include contributions to the TRISTAN project for RISC-V ecosystem development, model-driven architecture frameworks, and AI-driven timing analysis. He actively collaborates on open-source EDA tools and explores Rust-based embedded systems development. Ecker’s lab emphasizes practical applications in edge computing and automotive microcontroller safety, with a strong emphasis on interdisciplinary collaboration across TUM’s CIT School. His publications (15 most recent listed) reflect a focus on EDA tool innovation, processor design, and leveraging machine learning for hardware optimization. While no specific awards are mentioned, his involvement in ERC-funded projects and leadership in international collaborations underscores his academic impact.

Elisa BaniassadView profile

Teaching Professor

• Software Engineering
• Educational Technology
• Aspect-Oriented Programming
• +3 more

Elisa Baniassad is a Teaching Professor in the Department of Computer Science at the University of British Columbia (UBC), within the Faculty of Science. She specializes in software engineering education and has received numerous teaching accolades including the UBC Killam Teaching Prize and CS-Can/INFO-CAN Excellence in Teaching Award. Her courses focus on software construction, engineering principles, and advanced software design. Dr. Baniassad has taught CPSC 310 (Introduction to Software Engineering), CPSC 210 (Software Construction), and CPSC 410 (Advanced Software Engineering) across multiple terms since 2000. Her research interests span educational methodologies in software engineering, aspect-oriented programming, and the design of effective learning tools. Notable contributions include studies on team dynamics in software development, automated assessment techniques, and pedagogical frameworks for large-scale programming courses. She has authored over 50 peer-reviewed articles on topics ranging from mutation analysis in student tests to the efficacy of online learning environments. Awards include recognition for teaching excellence at UBC and contributions to computer science education. Her work emphasizes practical applications of software engineering principles in academic settings, with a focus on fostering student mastery through innovative assessment strategies and feedback mechanisms.

Jonathan SprinkleView profile

Professor

• Cyber-Physical Systems
• Autonomous Systems
• Traffic Control
• +3 more

Jonathan Sprinkle is Chair and Professor of Computer Science at Vanderbilt University's School of Engineering, with additional roles as Professor in Civil and Environmental Engineering and Electrical and Computer Engineering. Previously, he was Litton Industries John M. Leonis Distinguished Associate Professor at the University of Arizona and Interim Director of the Transportation Research Institute. His research focuses on model-based cyber-physical systems, autonomous systems, and traffic control, emphasizing industry impact. He holds a Ph.D., M.S., and B.S. in Electrical Engineering from Vanderbilt University and Tennessee Technological University. Key awards include the NSF CAREER Award (2013), UA Distinguished Scholar (2020), and NSF I-Corps Best Team (2012). His work spans traffic wave dissipation, autonomous vehicle safety, and large-scale field experiments like the CIRCLES consortium's 100-AV test. He leads initiatives in data-driven control systems and smart infrastructure through collaborations with NSF and industry. Research highlights include developing control barrier functions for automated vehicles, integrating LLMs for traffic analysis, and deploying ROS-based frameworks for vehicle communication. His contributions aim to bridge theoretical models with real-world applications, addressing challenges in energy efficiency, safety, and scalability.

Javad FattahiView profile

Assistant Professor

• Energy Equity and Inclusion
• Distributed Energy Resources (DER)
• Software-Defined Nanogrids
• +6 more

Dr. Javad Fattahi is an Assistant Professor at the School of Electrical Engineering and Computer Science, University of Ottawa. He holds roles as an IEEE Senior Member, Professional Engineer (P.Eng.), and member of the Standards Council of Canada. He leads the IEEE 2030.5 smart-grid interoperability verification initiative as its VP and chief editor. Dr. Fattahi earned his BSc in Electrical Engineering from Iran University of Science and Technology (IUT), followed by graduate studies at Sharif University of Technology (SUT). He completed his PhD and postdoctoral research at the University of Ottawa, specializing in energy systems and optimization. His research focuses on energy equity, distributed energy resources (DERs), software-defined nanogrids, game theory, smart mobility, and nonlinear systems. His recent work emphasizes data-driven digital twins for grid stability, V2G integration in residential complexes, and federated Byzantine agreement models for EV infrastructure. Key contributions include transactive energy systems under IEEE standards and energy disaggregation in institutional buildings. Dr. Fattahi has received accolades including IEEE Senior Membership and P.Eng. certification. His lab develops solutions for grid-edge technologies, smart mobility, and resilient energy systems. Graduate opportunities are available via his UniWeb page.

Natasha FernandesView profile

Senior Lecturer

• Data Privacy
• Differential Privacy
• Privacy-Preserving Machine Learning
• +3 more

Natasha Fernandes is a Senior Lecturer in the School of Computing at Macquarie University. She holds a PhD in Computing from Macquarie University and École Polytechnique (France), and an undergraduate degree in Pure Mathematics and Computer Science from the University of Sydney. Her roles include involvement in the Data Horizons Research Centre and Future Communications Research Centre, alongside professional casual appointments in academic computing. Her research focuses on the mathematical foundations of data privacy, particularly differential privacy and its applications in natural language processing and machine learning. She develops privacy-preserving systems and tools using quantitative information flow techniques rooted in information theory. Key areas include privacy analyses for financial systems (e.g., Open Banking), API privacy, and optimizing utility in privacy pipelines. Fernandes has led or contributed to five research projects, including work on privacy analyses for financial transaction protocols and UAV-based machine learning systems. She received the 2021 John Makpeace Bennett Award for her doctoral research on differential privacy in metric spaces. Her academic journey combines industry experience as a backend software engineer with rigorous academic contributions, spanning over 21 peer-reviewed publications and collaborations across cybersecurity and privacy engineering domains.

• Educational Technology
• Programming Tutoring Systems
• Game-Based Learning
• +1 more

Johan Jeuring is Professor of Software Technology for Learning and Teaching at Utrecht University's Department of Information and Computing Sciences. His research focuses on intelligent tutoring systems, computational thinking education, and game-based learning environments. Research Interests: Prof. Jeuring's work explores computational thinking pedagogy, automated feedback systems, and educational game design. His research bridges artificial intelligence with educational psychology to develop effective learning tools. Publications: Recent publications focus on augmented reality learning environments, programming education methodologies, automated assessment systems, and AI applications in education. His work combines empirical studies of learning behaviors with technological innovations in educational tools.

Elena TroubitsynaView profile

Professor

• Autonomous Systems
• Software Engineering
• Formal Verification
• +3 more

Elena Troubitsyna is a Professor of Computer Science with specialization in Software Engineering at KTH Royal Institute of Technology. Her research focuses on developing dependable, autonomous systems that ensure safety and reliability, particularly in complex environments like self-driving cars and drones. She employs rigorous mathematical modeling and verification techniques to address system complexity and real-time adaptability challenges. Her work emphasizes the co-engineering of safety and security in cyber-physical systems, integrating formal methods such as Event-B modeling with AI-driven solutions. Key research areas include cybersecurity for embedded systems, formal analysis of safety-security interactions, and resilient multi-agent systems. Elena has contributed to advancing methods for autonomous system navigation, fault tolerance, and privacy-preserving microservices architectures. Elena has organized international workshops like SENSEI (Safety-Security Interaction) and published extensively on topics such as model-driven engineering, formal verification of critical systems, and optimizing scheduling for distributed computing. Her research bridges theoretical foundations with practical applications, aiming to enhance societal trust in autonomous technologies.

• Scientific Computing
• Computational Fluid Dynamics
• Finite Element Methods
• +3 more

Johan Jansson is an Associate Professor in Scientific Computing at KTH Royal Institute of Technology and BCAM (Basque Center for Applied Mathematics). He leads research in predictive Direct FEM Simulation (DFS) for aerodynamics and multiphase flows, and co-founded Icarus Digital Math as CEO. His work includes the FEniCS open-source finite element software project and MOOC-HPFEM educational initiatives. He holds roles as Director of the Center for Digital Math and collaborates internationally in computational science. Research focuses on high-performance computing (HPC), fluid-structure interaction (FSI), biomedical modeling, and renewable energy systems. Notable contributions include adaptive FEM frameworks for turbulent flow, vocal fold simulations, and wave energy converter modeling. His work bridges academic research with industrial applications, leveraging FEniCS-HPC and Unicorn solvers. Key achievements include election to the IVA Royal Swedish Academy of Sciences 100-list and securing the Severo Ochoa Center of Excellence Award. He has pioneered open-source tools like SimTek and contributed to major projects like the Salter Sink and vocal production modeling. Teaching responsibilities include courses on database technology, computational fluid mechanics, and research methodology. He actively engages in large-scale simulation projects involving marine energy, cardiac ablation protocols, and aerodynamic optimization.

• Distributed/Parallel Computing
• Information Visualization
• Fault-Tolerant Communication Mechanisms
• +4 more

Philippas Tsigas is a Professor at the Department of Computer Science and Engineering at Chalmers University of Technology. He leads the Distributed Computing and Systems Research Group and has held roles as co-leader of research initiatives such as the PEPPHER project. His research spans distributed/parallel computing, information visualization, and fault-tolerant communication mechanisms. He has supervised numerous PhD students, including Yi Zhang, Håkan Sundell, and Farnaz Moradi. Research interests include lock-free data structures, multicore algorithms, secure network services, and visualization tools like Lydian and DataMeadow. Notable awards include Best Paper Awards at IPDPS 2003 and SNS 2012. His work has been published in top venues like IEEE Transactions on Parallel and Distributed Systems and ACM Journal of Experimental Algorithmics. Awards highlight contributions to lock-free algorithms and network modeling. Students have contributed to projects like NBmalloc (memory reclamation) and GPU Quicksort. Collaborations with institutions like SSF and VR have supported his research. Tsigas is also involved in teaching distributed systems and mentoring early-career researchers.

• Distributed Systems
• Cloud Computing
• Fault Tolerance
• +3 more

Rodrigo Miragaia Rodrigues is a full professor at the Instituto Superior Técnico (ULisboa) and a researcher at INESC-ID since 2015. He previously held roles as an associate professor at Universidade Nova de Lisboa, tenure-track faculty at MPI-SWS, and completed his PhD at MIT in 2005 under Barbara Liskov. Education: PhD in Computer Science, MIT, 2005 Research Interests: Focuses on distributed systems, fault-tolerant computing, cloud infrastructure, and consistency models. His work bridges theoretical foundations and practical implementations, addressing challenges in geo-replication, secure analytics, and resource allocation in serverless environments. He emphasizes scalable systems and resilient data management. Awards: Best Paper Award at SOSP ERC Starting Grant Google Faculty Research Award Advising & Grants: Has advised 7 PhD students as main advisor, with graduates in top institutions like Purdue, TU Munich, and USTC. Secured funding from the European Research Council (ERC) and Google, focusing on projects like DependableCloud (ERC Grant 307732). Labs & Teams: Leads research at INESC-ID and previously directed the Dependable Systems Group at MPI-SWS. Active in academic leadership roles, including President of the Scientific Council at IST.