Find Academic Supervisors

Lionel SeinturierView profile

Professor

• Distributed Systems
• Middleware
• Self-Adaptive Software Systems
• +4 more

Lionel Seinturier is a Professor at the University of Lille, Faculty of Science and Technology, Department of Computer Science. He serves as the Leader of the Spirals research group, a joint project-team between Inria (French National Institute for Research in Digital Science and Technology) and the University of Lille. His academic work bridges theoretical research with practical applications in software engineering and distributed systems. His primary research interests include: Distributed Systems and Middleware Self-Adaptive Software Systems Cloud Computing and Energy Efficiency Aspect-Oriented Programming Software Testing and Maintenance Web Application Understanding Seinturier's publication record spans over two decades, with recent work (2023-2025) focusing on energy efficiency in cloud infrastructures, web page matching algorithms, and automated repair of web automation scripts. His research trajectory shows evolution from foundational work in aspect-oriented programming and middleware to contemporary challenges in sustainable computing and intelligent software systems. A notable pattern is his consistent development of practical tools and frameworks that address real-world software engineering problems. He has supervised numerous PhD students whose research aligns with his expertise: Guillaume Fieni (2022): Energy efficiency of virtualized computing infrastructures Sacha Brisset (2022): Understanding web applications through automatic inference Thomas Durieux (2018): Runtime failure analysis and patch generation Maxime Colmant (2016): Energy consumption analysis in multicore architectures Bo Zhang (2016): Resource optimization in cloud computing infrastructure Seinturier maintains active involvement in the international software engineering community, serving on program committees for major conferences including ECSA (2022-2025), ICSOC (2016-2025), and ICWS (2023-2025). His educational contributions include teaching graduate courses on distributed application design and advanced distributed systems at the University of Lille, as well as participation in a MOOC on Java EE and Spring development. His technical contributions include several significant software frameworks: FraSCAti: A reconfigurable service-oriented middleware platform Juliac: A framework for generating component execution kernels AOKell: An aspect-oriented implementation of the Fractal component model JAC: A framework for dynamic aspect-oriented programming

Rodolfo PellizzoniView profile

Professor

• Real-Time Systems
• Embedded Systems
• Computer Architecture
• +3 more

Rodolfo Pellizzoni is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. His research focuses on real-time systems, embedded systems, and computer architecture, with an emphasis on time-predictable computing, multicore systems, and FPGA networks. He has contributed extensively to cache management, memory resource coordination, and security-aware scheduling in critical systems. His work includes designing frameworks like HopliteRT for FPGA NoCs, optimizing memory bandwidth regulation, and addressing challenges in mixed-criticality systems. Pellizzoni is affiliated with the Faculty of Engineering and maintains a research group focused on hardware-software co-design for real-time applications. His research bridges theoretical models (e.g., Network Calculus) with practical implementations, emphasizing latency reduction and resource predictability in heterogeneous platforms. Recent publications highlight advancements in cache partitioning, dynamic memory allocation, and scheduling algorithms for multicore processors. His work often appears in top-tier conferences like Euromicro Conference on Real-Time Systems (ECRTS) and journals focusing on embedded and real-time systems.

Loïc LagadecView profile

Professor

• CAD tools for FPGAs
• Homomorphic Encryption
• Cybersecurity
• +5 more

Loïc Lagadec is a Professor in Computer Science at ENSTA-Bretagne, an engineering school in Brest, France, where he serves as Assistant Head of Research Delegate for Cybersecurity Activities and is a member of LabSticc. His career spans academic leadership, research in reconfigurable architectures, cybersecurity, and hardware-software co-design. Affiliation: ENSTA-Bretagne, LabSticc Research Focus: FPGA CAD tools, Homomorphic Encryption, RISC-V security His research explores CAD tools for unconventional architectures (e.g., NASICs), homomorphic encryption evaluation, and hardware acceleration. He employs Smalltalk-based object-oriented languages for domain modeling and software quality. Current projects include on-chip monitoring for zero-day attack detection and secure RISC-V extensions. Recent publications highlight trends in machine learning hardware acceleration , JIT compiler security , and deep-sea IoT environmental constraints . Grants include DGA-funded "Overlays for long time maintenances" (2014-2016) and "Secure Overlays" (2017-2020), and Région Bretagne CPER Cyber-SSI (2015-2020). He has supervised PhD students including Xuan Sang Le , Théotime Bollengier , and Cyrielle Feron , and collaborates with institutions like Lab-STICC and European MORPHEUS IP FP6 projects. His work bridges theoretical innovation with practical embedded systems implementation.

• Computer Architecture
• High-Performance Computing (HPC)
• Internet of Things (IoT)
• +7 more

Vincent Bode is a researcher and teaching assistant at the Chair of Computer Architecture and Parallel Systems at the Technical University of Munich (TUM) . His work focuses on benchmarking and optimizing Data Distribution Service (DDS) middleware for Industrial IoT applications, particularly through the DDS-Perf project in collaboration with Siemens .

• Hardware-Software Co-Design
• Compiler Design
• Embedded Systems
• +5 more

Dr. Frank Hannig is a Professor at the Department of Computer Science, Friedrich Alexander University Erlangen-Nuremberg (FAU), Germany. He serves as the Head of the Architecture and Compiler Design Group within the Hardware-Software-Co-Design department (Department 12). With a career spanning over two decades at FAU since 2003, he has established himself as a leading researcher in hardware-software co-design, compiler design, and embedded systems. Dr. Hannig received his Diploma degree in Electrical Engineering/Computer Science from the University of Paderborn in 2000, followed by his Dr.-Ing. degree in Computer Science from FAU in 2009 with a thesis on "Scheduling Techniques for High-Throughput Loop Accelerators." He completed his habilitation (Dr.-Ing. habil.) in 2018 with a thesis titled "Domain-specific and Resource-aware Computing," which qualifies him for a full professorship in the German academic system. His research focuses on hardware-software co-design, compiler design for embedded systems, reconfigurable computing, parallel systems, and machine learning acceleration. Dr. Hannig has made significant contributions to domain-specific and resource-aware computing, with applications in image processing, automotive systems, and edge AI. His work bridges the gap between high-level programming models and efficient hardware implementations, particularly for resource-constrained environments. Dr. Hannig's recent publications reveal a strong trend toward efficient machine learning deployment on embedded devices and microcontrollers, with particular emphasis on memory optimization, hardware acceleration, and low-precision computing. His research spans multiple domains including computer architecture, machine learning, and embedded systems, with a focus on practical implementations for real-world applications. Dr. Hannig serves as an Associate Editor for IEEE Embedded Systems Letters and the Journal of Real-Time Image Processing. He has organized numerous prestigious conferences including SLOHA 2021, ARC 2021, and Euro-Par 2021, demonstrating his leadership in the academic community. As an educator, Dr. Hannig teaches courses on Domain-Specific and Resource-Aware Computing on Multicore Architectures, Parallel Systems, and Embedded Systems. He has supervised numerous students through lectures, exercises, and seminars covering electronic system level design and multi-core architectures. Dr. Hannig leads several significant research projects including InvasIC (DFG Transregional Collaborative Research Centre), ExaStencils (Advanced Stencil-Code Engineering), and HBS (DFG Research Training Group on Heterogeneous Image Systems). His work with the HIPAcc open-source project has contributed to domain-specific language and compiler development for image processing applications.

Seda OgrenciView profile

Professor

• Design Automation
• Real-Time Edge AI/ML for Science
• Thermal-Aware Circuit Design
• +3 more

Seda Ogrenci is a Professor of Electrical and Computer Engineering and Computer Science at Northwestern University. She holds affiliations with the McCormick School of Engineering and leads the Ogrenci-Memik Lab. Her research focuses on thermal-aware design, edge AI/ML acceleration, and energy-efficient computing systems. She teaches courses like EECS 303 (Advanced Digital Design), EECS 355 (FPGA Design), and EECS 459 (VLSI Algorithmics). Education includes a PhD in Computer Science from UCLA, MS in Electrical and Computer Engineering from Northwestern, and BS from Bogazici University. Her work spans thermal management, 3D stacked memory systems, and reconfigurable architectures. She authored the book Heat Management in Integrated Circuits (2016) and holds patents on thermal sensors and energy harvesting. Recent projects include ML-based real-time control at the edge, FPGA-accelerated ML monitoring, and in-pixel AI for X-ray detectors. Awards include the NSF CAREER Award (2006) and EECS Best Teacher Award (2013). She advises students like Dawei Li and Yingyi Luo and contributed to grants on thermal-aware HPC systems.

Seth GoldsteinView profile

Associate Professor

• Programming Languages
• Systems
• Computer Architecture
• +9 more

Seth Goldstein is an Associate Professor in the Computer Science Department at Carnegie Mellon University's School of Computer Science. His research focuses on ensembles (massively scalable systems), distributed systems, reconfigurable computing, and programmable matter (Claytronics). He leads projects like BoLT (a decentralized lending platform) and Phoenix (computing without traditional processors). He has advised numerous graduate students and teaches courses including Compiler Design, Computer Architecture, and Cloud Computing. Research Interests : Goldstein explores systems with massive interacting components, such as molecular-scale devices, modular robotics, and economic systems. His work spans compilers (e.g., register allocation optimizations), time synchronization protocols for embedded systems, and algorithms for self-reconfiguring robots. Recent projects include BlockGraph (a secure distributed ledger) and peer code review methodologies. Key Contributions : Goldstein's work on Claytronics pioneered programmable matter, enabling shape-shifting materials. His BoLT platform addresses lending market inefficiencies using blockchain principles. He has also developed algorithms for modular robot coordination and energy-efficient self-reconfiguration. Labs/Teams : Goldstein directs research in the CMU Robotics Institute and collaborates with interdisciplinary teams on projects like the PipeRench and Phoenix architectures. His lab explores intersections between nanotechnology, distributed systems, and societal applications like new monetary systems.

Paulo GarciaView profile

Assistant Professor

• Embedded Real-Time Systems
• Hardware/Software Co-Design
• FPGA Acceleration
• +3 more

Paulo Garcia is an Assistant Professor in the Department of Systems and Computer Engineering at Carleton University, Ottawa, Canada. He holds a Ph.D. in Computer Engineering from the University of Minho, Portugal, with research periods at Asian Institute of Technology and University of Würzburg. His academic roles include serving as a faculty member, thesis chair/examiner, and committee member in multiple university initiatives. Research Focus: Embedded real-time systems, hardware/software co-design, FPGA acceleration, and engineering pedagogy. Specific technical areas include multicore architectures, runtime systems, and hardware accelerators for embedded applications. His work emphasizes synergies between processor architectures, compilers, and FPGA-based solutions. Teaching: Courses include SYSC 3310 (Real-Time Systems), SYSC 4310 (Computer Architecture), and SYSC 5807 (Hardware/Software Co-Design). He supervises senior projects like robotic systems and eHealth wearable devices. Awards & Grants: Includes 2020 awards from General Dynamics Mission Systems and Carleton’s Rapid Response Grant, plus multiple scholarships from FCT Portugal and EU programs. His research has been supported by industry partnerships and defense collaborations. Service: Active in academic service as a thesis evaluator, member of student mental health committees, and representative in university governance bodies. Engaged in curriculum development and embedded systems program revisions.

Mark GondreeView profile

Associate Professor

• Security Pedagogy
• Applied Cryptography
• Computer Science Education
• +1 more

Mark Gondree is an Associate Professor in the Computer Science Department at Sonoma State University, with research expertise in security pedagogy, applied cryptography, and secure computation. He holds a PhD from UC Davis and has received multiple teaching awards including the CSU Student Success Analytics Certificate and POGIL Activity Clearinghouse recognition. His research explores cybersecurity education methods, cloud data geolocation, and industrial control system vulnerabilities. Recent publications focus on curriculum development for computer security concepts and efficient cryptographic protocols. Awards: CSU Student Success Analytics Certificate (2024) POGIL Activity Clearinghouse Publications (2022) QuARRY Repository Award (2020) He actively advises graduate and undergraduate researchers on projects ranging from fuzz testing to pseudorandom number generator analysis. Current grants include NSF funding for CS teacher preparation programs and cloud security research. As department chair, he oversees curriculum development and leads the Computer Science Colloquium series.

Peter WägemannView profile

Researcher

• Real-Time Systems
• Embedded Systems
• Worst-Case Analysis
• +5 more

Peter Wägemann is a postdoctoral researcher leading the Embedded Systems Software group at the Chair of Computer Science 4 (System Software) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His research focuses on real-time systems, energy-constrained systems, worst-case analysis, and fault tolerance in embedded systems. He has received multiple awards, including the Best Paper Award at ECRTS '24 and Outstanding Paper Awards at ECRTS '18 and RTAS '17. His work spans topics like clock reconfiguration, energy-neutral systems, and Byzantine fault tolerance. Wägemann's teaching includes courses such as System-Level Programming, Real-Time Systems, and Dependable Real-Time Systems. He has organized conferences like WCET and RTSS and serves on program committees for top venues. His funded projects include DFG grants for Byzantine Fault Tolerance (BFTeam), whole-system analysis (Watwa), and power-constrained systems (ResPECT). He also collaborates with industry partners like Schaeffler AG on safety-critical AI systems. Key contributions include the Platin WCET analysis tool, TinyBFT for resource-constrained systems, and energy-efficient frameworks like FusionClock. His work bridges theoretical analysis with practical implementations in embedded systems, emphasizing sustainability and real-time guarantees.

Konstantinos MamourasView profile

Assistant Professor

• Programming Languages
• Formal Methods
• Stream Processing
• +3 more

Konstantinos Mamouras is an Assistant Professor in the Department of Computer Science at Rice University, affiliated with the College of Engineering. His research focuses on programming abstractions for data streams, runtime verification for cyber-physical systems, and program semantics. He holds a PhD from Cornell University (2015) under Dexter Kozen and has held postdoctoral roles at the University of Pennsylvania. Education: PhD in Computer Science, Cornell University (2015) Research Interests: Mamouras designs languages and tools for efficient data stream processing (e.g., StreamQRE) and explores formal methods in program verification. His work bridges theoretical foundations (e.g., Kleene Algebra) with practical implementations, addressing challenges in real-time decision systems and resource-constrained applications like medical monitoring. Recent projects include GPU-accelerated regex matching, energy-efficient automata processors, and compositional monitoring frameworks for continuous signals. Publications: His work spans algorithm design, formal verification, and hardware-software co-design. Notable contributions include reconfigurable automata processors, verified regex matchers, and energy-efficient genome alignment accelerators. He has received awards at PLDI (2024) and EuroSys (2021) for impactful research. Awards: Best Paper Award, EuroSys 2021 Distinguished Paper Award, PLDI 2024 Teaching & Advising: Mamouras teaches courses on IoT programming, formal methods, and verified software. He advises students (e.g., Alexis Le Glaunec, Agnishom Chattopadhyay) and has supervised MSc and PhD theses on topics like streaming algorithms and quantitative monitoring. His lab focuses on advancing programming models for real-time data systems.

• High-Performance Computing
• Neuromorphic Engineering
• Bio-inspired Systems
• +7 more

Pedro Filipe Zeferino Tomás is an Associate Professor at the University of Lisbon's College of Engineering, Department of Electrical and Computer Engineering. He is affiliated with INESC-ID research institute and teaches courses on Large Scale Computing, Computer Architecture, and High Performance Computing. His academic career includes a PhD in Neural Code modeling (2009), a Master's in DSP hardware structures (2006), and a Bachelor's in Bio-Inspired Artificial Retina design (2003). His research focuses on neuromorphic engineering, parallel computing architectures, and biosensing applications. Key areas include GPU optimization, transprecision arithmetic, neural prosthetics, and participatory urban biosensing. He has pioneered bio-inspired systems for visual neuroprostheses and developed energy-efficient hardware accelerators for machine learning. His recent work integrates biosensors into urban studies, exploring participatory methods for analyzing affective geographies and walkability. Over 60 peer-reviewed publications demonstrate his contributions to high-performance computing, neural modeling, and interdisciplinary urban technology. Grants: Multiple EU-funded projects in neuromorphic systems and urban biosensing Labs: Leads the Heterogeneous Computing Lab at INESC-ID and collaborates with neural engineering teams

Seth Copen GoldsteinView profile

Associate Professor

• Programmable Matter
• Claytronics
• Reconfigurable Computing
• +6 more

Seth Copen Goldstein is an Associate Professor in the Computer Science Department at Carnegie Mellon University's School of Computer Science. His research spans multiple interdisciplinary domains focusing on ensembles - large collections of interacting agents. He has made significant contributions to reconfigurable computing, molecular-scale devices, programmable matter, and more recently, the impact of technology on labor markets and alternative monetary systems. Education: PhD in Computer Science, University of California at Berkeley BS, Princeton University Goldstein's research agenda has evolved from reconfigurable computing to molecular-scale devices and programmable matter, and most recently to social technology and alternative monetary systems. His early work focused on compiling high-level programming languages directly into configurations for computing ensembles of gates. He then investigated molecular-scale circuits and programmable matter - ensembles of computing elements that can be programmed to change physical properties. Since returning from a startup, he has shifted focus to ensembles of people, studying technology's impact on labor markets and innovation, and developing social technologies to reduce poverty and inequality. His publication trends show a consistent focus on modular robotics, distributed systems, and programmable matter. The research spans theoretical foundations, hardware implementation, and programming languages for large-scale ensembles. Recent work emphasizes energy efficiency, distributed algorithms, and novel programming paradigms for heterogeneous systems. The interdisciplinary nature of his work connects computer science, electrical engineering, and social sciences. Research Leadership: Claytronics project - creating ensembles of cooperating submillimeter robots Development of Meld and LDP programming languages for ensemble systems Phoenix project - computing without processors Building on Local Trust (BoLT) initiative Goldstein has advised numerous PhD students who have gone on to positions at major technology companies including Microsoft Research, Sun Microsystems, and NEC Labs. His work has been supported by significant research grants focusing on modular robotics, programmable matter, and distributed computing systems. He has taught core computer science courses including Compiler Design, Introduction to Computer Systems, and Cloud Computing.

Zhong ShaoView profile

Professor

• Programming Languages
• Formal Methods
• Operating Systems
• +4 more

Zhong Shao is the Thomas L. Kempner Professor of Computer Science at Yale University. He leads the FLINT research group and is a prominent researcher in programming languages, formal methods, operating systems, and computer security. His work focuses on building certified system software through mechanized proofs to create dependable software systems that can manage increasing complexity in modern computing. Professor Shao's research spans multiple domains including programming language design, OS kernel development, formal semantics, compiler construction, and proof engineering. His work addresses challenging problems in concurrency and distributed computing, with a particular emphasis on creating hacker-resistant systems. He has collaborated with researchers at Princeton, University of Pennsylvania, and MIT on the NSF Expedition project 'The Science of Deep Specification.' Shao's recent publications demonstrate a strong focus on compositional verification techniques for distributed systems and certified compilation. His work on DeepSEA language, CertiKOS operating system, and various verification frameworks shows a consistent trajectory toward building fully verified system software from the ground up. Key themes include linearizability, Byzantine fault tolerance, compositional reasoning, and refinement-based verification approaches across concurrent and distributed systems. As an educator, Professor Shao teaches courses including CS430 Formal Semantics (Spring 2025), CS421 Compilers and Interpreters, CS422 Operating Systems, and CS428 Language-Based Security. He participates in systems seminars on APLAR and SPAM, contributing to the academic community through both research and teaching. Professor Shao leads the FLINT research group at Yale, which focuses on building novel certified system software. The group's work has resulted in breakthroughs such as the CertiKOS operating system, which represents a significant advancement in hacker-resistant concurrent operating systems. The group collaborates with the DeepSpec project, an NSF Expedition focused on deep specifications for trustworthy systems, and has developed frameworks like LiDO, Adore, and AdoB for verifying distributed systems with strong guarantees.

• Experimental Fluid Mechanics
• Computational Fluid Mechanics
• Dynamic Flow Control
• +4 more

Daniel M Nosenchuck is an Associate Professor at Princeton University's School of Engineering, Department of Mechanical and Aerospace Engineering. His work bridges experimental fluid mechanics and supercomputer architecture , focusing on flow control and simulation technologies. PhD in Aeronautics (Caltech, 1982) MS in Aeronautics (Caltech, 1977) BS in Aerospace and Mechanical Engineering (Syracuse, 1976) Research Highlights : Active control of turbulence and boundary layers using electromagnetic and thermal methods Invention of the Navier-Stokes Computer for advanced hydrodynamic simulations Development of laser-sheet scanning techniques for 3D flow visualization Patents in electromagnetic boundary layer control and dynamic reconfiguration systems Prominent Research Themes from 1982-1994 include: Experimental fluid mechanics with applications in aerospace and marine systems Parallel computing architectures for turbulence simulation Interdisciplinary studies in bioluminescence and hydrodynamics Active control of wake vortices and transitional flows Development of optimizing compilers for supercomputers Innovative visualization techniques for complex flows Scientific Awards : NSF Presidential Young Investigator Award (1984-1989) IBM Faculty Development Award (1984-1985) Princeton Rheinstein Award (1986) National EMMY for Special Visual Effects (1984) GTE Emerging Scholar (1987) William F Ballhaus Prize (1982) Undergraduate Engineering Council Teaching Award (1993) Advising & Grants : Advisor to multiple co-authors in fluid mechanics and computer science NSF funding through Presidential Young Investigator program Industrial and DoD consulting projects Labs & Facilities : Moody Hydrodynamics Laboratory (Princeton) Low-Speed Water Channel High-Speed Water Tunnel