Find Academic Supervisors

• Computer Architecture
• High Performance Computing
• Parallel Programming
• +5 more

Andrea Marongiu is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences at the University of Modena and Reggio Emilia, specifically affiliated with the Mathematics department. He maintains an active research profile while teaching multiple courses in computer architecture and parallel systems. His research interests span computer architecture, high performance computing, parallel programming, and embedded systems. Marongiu focuses particularly on memory systems, heterogeneous computing architectures, FPGA-based acceleration, and real-time performance analysis. His work bridges theoretical foundations with practical implementation challenges in modern computing systems, with special attention to predictable execution models and quality of service guarantees. Analysis of his recent publications reveals a strong emphasis on memory bandwidth management in heterogeneous systems, particularly focusing on FPGA-based architectures and multicore SoCs. His research trajectory shows consistent work in memory interference analysis, PREM (Predictable Execution Model) scheduling techniques, and fine-grained QoS control mechanisms. The publications demonstrate a progression from general parallel programming concepts toward increasingly specialized techniques for resource-constrained environments like autonomous vehicles and edge computing devices. Marongiu teaches several advanced computer science courses including Computer Architecture I & II, Compilers, High Performance Computing, and Electronic Calculators across multiple degree programs. His teaching approach emphasizes both theoretical foundations and practical implementation, with a focus on RISC-V architecture and modern parallel programming techniques. The course materials indicate he incorporates hands-on laboratory work as an essential component of his pedagogy, particularly in areas like compiler construction and parallel programming.

Mostafa Hadadian Nejad YousefiView profile

Researcher

• Machine Learning
• Distributed Systems
• Service-Oriented Computing
• +5 more

Mostafa Hadadian Nejad Yousefi is a Researcher at the Faculty of Science and Engineering , University of Groningen , specializing in Distributed Systems . His work bridges machine learning and distributed computing, focusing on adaptive systems and digital twins. His research interests include: Machine Learning Service-Oriented Computing Neural Networks Distributed Systems Digital Twins Big Data Bioinformatics Recent publications highlight his work on: Digital twin architectures for water distribution networks (2024) Self-adaptive service selection in ML pipelines (2024) Service-oriented principles for ML development (2023) Dynamically reconfigurable distributed pipelines (2021) Neural network-based genomics analysis (2021) Contact: m.hadadian@rug.nl

Ian GibsonView profile

Professor

• Electronics
• Sensors and Digital Hardware
• Artificial Intelligence
• +6 more

Professor Ian Gibson is a distinguished faculty member at the University of New South Wales with over 30 years of experience as a computer scientist and engineer at executive level R&D management. He has led the research, development and global commercialisation of new technology across a broad range of electrical engineering, computer science and digital imaging. His educational background includes: BE (Hons) Electrical Engineering / BSc, University of NSW (1986) PhD Electrical Engineering, University of NSW (1991) Professor Gibson's research spans multiple cutting-edge fields in computer science and engineering. His primary interests include Electronics, Sensors and Digital Hardware, Artificial Intelligence, Machine Learning, Computer Vision and Multimedia Computation, Software Engineering, and Distributed Computing and Systems Software . His work demonstrates a consistent focus on bridging theoretical concepts with practical applications, particularly in image processing and hardware design for specialized computational tasks. Analysis of Professor Gibson's publication record reveals a clear evolution from early foundational work in logic programming hardware (Prolog processors) to more recent innovations in image processing, computer vision, and data management systems. His research shows a strong emphasis on practical, commercially viable technologies with numerous patents and billion-unit scale deployments. While specific academic awards aren't listed in the available information, Professor Gibson's professional achievements are substantial: Technology shipped in over 1 billion units worldwide Secured over $200 million in research funding from various sources Generated hundreds of patents during his tenure at CiSRA Professor Gibson has held significant leadership positions that demonstrate his impact beyond pure research. As the founding CEO of Intersect Australia Ltd (2008-2015), he shaped research infrastructure services for the Australian academic community. Prior to this, as General Manager at CiSRA (Canon Inc's Australian R&D lab), he built research capability that delivered world-leading technology into Canon's major product groups.

Melike Erol KantarciView profile

Associate Professor

• 5G and 6G Networks
• Artificial Intelligence (AI)
• Tactile Internet
• +9 more

Dr. Melike Erol-Kantarci is an Associate Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, and a Canada Research Chair in AI-enabled Next-Generation Wireless Networks. She founded the Networked Systems and Communications Research (NETCORE) Laboratory and holds a courtesy appointment as Assistant Professor at Clarkson University's Electrical and Computer Engineering Department. With over 6,000 citations and an h-index of 40, she contributes to IEEE as a Senior Member, chairs the Green Smart Grid Communications special interest group, and serves as Editor for IEEE Communications Letters and IEEE Access . Research Focus: 5G/6G wireless networks AI/ML-driven network optimization Smart grid communications Cyber-physical system security Edge computing and IoT Reconfigurable Intelligent Surfaces (RIS) Scientific Contributions: Her recent publications highlight generative AI integration in 6G, intent-driven network management using hierarchical reinforcement learning, physical layer security for connected vehicles, and explainable AI frameworks in communications. The 15 most recent works (2024-2025) span topics like beamforming optimization, federated learning security, UAV-assisted networks, and semantic communication systems. Leadership: As director of the NETCORE Laboratory, she leads cutting-edge research in networked systems, bridging wireless communication paradigms with energy sustainability and security requirements for next-generation networks.

Ulrik Pagh SchultzView profile

Professor

• Generative Programming
• Embedded Systems
• Domain-Specific Languages
• +3 more

Ulrik Pagh Schultz is a Professor at the University of Southern Denmark, specializing in generative programming, domain-specific languages, and embedded systems. His research focuses on automatic code generation, real-time systems, and reconfigurable robotics, with applications in autonomous drone operations and energy modeling for embedded systems. He has served as a committee member and session chair for numerous conferences including PEPM, GPCE, SPLASH, and POPL since 2011. Notable contributions include work on Idris programming language, reversible computing, and service-oriented architectures for drones. His career spans active involvement in programming language design and practical implementation challenges in robotics software engineering, particularly through collaborations at ACM SIGPLAN conferences. While specific students and awards aren't listed, his extensive service roles demonstrate significant academic engagement.

Francisco Jurado MelguizoView profile

Professor

• Power Systems
• Renewable Energy
• Energy Storage
• +3 more

Francisco Jurado Melguizo is a Professor in the Department of Electrical Engineering at Universidad de Jaén. His research focuses on power systems, renewable energy integration, and optimization algorithms, with over 520 JCR-indexed publications and 260 conference papers. He has led projects funded by Spanish Ministries and the European Commission and authored 8 books. PhD: Universidad Nacional de Educación a Distancia (UNED), 1999 His work spans distributed generation, energy storage, smart grids, and techno-economic analysis, often incorporating AI and metaheuristic optimization techniques. Recent projects include hybrid renewable systems, EV charging infrastructure, and grid resilience under climate uncertainties. He has received recognition as one of the most influential researchers globally by Stanford University and contributes to research groups focused on electrical technology and energy systems.

Jonathan CohenView profile

Professor

• Cognitive Control
• Computational Neuroscience
• Psychiatric Disorders
• +5 more

Jonathan Cohen serves as the Robert Bendheim and Lynn Bendheim Thoman Professor in Neuroscience at Princeton University's Princeton Neuroscience Institute, where he leads groundbreaking research on the neurobiological foundations of cognitive control and its disruption in psychiatric disorders. His work bridges computational modeling, cognitive science, and clinical neuroscience to unravel how distributed neural systems enable goal-directed behavior. Education: M.D. from the University of Pennsylvania Ph.D. from Carnegie Mellon University Cohen's research centers on cognitive control mechanisms involving prefrontal cortex, anterior cingulate cortex, basal ganglia, and neuromodulatory systems, with direct applications to schizophrenia and depression. His lab develops mechanistically explicit computational models to explain how billions of neurons coordinate purposeful behavior, seeking to establish a theoretical foundation for psychiatric research. This integrative approach combines empirical neuroimaging with rigorous mathematical frameworks to decode the neural basis of executive function. Analysis of his recent publications (2022-2025) reveals a compelling evolution toward interdisciplinary synthesis, where computational neuroscience increasingly intersects with artificial intelligence. His work now explores emergent symbolic reasoning in neural networks, cerebellar-cortical interactions in neurodevelopmental disorders, and the neural reconfiguration underlying task switching – all while maintaining clinical relevance to mental illness. Scientific Awards: Election to American Academy of Arts and Sciences APS William James Award Cohen mentors graduate students including Younes Strittmatter and directs the Neuroscience of Cognitive Control Lab, which has secured substantial funding such as a $16M Princeton-Rutgers Collaboration Grant for mental illness research. His lab actively investigates how disturbances in brain function manifest as psychiatric symptoms, with recent projects examining cognitive control allocation in depression and neural mechanisms of grief. The Neuroscience of Cognitive Control Lab employs a multidisciplinary framework combining computational modeling, fMRI, behavioral experiments, and machine learning to dissect the architecture of executive function. Current initiatives explore cerebellar contributions to cognitive aging, abstract reasoning mechanisms, and the development of theoretically grounded interventions for psychiatric disorders through collaborative neuroscience initiatives.

M. C. Frank ChangView profile

Professor

• High-speed semiconductor devices
• Terahertz electronics
• CMOS integrated circuits
• +4 more

M. C. Frank Chang is a Distinguished Professor and Wintek Chair in Electrical Engineering at the University of California, Los Angeles (UCLA). He leads cutting-edge research in high-speed semiconductor devices and Terahertz electronics at the High Speed Electronics Lab. Department: Electrical and Computer Engineering Email: mfchang@ee.ucla.edu Website: Full publication list His research focuses on high-frequency mixed-signal semiconductor devices and CMOS integrated circuits for applications in: Radio and radar systems Space science instrumentation Edge-AI (AIoT) systems Wireless communication infrastructure Terahertz imaging and sensing Recent publications (2025) highlight trends in sub-Terahertz transceivers for 6G communication, on-chip antenna design, and advanced calibration techniques for high-frequency systems. Earlier works (2018-2022) explore AI accelerators for IoT, regenerative receivers for mm-Wave imaging, and noise-cancelling RF architectures. Scientific accolades include: 2024 AASF Asian American Pioneer Medal 2023 IEEE James Clerk Maxwell Medal 2022 IEEE Life Fellow 2017 J J Thomson Medal Multiple IEEE Best Paper Awards Honorary Doctorates from NTU and NCTU He has pioneered innovations in semiconductor device commercialization, including HBT power amplifiers for smartphones, and holds patents in advanced wireless interconnects. His work bridges fundamental research and practical applications in high-frequency electronics.

Brian J. GermanView profile

Associate Professor

• Aerospace Engineering
• Electric Propulsion
• Urban Air Mobility (UAM)
• +6 more

Brian J. German is the National Institute of Aerospace Langley Associate Professor in the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology. His research focuses on electric propulsion, urban air mobility (UAM), and the transformation of aviation through autonomy and distributed electric propulsion technologies. Education: Ph.D. in Aerospace Engineering, Georgia Tech (2007) M.S. in Aerospace Engineering, Georgia Tech (2000) B.S. in Aerospace Engineering, Georgia Tech (1999) German specializes in aircraft design optimization, battery modeling for electric aircraft, and operations research for emerging aviation markets. His work spans technical domains like aerodynamics, propulsion systems, and airspace utilization, with applications in UAM, thin-haul regional aviation, and cargo delivery via eVTOL aircraft. Recent research trends emphasize multidisciplinary optimization frameworks, propeller-wing interaction modeling, and economic feasibility studies for electric aircraft. He has led NASA-sponsored projects on vertiport placement, battery recharge economics, and blown wing performance analysis. Scientific Awards: NSF CAREER Award (2012) AIAA Associate Fellow (2017) Fulbright Scholarship (2002) Lockheed Martin Dean’s Excellence in Teaching Award (2012) National Defense Science and Engineering Graduate Fellowship (1999) German has advised students on eVTOL cargo delivery, blown wing wind tunnel studies, and optimization of reconfigurable aircraft. He teaches undergraduate and graduate courses on aerospace performance, design methods, and optimization. His lab conducts wind tunnel and flight tests of subscale CTOL/STOL/VTOL aircraft to validate aerodynamic and performance models.

Arijit RaychowdhuryView profile

Professor

• Low Power Digital Circuits
• Compute-in-Memory (CIM)
• Adaptive Clocking and Power Management
• +7 more

Arijit Raychowdhury is a Professor and the Steve W. Chaddick School Chair at Georgia Tech's School of Electrical and Computer Engineering (ECE). He leads the Center for the Co-Design of Cognitive Systems (CoCoSys) and directs the DoD-sponsored SCALE Workforce Development Program in SoC Design. Current affiliations: Georgia Tech (ECE), Integrated Circuits and Systems Research Lab Prior affiliations: Intel Corporation (6 years), Texas Instruments (1.5 years) Research interests focus on low-power circuits, compute-in-memory (CIM) systems, cryogenic electronics, and neuro-symbolic AI. His work bridges circuit design with emerging device technologies and machine learning applications. Scientific contributions include: Over 250 publications and 27 patents Leadership in top conferences (ISSCC, VLSI Symposium, DAC, CICC) Pioneering 3D Gaussian Splatting acceleration, adaptive echo-cancellation networks, and CIM architectures Advancing GaN-based power converters and cryogenic CMOS Awards : IEEE Fellow (2022) SRC Technical Excellence Award (2021) Qualcomm Faculty Award (2021, 2020) IEEE/ACM Innovator under 40 (2018) Intel Young Faculty Award (2015) Dimitris N. Chorafas Award (2007) Leadership : • Director of CoCoSys Center • Site Director for SCALE Program • Distinguished Lecturer, IEEE Solid-State Circuits Society

Jonathan M. AitkenView profile

Senior Lecturer

• Autonomous robotics
• Computer vision
• Spatial awareness in robotic systems
• +4 more

Dr. Jonathan M. Aitken is a Senior Lecturer in Robotics at the University of Sheffield's School of Electrical and Electronic Engineering. Previously a Research Fellow at the Autonomous Control Laboratory (ACSE), his work focuses on autonomous robotic systems with emphasis on quadcopters, computer vision, spatial awareness, and multi-robot collaboration. Expert in safe autonomous drone deployment Specializes in collaborative robotics (cobots) Qualified UK commercial drone pilot Research spans: Autonomous reconfiguration of robotic systems Dynamic risk assessment for systems-of-systems Visual SLAM for feature-sparse environments Formal verification of UAS systems Human-robot co-working interfaces Recent publications examine: Robust localization in sewer pipes Visual saliency algorithms for mobile robots Cobotic safety controller synthesis Modular digital twinning frameworks Spatial awareness for multi-robot teams Major grants include EPSRC Programme Grants for buried pipe sensing and Lloyds Registry Foundation funding for cobot safety integration.

• Robotics
• Mechatronic Systems
• Human-Robot Interaction
• +4 more

Xiumin Diao is an Associate Professor at Purdue University's School of Engineering Technology, specializing in robotics and mechatronic systems for healthcare and manufacturing applications. His work emphasizes human-robot interaction, control algorithms, and energy-efficient UAV designs. Education: Ph.D. in Mechanical Engineering (2007, New Mexico State University) M.S. in Measurement Technology and Automatic Device (2003, Beihang University) B.S. in Mechanical Design and Manufacturing (2000, Yantai University) Research focuses on cable-driven parallel robots , reinforcement learning , and intention prediction using neural networks. Recent publications explore stiffness analysis, UAV arm rotation efficiency, and hybrid control strategies. Key trends in his work include: Advancing adaptive control for robots with unknown dynamics Optimizing energy efficiency in aerial robotics Applying deep learning to human motion understanding His lab develops hardware-in-the-loop microgravity simulators and rehabilitation devices, with applications in disaster exploration and satellite docking.

Patricia DesgreysView profile

Professor

• Analog and Mixed Signal (AMS) Circuit Design
• Cognitive Radio Systems
• Internet of Things (IoT)
• +7 more

Patricia Desgreys is a full professor at Institut Polytechnique de Paris , where she leads the Communication Circuits and Systems (C2S) research team within the Laboratory of Information Processing and Communication (LTCI) . Her work spans analog and mixed-signal (AMS) circuit design, cognitive radio systems, and digitally enhanced mixed-signal architectures for IoT and cyber-physical systems. Agrégation in Applied Physics, École Normale Supérieure de Cachan M.Sc. and Ph.D. in Microelectronics, University of Bordeaux (1995-1999) Her research focuses on AMS circuit design from transistor to architectural levels, including software-defined radio , cognitive radio , and neural-inspired analog-to-feature converters . She has contributed to digital predistortion techniques for power amplifiers, compressive sampling for astrophysical signals, and leadless pacemaker communication channels . Her 150+ publications highlight advancements in wireless systems, biomedical sensors, and 5G infrastructure. Recent work (2024) explores AI-driven analog design and 75 years of circuits innovation in IEEE Transactions. She has graduated 16 PhD students and co-authored the book Digitally Enhanced Mixed Signal Systems (IET, 2019). Her leadership includes Technical Program Chair roles at IEEE PRIME (2019), ICECS (2016), and NEWCAS (2012-2013), plus editorial work for IEEE TCAS-II special issues (2018-2019). She directs the ICS Master’s program (Institut Polytechnique de Paris/Paris-Saclay University) and teaches advanced electronics at SJTU-ParisTech in Shanghai . Her patents include signal sampling circuits and power amplifier linearization techniques.

• Embedded Systems
• Artificial Intelligence
• FPGA Optimization
• +2 more

Chao Qian, M.Sc., is a researcher and PhD student at the Department of Embedded Systems, University of Duisburg-Essen, since April 2020. He holds a bachelor's degree in Electrical Engineering from the University of Electronic Science and Technology of China (2015) and a master's degree in Embedded Systems from the University of Duisburg-Essen (2020). His research focuses on enabling artificial intelligence (AI) in reconfigurable hardware like FPGAs for energy-efficient and high-performance embedded systems. He investigates methods to deploy pre-trained neural networks on FPGAs, targeting traditionally resource-constrained embedded systems. Recent publications highlight his work on Configuration-aware FPGA power management Quantized transformers for time-series forecasting Soft sensor design for fluid flow estimation LSTM acceleration on embedded FPGAs In projects like "KI-Sprung: LUTNet" and "Elastic AI", he contributes to adaptive machine learning in pervasive computing. Contact: Email: chao.qian@uni-due.de Phone: +49 203 379 2390 Address: Bismarckstr. 90 (BC), Room BC 104, Duisburg

• Hardware Security
• Internet of Things (IoT)
• Physical Unclonable Functions (PUFs)
• +3 more

Armin Babaei is a Ph.D. researcher at the University of Duisburg-Essen (Uni DUE) within the Department of Computer Science, focusing on hardware security solutions for IoT devices. He holds an M.Sc. in Communications Engineering from RWTH Aachen and previously served as CTO in a startup for two years. Education: M.Sc. in Communications Engineering (RWTH Aachen) since 2015 His research integrates Physical Unclonable Functions (PUFs) with FPGA technology to develop secure, low-power authentication mechanisms for IoT systems. Publications highlight innovations in reconfigurable security architectures and spatial PUF implementations. Current research interests emphasize balancing security requirements with computational constraints in embedded systems. Key themes include: Hardware security for resource-constrained devices PUF-based authentication protocols Energy-efficient cryptographic solutions Contact: ababaei2000@gmail.com