Find Academic Supervisors

• Digital Design and Manufacturing (D2M)
• Sustainable Manufacturing
• Optimization Driven Design
• +7 more

Inigo Flores Ituarte is a Research Professor at Tampere University's Faculty of Engineering and Natural Sciences, affiliated with the Automation Technology and Mechanical Engineering department. He leads the Digital Design and Manufacturing (D2M) research lab, focusing on sustainable manufacturing and twin-transition strategies integrating digital and green technologies. His work emphasizes optimization-driven design, additive manufacturing innovations, and AI-driven expert systems to enhance energy efficiency and reduce environmental impacts. Key research pillars include: Pillar 1: Twin-transition in Engineering Design and Manufacturing Processes, addressing sustainable manufacturing and intelligent systems Pillar 2: Development of open D2M systems and Process-Structure-Property-Performance (PSPP) linkages in advanced materials His research explores multi-disciplinary optimization combining model-based simulations and data-driven techniques. Notable contributions include generative AI integration in CAD systems, cognitive manufacturing systems, and cost-effective process monitoring using CNN-based methods. Inigo's work emphasizes environmental sustainability, with a focus on reducing manufacturing's energy consumption (54% of global use) and CO2 emissions. He advocates for interconnected material systems, smart manufacturing processes, and AI-assisted decision-making to achieve cognitive intelligence in industrial operations. His D2M lab's overarching goal is to maximize product/process performance while improving cost-effectiveness and minimizing environmental footprints. Recent projects include railway bogie demonstrators via multi-material deposition and sensor systems leveraging IoT and ChatGPT integration.

• Terahertz Microsystems
• RF/Microwave MEMS
• Sub-THz Radar Concepts
• +3 more

Joachim Oberhammer is a Professor in Microwave and THz Microsystems at KTH Royal Institute of Technology in Stockholm, Sweden. He leads research in radio-frequency/microwave/terahertz micro-electromechanical systems (MEMS) and has held academic roles since 2005. His work includes pioneering advancements in THz communication, sub-THz radar concepts, and MEMS-based components. Oberhammer has been awarded the 2023 Young Engineer Award by the European Microwave Association and holds multiple grants, including an ERC Consolidator Grant (2013) and SSF framework grants (2014–2025). He has authored over 200 peer-reviewed publications and holds four patents in MEMS and THz technology. Education: M.Sc. in Electrical Engineering (Graz University of Technology, 2000), Ph.D. in Microwave Engineering (KTH, 2004). Postdoctoral research at Nanyang Technological University (2004) and Kyoto University (2008). Guest professorships at Universidad Carlos III de Madrid (2019–2020) and NASA-JPL (2014). Research focuses on MEMS fabrication, THz systems integration, and radar technologies. Key projects include the EU-funded M3TERA and Car2TERA projects, and leadership in SSF framework grants for electronics research. He coordinates the EU RIA projects TeraMeasure and TESLA, advancing terahertz applications. Teaching responsibilities include MSc and PhD courses in MEMS engineering, radar systems, and integrated circuits. His lab develops high-performance THz components, including waveguide switches, antennas, and filters, with applications in communication, sensing, and aerospace.

Cong LiuView profile

Associate Professor

• Real-Time Systems
• Embedded Systems
• Cyber-Physical Systems
• +3 more

Cong Liu is an Associate Professor of Computer Science at The University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. He joined UT Dallas in 2012 as an Assistant Professor and was promoted to his current rank. His research focuses on real-time and embedded systems, cyber-physical systems, and energy-efficient heterogeneous computing. Liu earned his Ph.D. in Computer Science from the University of North Carolina at Chapel Hill (2013), M.S. from Auburn University (2007), and B.E. from Wuhan University of Technology (2005). His research interests include real-time operating systems, cluster/cloud computing, and autonomous systems. He received the NSF CAREER Award in 2017 to develop algorithmic solutions for real-time data processing in autonomous vehicles and robotics. His work emphasizes GPU-accelerated embedded systems that enable autonomous decision-making in resource-constrained environments. Liu has held roles such as TPC member for IEEE RTAS and reviewer for multiple journals/conferences, including IEEE Transactions on Computers and Journal of Parallel and Distributed Computing. His publications address critical challenges in real-time scheduling, heterogeneous computing, and energy efficiency. He leads research on data-induced challenges in embedded systems, aiming to make autonomous driving systems predictable and controllable. Liu’s contributions bridge theoretical foundations with practical implementations in automotive and robotics domains.

Papadimitriou KyprianosView profile

Researcher

• Reconfigurable Systems
• Hardware Design
• Digital Systems
• +7 more

Kyprianos Papadimitriou is a Researcher at the Microprocessor and Hardware Laboratory within the School of Electrical and Computer Engineering at the Technical University of Crete . He holds a PhD in Electronic and Computer Engineering (2012) and has been involved in teaching laboratory courses such as Logic Design , Computer Architecture , and VLSI/ASIC Circuit Design . Research Areas : His work spans Reconfigurable Systems , Hardware Design , Computer Architecture , RFID Systems , and Real-Time Systems . He has developed innovative approaches in FPGA-based dynamic reconfiguration, MPSoC security, and 3D stereo vision for surveillance. Key Trends : Runtime reconfiguration for FPGAs Security frameworks for NoC-based MPSoCs Low-cost embedded vision systems Optimization of reconfiguration overhead Hardware task scheduling methodologies Genetic algorithm implementations on FPGAs Scientific Contributions : 1 USA patent (2005) Co-author of VLSI-SoC 2013 paper nominated for 1st Prize Active member of scientific committees (FPL, ReConFig) Peer reviewer for IEEE, Elsevier, and Springer journals Session chair at IEEE CNS and HPCC conferences Grants & Projects : Participated in competitive European and national programs, serving as scientific manager, coordinator, and technical coordinator. Developed spin-off company (2003-2005) to commercialize master's thesis research. Laboratory & Teaching : Affiliated with the Microprocessor and Hardware Laboratory , focusing on practical training in digital systems, processor-based systems, and VLSI design.

• Computer Graphics
• Rendering Algorithms
• Photo-realistic Rendering
• +9 more

Philip Dutré is a full professor at the Department of Computer Science , Faculty of Engineering Science , KU Leuven. He leads the Computer Graphics Research Group and chairs the Human-Computer Interaction division . His teaching portfolio includes courses on algorithms, data structures, and computer graphics fundamentals. Research Focus : Rendering algorithms, photo-realistic and image-based rendering, perceptual-based rendering, material models, and intuitive controls for computer animation. He explores deep learning applications in global illumination and uses quantum field theory for efficient light transport in participating media. Publications : Recent work includes advancements in temporal coherence for light transport (2017–2023), functional integrals for scattering models (2025), and optimization of spatial data structures (2019). Teaching Innovations : Advocate for ungrading (feedback-only assignments), flipped classroom techniques, and interactive learning. His approach emphasizes conceptual understanding over rote memorization, with structured, self-contained lessons and active student engagement. Leadership : Serves on multiple academic councils and committees including the Commission on Research Integrity and Student Services Council .

Andreas GrotheyView profile

Senior Lecturer

• Stochastic Programming
• Interior Point Methods
• Decomposition Methods
• +5 more

Andreas Grothey is a Senior Lecturer in the School of Mathematics at The University of Edinburgh, a position he has held since 2011. He completed his MSc in Numerical Algebra and Mathematical Computing at the University of Dundee (1995) and his PhD in Optimization at the University of Edinburgh (2001), supervised by Ken McKinnon. His research focuses on stochastic programming, interior point methods, decomposition approaches, high-performance computing, and energy systems optimization. He has contributed to energy planning, power grid reliability, and emergency response strategies for power networks. Grothey has advised seven PhD students, including work on unit commitment, top-percentile traffic routing, and power flow optimization. His projects include the OOPS solver, CESI energy integration center, and the Structured Modelling Language (SML). Recent work addresses pandemic policy optimization and exascale computational challenges. Education: MSc in Numerical Algebra and Mathematical Computing (University of Dundee, 1995) PhD in Optimization (University of Edinburgh, 2001) Research Interests: Stochastic Programming Interior Point Methods Decomposition Methods High-Performance Computing Energy Systems Optimization Advising & Projects: PhD Supervision (7 students, 2007–2022) OOPS Parallel Solver Development CESI Energy Systems Integration SML Structured Modelling Language Labs/Teams: Member of the Edinburgh Research Group on Optimization, leading projects in power grid stability and energy planning.

Cliff ZouView profile

Professor

• Computer Science
• Cybersecurity
• Network Security
• +3 more

Cliff Zou is a Professor in the Department of Computer Science at the University of Central Florida (UCF), where he coordinates master’s programs in cybersecurity, privacy, and digital forensics. He directs the UCF Alliance for Cybersecurity and contributes to the university’s Cyber Security and Privacy Cluster. Education: Ph.D. in Electrical and Computer Engineering from University of Massachusetts-Amherst His research focuses on computer and network security , network modeling , and performance evaluation . Key areas include malware analysis, botnet defense, and adaptive cybersecurity protocols. His publications address threats like email worms, peer-to-peer botnets, and internet worms, reflecting his work in proactive threat mitigation and network resilience. Scientific recognition includes: Senior Member of IEEE Best Student Paper Award (ACSAC 2007) UCF Teaching Incentive Program (TIP) award (2013) Best Paper runner-up (PADS 2005, ICCCN 2004) First-place award for undergraduate project 'Personal Medication Monitor' His research has been featured in New Scientist Magazine , EurekAlert! , PCWorld , and The Register . Zou actively contributes to academic conferences as an organizer and program committee member.

Fabio PierazziView profile

Associate Professor

• Adversarial Machine Learning
• Concept Drift Mitigation
• Malware Analysis
• +4 more

Dr Fabio Pierazzi is an Associate Professor in Information Security at the Department of Computer Science, University College London. His research focuses on enhancing systems security through AI, particularly in environments where attackers rapidly adapt to defenses. He investigates adversarial attacks, concept drift mitigation, and explainability of ML-based security systems. Research emphasizes adversarial machine learning in security contexts Works on practical applications in malware analysis and network intrusion detection Explores concept drift robustness and problem-space constraints Collaborates with industry to improve real-world security solutions His publications span top-tier venues like IEEE Security & Privacy, ACM CCS, and USENIX Security. Key themes include adversarial robustness, security evaluation methodologies, and AI's limitations in practice. He supervises research degrees and provides consultancy for security projects.

• Cloud Computing
• Green Computing
• High-Performance Computing
• +7 more

Jordi Guitart Fernández is a Professor at the Department of Computer Architecture, Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading national supercomputing facility. He leads the CROMAI research group, focusing on Computing Resources Orchestration and Management for AI. His work bridges high-performance computing, cloud systems, and artificial intelligence. Research Interests: Cloud Computing and Edge Computing Green and Energy-Efficient Computing Containerization and Virtualization for HPC Resource Orchestration and Management Autonomic and Self-Adaptive Systems Machine Learning Workflow Management AI-Driven System Optimization His recent publications reveal a strong focus on intelligent management of computing resources across cloud, edge, and HPC environments using machine learning and agent-based frameworks. He investigates performance, efficiency, and reliability in containerized AI and HPC workloads, particularly within Kubernetes and distributed infrastructures. His work increasingly integrates human-in-the-loop and trustworthiness aspects into AI systems. Scientific Awards: CLOUD Conference 2025 Best Paper Award VISIGRAPP 2025 Best Student Paper Award Premi Extraordinari de Doctorat 2025 - Àmbit d'Enginyeria de les TIC Test of Time Award Honorable Mention (e-Energy) Reconeixement als Mèrits Docents d'Especial Qualitat Top reviewers for Polytechnic University of Catalonia (Computer Science) - September 2017 Advising and Grants: He has advised doctoral students, including Peini Liu. He leads and participates in numerous competitive R+D+i projects, such as CROMAI and DALEST, funded by national and European programs like HORIZON 2020 and the Spanish State Research Plans. His work is supported by grants focused on knowledge generation and industrial leadership in computing technologies. Labs and Teams: He is the leader of the CROMAI - Computing Resources Orchestration and Management for AI research group at UPC. He also collaborates closely with the Barcelona Supercomputing Center (BSC-CNS), contributing to large-scale computing initiatives and strategic research agendas in Europe.

David FinkelsteinView profile

Associate Professor

• Limnogeology
• Biogeochemistry
• Aqueous Geochemistry
• +7 more

David Finkelstein is an Associate Professor in the Department of Geosciences at Hobart and William Smith Colleges, where he has been a faculty member since 2013. He earned his Ph.D. from the University of Illinois at Urbana-Champaign and holds advanced degrees from the University of Massachusetts, Amherst. His academic affiliations include prior roles as a Research Assistant Professor and Lab Manager at the University of Massachusetts and as an Assistant Professor at the University of Tennessee. Ph.D., University of Illinois at Urbana-Champaign M.S., University of Massachusetts, Amherst B.S., University of Massachusetts, Amherst Dr. Finkelstein's research centers on limnogeology and biogeochemistry , with a focus on the chemical evolution of lake systems, stable isotope geochemistry, and microbial life in extreme environments. His work integrates aqueous geochemistry, organic molecular analysis, and microbiological methods to reconstruct paleoenvironments and climate change across geological timescales, including the Holocene, Pleistocene, Cretaceous, and Triassic periods. He has extensively studied lake sediments, wildfires, and the environmental impacts of the 2010 Gulf of Mexico oil spill. His recent publications show a strong trend in using biogeochemical proxies and isotopic signatures to understand past climate variability, human-environment interactions, and extreme environmental conditions. His research often involves multidisciplinary collaborations and field-based studies in diverse regions such as Russia, Iran, and Central America. Dr. Finkelstein is actively involved in scientific communities, with affiliations including: International Association of Limnogeology American Geophysical Union Geological Society of America Geochemical Society SEPM (Society for Sedimentary Geology) He has advised numerous research projects and mentored students in geoscience, though specific names are not listed. His teaching includes courses such as Stable Isotope Geochemistry, Limnology, and Environmental Geochemistry, reflecting his expertise in both theoretical and applied aspects of earth sciences. Dr. Finkelstein has not received any explicitly listed scientific awards in the provided text, but his publication record in high-impact journals demonstrates significant scholarly contributions. He does not appear to lead a named laboratory or research center, but his work is deeply embedded in field and laboratory-based geochemical analysis.

• Trustworthy Machine Learning
• Algorithmic Fairness
• Data Privacy
• +7 more

Hui Wang is a Professor and Associate Chair for PhD Studies and Research in the Department of Computer Science at the Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology. She also serves as the Director of the Data Science PhD Program and holds leadership roles in multiple institutional committees, including the Doctoral Committee, Faculty Mentoring Program, and Strategic Planning initiatives at both departmental and university levels. Research Interests: Dr. Wang's research focuses on building trustworthy machine learning systems by integrating privacy, fairness, and accountability . Her work aims to fortify ML models against privacy attacks, eliminate algorithmic biases, and ensure auditable decision-making. She explores intersections between machine learning, data mining, and cybersecurity, with applications across domains requiring ethical and secure AI deployment. Recent Research Trends: Her recent publications and funded projects reflect a strong emphasis on privacy-preserving machine learning , fairness-aware systems , and verifiable computing . Themes include securing graph embeddings, federated learning with fairness guarantees, and audit mechanisms for black-box models. Supported by NSF, Cisco, and Google, her work bridges theoretical rigor with practical system design. Scientific Awards: NSF CAREER Award, 2014 Advising and Grants: Dr. Wang actively mentors PhD students and hosts visiting scholars. She leads multiple NSF-funded projects, including Securing Network Embedding against Privacy Attacks and Privacy for All: Ensuring Fair Privacy Protection in Machine Learning . Her research is supported by substantial grants from the National Science Foundation, Cisco, and Google, reflecting her leadership in trustworthy AI. Labs and Teams: While not explicitly named, Dr. Wang leads a research group focused on trustworthy machine learning, advising students and collaborating with industry partners. She is deeply integrated into the Data Science PhD program and CS faculty leadership, shaping research and academic strategy at Stevens.

Farhad MerchantView profile

Assistant Professor

• Hardware Security
• Neuromorphic Computing
• Algorithm-Architecture Co-design
• +3 more

Dr. Farhad Merchant is an Assistant Professor of Innovative Computer Architecture at the Bernoulli Institute, University of Groningen, since July 2024. Previously, he served as a Lecturer (Assistant Professor) at Newcastle University (2022–2024) and held research roles at Bosch Research, NTU, and RWTH Aachen University. His research focuses on emerging technology-based computing and hardware-oriented security, including neuromorphic architectures, in-memory computing, and secure hardware design. Education: PhD in Electronics Engineering from the Indian Institute of Science, Bangalore, with a DAAD-funded visit to RWTH Aachen University. He also holds industry experience from Bosch Research. Research Interests : - Hardware Security - Neuromorphic Computing - Algorithm-Architecture Co-design - Reconfigurable Computing - Computer Arithmetic Projects : - Coordinator for the REACT project (2025–2029): Focuses on self-aware neuromorphic architectures. - Principal Investigator for Privacy-Preserving Computer Architectures (CogniGron, 2025–2029). - Completed BioNanoLock project (DFG-funded, focusing on bio-nanoelectronic security). Awards : - Best Paper Awards at ISQED 2022, NEWCAS 2023, and VLSI-DAT 2024. - Minerva Fellowship (Technion, Israel), HiPEAC Technology Transfer Award (2019). He co-founded the SeHAS workshop (since 2019) and serves on editorial and program committees for major conferences like DAC, ISLPED, and VLSI-SoC.

Jens KrauseView profile

Professor

• Behavioural Ecology
• Collective Intelligence
• Social Networks
• +7 more

Jens Krause is a Professor and Head of Department at the Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB) in Berlin, leading the Research Group on Mechanisms and Functions of Group-Living. He holds a full professorship in Fish Ecology at Humboldt-Universität zu Berlin, Faculty of Life Sciences, Thaer-Institute, and since 2018 has been an Adjunct Professor at Technical University Berlin within the Excellence Cluster 'Science of Intelligence'. His research is centered on collective intelligence, social networks, decision-making, and behavioural ecology in fish and other animals. Full Professor in Fish Ecology, Humboldt-Universität zu Berlin Adjunct Professor at Technical University Berlin (since 2018) Head of Department, IGB Berlin PhD, University of Cambridge Diploma, Free University Berlin His work integrates experimental biology, network analysis, and biomimetic robotics to understand how animals make collective decisions. His expertise spans animal behaviour, evolution, and ecological physiology, with a strong focus on group-living dynamics. Recent research explores group hunting, predator evasion, social foraging, and the impact of environmental stressors on collective behaviour. The analysis of his recent publications reveals a strong trend in understanding collective behaviour in fish, including escape waves, social foraging, group hunting in marlins and sailfish, and the use of robotic agents to study social integration. His interdisciplinary approach combines marine biology, physics, robotics, and data science to uncover the mechanisms behind collective intelligence in both animal and human systems. Editorial Board, Behavioral Ecology Editorial Board, Fish and Fisheries Executive Board, Excellence Cluster 'Science of Intelligence' Advisory Board, Bimini Biological Field Station Foundation He advises numerous PhD students and postdoctoral researchers, and leads major research projects, including 'Developing exploration behaviour' funded by the Excellence Cluster. His work has been supported by extensive collaborations across Europe and North America, and he frequently publishes in top-tier journals such as Nature , Science Advances , Proceedings of the Royal Society , and Current Biology . His lab employs cutting-edge methods including automated tracking, social network analysis, and interactive robotics to study animal groups. His research group, 'Mechanisms and Functions of Group-Living', is embedded within the Excellence Cluster 'Science of Intelligence', where they investigate collective cognition, social information use, and the role of individual differences in group performance. The team combines field studies with laboratory experiments and computational modelling to understand the evolution and function of collective behaviour across species.

Brian IngallsView profile

Professor

• Systems Biology
• Synthetic Biology
• Mathematical Modeling
• +3 more

Brian Ingalls is a Professor in the Department of Applied Mathematics and cross-appointed to Biology at the University of Waterloo. His research applies mathematical and control-theoretic approaches to biological systems, including genetic regulatory networks, microbial communities, and cellular metabolism. Institutional Affiliation: Faculty of Mathematics, University of Waterloo Contact: bingalls@uwaterloo.ca His work focuses on systems biology and synthetic biology , particularly sensitivity analysis of biochemical networks, optimal experimental design, and mathematical modeling of cellular processes. Research funding comes from NSERC and CIHR . Notable contributions include the textbook Mathematical Modeling in Systems Biology (MIT Press, 2013) and the Ingalls Quantitative Cell Biology Lab , which investigates intracellular and intercellular network dynamics through computational and experimental methods. Key Collaborations: iGEM Waterloo, Chemical Engineering, and international synthetic biology networks Advising: Mentored 15+ graduate students and postdocs across applied math, biology, and engineering fields

Anomadarshi BaruaView profile

Assistant Professor

• System Design and Security
• Healthcare Assistive Systems
• Industrial Control Systems (ICS)
• +5 more

Anomadarshi Barua is an Assistant Professor in the Department of Cyber Security Engineering at George Mason University, leading the System Design and Security research group. His work spans hardware-software co-design for securing cyber-physical systems (CPS), robotics, and sensors. Prior Affiliation: PhD from University of California, Irvine (2023) Industry Experience: Intel Corporation, Solidigm, Nordic Semiconductor, IDEAS Research Themes: Focuses on multimodal system security (audio, visual, electromagnetic data), analog-digital signal integrity, and quantum-inspired defenses in CPS. Key applications include healthcare systems, smart grids, and industrial control systems (ICS). Recent ACSAC 2024 paper acceptance Best Paper Award at ACSAC 2022 NSF panel reviewer (2024) Labs & Collaborations: Collaborates with University of Louisville on robotics and works on Commonwealth-funded UG research (2024). Publications in ACM CCS, USENIX, CHES, and IEEE Transactions (TDSC, TIFS).