Find Academic Supervisors

Theo ArentzeView profile

Professor

• Spatial Choice Behavior
• Decision Support Systems
• Activity-Based Modeling
• +9 more

Theo Arentze is a Full Professor at Eindhoven University of Technology (TU/e) in the Department of the Built Environment, leading the Real Estate Management and Development group. He is affiliated with EAISI Health and EAISI Mobility research institutes. Education: MSc in Psychology (Cognitive Psychology & AI) from Groningen University, PhD from TU/e Urban Planning Research: Spatial choice behavior, decision support systems, activity-based modeling, agent-based simulation His research integrates bounded rationality into spatial choice models to enhance behavioral realism, with applications in real-estate management , neighborhood development , healthy cities , and hybrid work environments . Recent work includes child-friendly urban planning and energy-efficient housing impacts . Prominent article themes include: Hybrid work location decisions Urban public space affective experiences Child friendliness in residential choices Sustainable energy preferences Spatial decision support systems Social network modeling Scientific recognition includes: Best Poster Award (2025) - Computational Urban Planning Conference Long Paper of Distinction (2021) - Healthy Buildings Europe EuroFM Best Paper Award (2017) Pyke Johnson Award (2016) As an educator, he teaches courses in Urban Planning , Housing Economics , and Quantitative Research Methods . His multidisciplinary team combines expertise from psychology, sociology, and urban economics to create high-quality built environments through behavioral research.

Roy DongView profile

Assistant Professor

• Control Theory
• Cyber-Physical Systems
• Machine Learning
• +7 more

Roy Dong is an Assistant Professor at the University of Illinois at Urbana-Champaign, affiliated with the Coordinated Science Laboratory. His research bridges Control Theory Economics Statistics Optimization to address challenges in cyber-physical systems and the Internet of Things, focusing on data manipulation, privacy, and strategic behavior in interconnected systems. His academic journey includes a Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley (2017) and dual B.S. degrees in Economics and Computer Engineering from Michigan State University (2010). At Illinois, he teaches courses ranging from Control Systems to Convex Optimization , with multiple teaching excellence awards. Roy's research explores Closed-loop effects of machine learning Causality in decision systems Incentive design for strategic agents Privacy-utility tradeoff optimization Human behavior modeling with applications in smart grids, transportation networks, and semi-autonomous vehicles. His work formulates privacy-preserving mechanisms as optimization problems, balancing data utility against user privacy in dynamic systems. Article trends show expertise in Game theory for strategic data sources Energy disaggregation techniques Nonlinear basis pursuit algorithms Privacy-aware control systems with a focus on cyber-physical systems and human-in-the-loop applications. Scientific recognition includes 'Teacher Ranked as Excellent' awards (ECE 120, ECE 486, ECE 515) Contributions to smartSDH building control and CPRL compressive sensing Roy leads the Privacy-aware Control Systems research group, collaborating with institutions like UC Berkeley and Michigan State University , and directs projects funded by grants including the New USDA NIFA grant for agricultural robot autonomy .

Shuang (Cynthia) CuiView profile

Assistant Professor

• advanced thermal energy storage materials and systems
• intelligent soft materials and devices
• nanoscale heat transfer and energy conversion
• +3 more

Dr. Shuang (Cynthia) Cui serves as Assistant Professor of Mechanical Engineering in the Erik Jonsson School of Engineering and Computer Science at The University of Texas at Dallas, holding a joint faculty appointment at the National Renewable Energy Laboratory (NREL). Awarded the Eugene McDermott Distinguished Professorship in 2017, she pioneers research in energy-efficient materials and systems for sustainability. Her academic foundation includes: PhD from University of California, San Diego (2018) Master of Science in Thermal Engineering from Wuhan University Bachelor of Science in Energy Systems and Power Engineering from Wuhan University Dr. Cui's research targets critical energy challenges through advanced materials innovation. She develops polymeric desiccants for building humidity control that reduce air-conditioning energy use, and novel paper-drying methods achieving 60% energy savings in manufacturing. Her work spans thermal energy storage, nanoscale heat transfer, and grid-interactive building technologies, directly addressing global energy consumption in buildings and industrial processes through intelligent materials design. Her distinguished recognition includes: Eugene McDermott Distinguished Professorship for early-career research excellence NREL President’s Award for Exceptional Performance 2024 UTD Recognition of Outstanding Achievement in Research Research funding flows from the National Science Foundation, U.S. Department of Energy, Department of Defense, and private sector partners. She mentored the student team winning DOE’s 2024-2025 JUMP into STEM competition for wood pulp-based energy-saving building materials. Her collaborative work extends through UT Dallas’ Batteries and Energy to Advance Commercialization and National Security center and the U.S. Department of Energy’s Energy Earthshot Research Centers, driving translational sustainability solutions.

• EEG Signal Processing
• Brain-Computer Interfaces
• Artificial Intelligence
• +5 more

Marta Molinas is a Professor at the Department of Engineering Cybernetics within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). Her research spans multiple interdisciplinary domains with a focus on EEG technology and brain-computer interfaces. She actively supervises numerous Master's projects and maintains extensive international collaborations with institutions including Kavli Institute for Systems Neuroscience, RIKEN Center for Brain Science, University of Tsukuba, Juntendo University, and several European universities. Professor Molinas' research interests center on developing innovative EEG technologies, particularly her FlexEEG concept for reduced-channel EEG systems with brain imaging capabilities. Her work integrates signal processing, artificial intelligence, and neuroscience to create practical applications in mental health, sleep research, neurorehabilitation, and human-computer interaction. She specializes in EEG source imaging, machine learning for brain signal analysis, and the development of brain-computer interfaces for various applications including locked-in syndrome communication, ADHD treatment, and driver monitoring systems. Her publication portfolio demonstrates strong trends in interdisciplinary research combining neuroscience with electrical engineering and artificial intelligence. The work shows particular emphasis on developing practical EEG-based systems that minimize invasiveness while maintaining analytical power, with applications spanning healthcare, rehabilitation, and human augmentation. Her research bridges theoretical signal processing with real-world implementations through numerous student projects and international collaborations. Professor Molinas actively supervises a large team of Master's and PhD students across multiple projects, with each project typically requiring two students working collaboratively. Her research is supported through numerous international collaborations with institutions in Japan, India, and Europe, indicating substantial research funding and project leadership. She has developed a pipeline of student projects that build upon previous work, creating a cumulative knowledge base within her research group. She leads the EEG ITK research team at NTNU, which focuses on developing the FlexEEG headset prototype featuring flexible, wireless, dry electrodes designed to move across the scalp. This team works at the intersection of neuroscience, electrical engineering, and computer science, developing applications for sleep research, mental health monitoring, neurorehabilitation, and brain-computer interfaces. The team collaborates extensively with international partners including the Kavli Institute for Systems Neuroscience, the International Institute of Integrative Sleep Medicine at University of Tsukuba, and several engineering departments across Europe and Asia.

Brad HayesView profile

Associate Professor

• Collaborative Robotics
• Human-Robot Interaction
• Artificial Intelligence
• +5 more

Brad Hayes is an Associate Professor of Computer Science at the University of Colorado Boulder within the College of Engineering and Applied Science, where he directs the Collaborative AI and Robotics (CAIRO) Laboratory. He also serves as Chief Technology Officer at Circadence, leading efforts in developing AI-enabled products for cybersecurity training and assessment. Undergraduate degree from Boston College PhD in Computer Science from Yale University Postdoctoral Associate at MIT Professor Hayes' research focuses on developing techniques that enable autonomous agents and robots to learn from and collaborate with humans safely, reliably, and productively. His work occurs at the intersection of pervasive and personalized artificial intelligence, human-robot teaming, and decision support. He has made significant contributions to collaborative robotics, dependable explainable AI, and imitation learning, with applications spanning manufacturing, healthcare, disaster response, autonomous vehicles, and space exploration. His recent publications reveal a strong emphasis on human-robot interaction, with particular focus on improving predictability in collaborative tasks, developing explainable AI systems that build trust, leveraging augmented and virtual reality for enhanced collaboration, and creating more efficient learning algorithms from human demonstrations. His work increasingly integrates large language models and advanced neural network architectures while maintaining a strong human-centered design approach. Sustainability Recognition (2025) for computational efficiency in motion planning Best Student Paper Runner-up at AAMAS 2022 Nominated for Best Technical Paper at HRI 2024 Best Technical Paper Runner-up at HRI 2019 Hayes has successfully mentored numerous graduate students through the CAIRO Lab, including multiple PhD graduates in 2024 alone. His lab receives funding from various organizations supporting research in human-robot interaction and collaborative AI. He frequently collaborates with industry partners and has established connections with major technology companies through his research and speaking engagements. The CAIRO Lab, under Hayes' direction, is a vibrant research environment focused on turning theoretical concepts into practical applications through hands-on work with real robots and human participants. The lab's research spans multiple domains including manufacturing, disaster response, autonomous vehicles, and space exploration, with a consistent emphasis on safe and effective human-machine teaming.

• Power Grid Planning
• Electricity Market Modeling
• Renewable Energy Integration
• +4 more

Anh Tuan Le is an Associate Professor at the Department of Electrical Engineering, Chalmers University of Technology. He holds a PhD in Power Systems from Chalmers (2004) and a Master's in Energy Economics from the Asian Institute of Technology (1997). Specializes in power grid planning, electricity market modeling, and renewable energy integration Active in electric vehicle-grid interaction and battery storage systems Develops voltage stability solutions and decentralized control strategies His recent research focuses on: Flexibility markets for congestion management Machine learning applications in load forecasting Real-time security margin control using AI Key projects include: DigiRES (2024-2027): Digital integration of multi-energy flexibility POTENT-X (2024-2027): Port energy transition hubs FLEXIGRID (2019-2023): Distribution grid flexibility solutions

Harald RohracherView profile

Professor

• Sociotechnical transitions
• Climate change
• Sustainable development
• +9 more

Harald Rohracher is a Professor at the Department of Theme (TEMA) , Linköping University , affiliated with the Theme Technology and Social Change (THEME) . His research focuses on sociotechnical transitions for climate-neutral cities , examining energy systems, digitalization, and governance strategies. Grants: Formas, Horizon Europe, Vinnova Labs: STRIPE (Sociotechnical Research on Infrastructures, Politics, and Environment), Biogas Solutions Research Center Students: Adam Svensson, Stella Huang, Gavin Nilsson Lewis, Giorgi Kankia Rohracher investigates how households , social movements , and policy frameworks interact in transformative processes. His recent work explores smart grid politics , decentralized energy systems , and urban food digitalization , emphasizing power dynamics and governance experiments. He leads projects on transdisciplinary education for climate governance, positive energy districts , and collective experimentation across Sweden and Spain. His scientific grants highlight institutional support for sustainability research, while his research teams bridge academic, governmental, and civil society actors.

• Earthquake Engineering
• Structural Dynamics
• Seismic Risk Assessment
• +3 more

Prof. Dr. Hakkı Polat Gülkan is a Professor at Başkent University's Civil Engineering Department. With a PhD (1971) and Master's (1968) from the University of Illinois in Civil Engineering and a Bachelor's (1966) from METU, his career spans over five decades in earthquake engineering, structural dynamics, and disaster management. PhD: University of Illinois, Civil Engineering (1971) Master's: University of Illinois, Civil Engineering (1968) Bachelor's: Middle East Technical University, Civil Engineering (1966) His research focuses on seismic risk assessment, structural behavior under extreme loads, and disaster mitigation strategies. Key contributions include earthquake simulator development, ground motion analysis, and retrofitting techniques for masonry and reinforced concrete structures. He has published extensively on deformation limits, response spectra, and historical building preservation. Recent work includes 15+ articles from 2024-2012 analyzing Istanbul's seismic hazards, Marmara region dynamics, and post-earthquake structural integrity. Conference papers address Turkey's endemic building vulnerabilities and deformation thresholds for seismic isolation systems. Scientific Achievements: Elected to U.S. National Academy of Engineering (2023) As an active journal reviewer for 13+ publications (2023-2024), he contributes to advancing earthquake engineering discourse. His teaching portfolio includes advanced structural analysis, concrete mechanics, and seismic design courses.

• Homomorphic Encryption
• Big Data Analysis
• Database Systems
• +6 more

Hayato Yamana serves as Professor at Waseda University's Faculty of Science and Engineering and concurrently holds the position of Vice President for IT Promotion and Chief Information Officer since October 2020. His academic journey began with a Dr. Eng. degree from Waseda University in 1993, followed by positions at the Electrotechnical Laboratory of MITI, before joining Waseda University as Associate Professor in 2000 and becoming full Professor in 2005. He has held significant leadership roles including Director of the Database Society of Japan and the Information Processing Society of Japan, as well as Vice Chair of IEICE's Information and Communication Society. Waseda University, Faculty of Science and Engineering (2005-Present) National Institute of Informatics, Visiting Professor (2005-Present) Waseda University, Vice President for IT Promotion (2020-Present) Deputy Chief Information Officer (2015-2020) His research spans homomorphic encryption, big data analysis, and computer architecture, with notable contributions in privacy-preserving computation, recommender systems, and secure data processing. His work bridges theoretical cryptography with practical applications in smart cities, healthcare, and e-commerce security. Recent publications demonstrate strong focus on accelerating homomorphic encryption operations, improving recommendation system diversity, and developing novel authentication mechanisms. Analysis of his 15 most recent publications reveals consistent emphasis on privacy-preserving technologies (particularly homomorphic encryption applications), innovative recommender system architectures, and biometric security solutions. His research group produces highly cited work at the intersection of cryptography, machine learning, and systems security, with practical implementations in real-world scenarios including smart grids, e-commerce, and healthcare. Fellow, Information Processing Society of Japan (IPSJ), 2020 Golden Core Award, IEEE Computer Society, 2018 Fellow, Institute of Electronics, Information and Communication Engineers (IEICE), 2018 IBM Faculty Award, 2009 Multiple Best Paper Awards from IEICE, IPSJ, and ITE Yamana has secured substantial research funding for projects in homomorphic encryption, smart city infrastructure, and privacy-preserving systems. His leadership extends to advising numerous doctoral students and directing major research initiatives including the Smart Systems and Services Innovative Professional Education Program. He maintains active collaborations with industry partners through projects involving secure computation and data analytics. His research group operates at the forefront of secure computing, with specialized laboratories focused on homomorphic encryption acceleration, privacy-preserving machine learning, and secure mobile authentication. The team actively develops practical implementations of cryptographic protocols for real-world applications in healthcare, finance, and smart city infrastructure, bridging theoretical cryptography with deployable security solutions.

• Computational Fluid Dynamics (CFD)
• Wave Hydrodynamics
• Wave Modeling
• +9 more

Hans Bihs is a Professor in the Department of Civil and Environmental Engineering, Faculty of Engineering. His research focuses on computational fluid dynamics (CFD), wave hydrodynamics, and wave-structure interaction using the open-source framework REEF3D. Key Research Areas: CFD simulations, wave modeling, floating body dynamics, ocean wave energy, aquaculture hydrodynamics, sediment transport, and high-performance computing. Projects: ERC Consolidator Grant PARTRES (2023-2028), EEA Grants Portugal SurfWave (2023), NFR KPN IPIRIS (2021-2025), EEA Baltic SolidShore (2021-2024), NTNU's MAPLE (2022-2025), and DigiCoast (2021-2024). Email: hans.bihs@ntnu.no His recent publications (2025-2020) analyze fluid-structure interaction, ship-induced waves, floating offshore wind turbines, submerged vegetation, and coastal structures using advanced CFD techniques. Topics include wave hydrodynamics, turbulence, and numerical modeling for marine and aquaculture systems.

• Artificial Intelligence
• Machine Learning
• Pattern Recognition
• +11 more

Jianhua Zhang is a Professor of Computer Science and founding deputy head of the AI Lab at the Department of Computer Science, OsloMet - Oslo Metropolitan University, Norway. He holds affiliations with the Faculty of Technology, Art and Design. His career includes roles as Scientific Director at Vekia (France), Head of Machine Learning Lab, and Professorships at East China University of Science and Technology and Beijing University of Technology. He has held visiting positions at TU Berlin, TU Dresden, and the University of Catania. Educations: PhD in Electrical Engineering and Information Sciences (Ruhr University Bochum, 2005), Postdoctoral Research at the University of Sheffield (2005-2006). Research focuses on artificial intelligence, computational intelligence, cognitive human-machine systems, neuroergonomics, affective computing, and AI-driven neuroergonomics. Applications span engineering, biomedicine, finance, and business. He has led over 20 large-scale projects and published extensively (4 books, 13 chapters, ~200 papers). Leadership roles include Chair of IFAC Technical Committee on Human-Machine Systems (2017-2023), Vice Chair of IEEE Norway Section, and editorial roles at journals like Frontiers in Neuroscience and Cognitive Neurodynamics . He organized major conferences like IFAC HMS2025 (Beijing) and ICMLT 2024 (Oslo). Awards: Stanford/Elsevier Top 2% Scientists (2023/2024), Senior Research Fellowship (CSC, 2012), Max Planck Fellowship (2011), Shanghai Pujiang Talent (2007), DAAD Scholarship (2002-2004). Grants and advising: PI for 20+ projects, advising PhD students in AI, machine learning, and control systems. Teaching includes courses on computational intelligence, IoT, and fuzzy systems at both undergraduate and graduate levels. Labs/Teams: AI Lab at OsloMet, Machine Learning Lab (Vekia), and collaborations with institutions globally. Current work emphasizes AI ethics, neuroergonomics in smart cities, and adaptive human-machine systems.

• Industrial Automation
• Control Systems
• Machine Learning Applications
• +5 more

Valeriy Vyatkin is a Professor at the Department of Electrical Engineering and Automation, Aalto University. His research focuses on advancing industrial automation, control systems, and their integration with emerging technologies like machine learning and digital twins. He specializes in standards such as IEC 61499, addressing interoperability, formal verification, and performance optimization in distributed automation systems. Key research interests include: Physics-informed machine learning for industrial processes (e.g., steel rolling, reservoir engineering) Formal methods for control system validation and safety-critical applications Development of adaptive automation frameworks for Industry 5.0 challenges, including human-robot collaboration and energy systems Interoperability between legacy and modern industrial standards (OPAS, OPC UA) Recent work emphasizes real-time simulation, FPGA-based control prototyping, and AI-driven solutions for energy efficiency and sustainability in manufacturing, horticulture, and process industries. Publications span topics like robotic walker design, probabilistic model checking, and decentralized learning management systems. He collaborates on EU and industry-funded projects, focusing on digital twin implementation, edge computing, and virtual commissioning. His team develops tools for automated code generation, system migration, and anomaly detection in complex industrial settings.

Li SongView profile

Professor

• Building Energy System Optimization
• HVAC System Fault Detection
• Energy Efficiency Technology
• +3 more

Li Song is a Professor and holds the Lesch Centennial Chair & Lloyd G. and Joyce Austin Presidential Professor at the University of Oklahoma's Aerospace & Mechanical Engineering Department. He leads the Building Energy Efficiency Lab and serves as AME Associate Director for Research. His expertise spans building energy systems, HVAC optimization, and fault detection technologies. Education: Ph.D. (Thermal/Fluid Science, 2004) from University of Nebraska-Lincoln; M.S. (Thermal/Fluid Science, 1996) from Harbin Institute of Technology; B.S. (Thermal Energy Systems, 1993) from Shengyang University of Civil Engineering and Architecture. Research focuses on energy-efficient HVAC systems, fault detection algorithms, and building performance analytics. Notable contributions include the ULEM-FDD system for high-performance buildings and virtual sensor technologies for airflow/water flow measurement. Awards include the ConocoPhillips Energy Prize (2011 finalist) and Bes-Tech Innovation Award (2006). Publications emphasize HVAC control strategies, energy modeling, and IoT-enabled diagnostics. Courses taught include Thermodynamics, Energy Efficient Building Systems Design, and HVAC Systems Engineering.

Navid BayatiView profile

Associate Professor

• Renewable/Hybrid Power Systems
• Protection and Transient Analysis of Power Grids
• Microgrids and Active Energy Networks
• +5 more

Navid Bayati is an Associate Professor at the University of Southern Denmark, affiliated with the Institute of Mechanical and Electrical Engineering and the Centre for Industrial Electronics. He leads the Control and Protection of Smart Grids (CAP-SG) group and focuses on renewable/hybrid power systems, microgrid protection, and grid code compliance. Education: Ph.D. in Power Systems & Microgrid Protection (2020, Aalborg University); M.Sc. in Power Systems (2017, Amirkabir University of Technology) His research spans renewable energy integration , transient analysis , grid interconnection , and digital twin applications . Recent work includes machine learning for carbon emission prediction, fault localization in DC microgrids, and supercapacitor resilience in hybrid systems. Collaborations include projects like IEA Wind Task 50 and RePoSys , addressing grid renovation, life cycle assessment, and digital twin resilience. His teaching portfolio covers power electronics , energy management , and microgrid control .

Donna GreenView profile

Professor

• Environmental Science
• Climate Change
• Air Pollution
• +6 more

Professor Donna Green is an internationally recognized environmental scientist at the University of New South Wales (UNSW), affiliated with the School of Biological, Earth & Environmental Sciences. She holds a PhD from the University of California, Berkeley (2004) and leads multidisciplinary research at the intersection of climate change, energy policy, and air pollution. Her work focuses on balancing improvements in indoor air quality against outdoor pollution sources such as traffic, bushfires, and industry, while addressing increasingly recognized risks from indoor air contaminants including airborne diseases. PhD, University of California, Berkeley (2004) Professor Green's research spans environmental science, climate change impacts, air pollution health effects, renewable energy policy, and environmental justice. Her work demonstrates particular expertise in the health impacts of climate change, with emphasis on vulnerable populations including Indigenous communities. She investigates the synergistic impacts of urban air pollution compounding climate emergencies, and has published extensively on environmental injustice in resource-rich Aboriginal Australia. Her research often bridges scientific findings with practical policy solutions, working collaboratively with engineers, legal practitioners, and public health experts to design evidence-based approaches to environmental challenges. The most recent publications reveal a strong focus on wildfire smoke impacts on health, indoor air quality in educational settings, climate litigation trends, and the intersection of renewable energy development with Indigenous rights. Her work shows increasing attention to the health consequences of climate change, particularly through the MJA-Lancet Countdown reports which document Australia's preparedness (or lack thereof) for climate-related health challenges. There's also a clear trend toward interdisciplinary collaboration, with publications spanning environmental science, public health, engineering, and social justice perspectives. Clean Air Society Australia & New Zealand Innovation & Excellence in Air Quality Award for CleanAir Schools program Professor Green leads the CleanAir Schools program and is currently implementing Fresh Air Innovators in 100 NSW school classrooms. She has secured significant research funding through collaborations with multiple institutions and has supervised numerous students, though specific advisees aren't listed in the provided text. Her research has informed policy discussions on air quality standards, climate adaptation strategies, and environmental justice frameworks. Professor Green directs research teams investigating indoor air quality solutions, climate-health interactions, and renewable energy policy frameworks. Her CleanAir Schools initiative represents a major practical application of her research, translating scientific findings into classroom interventions that protect children from air pollution. She collaborates extensively with engineers, public health experts, and policy practitioners to develop evidence-based solutions to environmental challenges.