Find Academic Supervisors

CHENG Shih-FenView profile

Associate Professor

• Artificial Intelligence
• Data Science
• Decision Making & Optimization
• +5 more

CHENG Shih-Fen is an Associate Professor of Computer Science at Singapore Management University (SMU) and a Principal Research Scientist at Amazon. He holds a PhD in Industrial and Operations Engineering from the University of Michigan and a BSE in Mechanical Engineering from National Taiwan University. His research focuses on modeling and optimization of complex systems in urban computing, decision-making, and transportation, with notable contributions to taxi fleet management, ride-hailing systems, and sustainable logistics. Research interests include Artificial Intelligence , Decision Optimization , Machine Learning , and Urban Sustainability . Notable achievements include prestigious awards from CIKM, AAMAS, and INFORMS. He has advised students such as Qian Shao and Pang Jin Tan, who received SMU Presidential Doctoral Fellowships. Key contributions include the Driver Guidance System (DGS) for taxis and patented taxi demand prediction models. Publications span top venues like IJCAI, AAAI, and Transportation Science. He is a Senior Editor of Electronic Commerce Research and Applications and actively contributes to professional communities like INFORMS and AAAI.

• Renewable Energy Systems
• Thermal Energy Storage
• Building Energy Efficiency
• +4 more

Professor Zhenjun Ma is a Professor and Deputy Director of the Sustainable Buildings Research Centre (SBRC) at the University of Wollongong. He holds a PhD from The Hong Kong Polytechnic University and has expertise in renewable energy systems, thermal energy storage, and building energy efficiency. His research focuses on advancing sustainable HVAC solutions, building control optimization, and demand flexibility in energy systems. He has received prestigious awards including the World Society of Sustainable Energy Technologies Innovation Award and Excellence in HVAC&R Research from AIRAH. Education: BEng and MSc from Xian Jiaotong University; PhD from Hong Kong Polytechnic University. Current academic roles include editorial board memberships in journals like Renewable Energy and Energy Conversion and Management , and leadership in initiatives like the NSW Decarbonisation Innovation Hub. Research Interests: Renewable energy integration in buildings, thermal storage technologies, data-driven building analytics, and grid-to-building energy systems. Active in over 40 funded projects, including grants from Australia's Department of Industry and the NSW Government. Awards: Invitational Fellowship from Japan Society for the Promotion of Science (2025), Fellow of AIRAH (2021), and multiple best paper awards. Supervises over 30 PhD/Master’s students on topics like energy flexibility optimization and net-zero building systems. Labs/Teams: Leads SBRC’s energy efficiency and sustainability research clusters. Collaborates with industry partners like BlueScope Steel on solar energy solutions.

Tom van WoenselView profile

Professor

• Freight Transport
• Logistics
• Operations Research
• +5 more

Tom van Woensel is a Full Professor of Freight Transport and Logistics at Eindhoven University of Technology (Netherlands), affiliated with the School of Industrial Engineering and Innovation Sciences and the Department of Operations Planning Accounting & Control. He also holds roles as Academic Director of the Global Supply Chain Management program at Antwerp Management School and Director of the European Supply Chain Forum. His research focuses on freight transport, logistics systems, and operations research methodologies, with contributions to over 150 peer-reviewed publications in journals like Transportation Science and European Journal of Operational Research . Education: BSc/MSc in Applied Economic Sciences (Econometrics), University of Antwerp (Belgium) PhD: Queueing Theoretical Approaches for Traffic Flow Networks, University of Antwerp Research Interests: Optimization of transport and logistics networks using integer programming, metaheuristics, and reinforcement learning Urban freight systems, last-mile delivery, and sustainable logistics Supply chain resilience, collaboration in logistics networks, and industry-academia partnerships Applications of AI in solving stochastic transportation problems Awards and Recognition: Outstanding Professor in Supply Chain & Logistics (2021) European Journal of Operational Research Best Review Paper (2016) INFORMS Senior Member (2024) Collaborations and Projects: Leads initiatives like SYNERCIZE (zero-emission construction logistics) and Circulaire stromen (circular logistics) Editorial roles at Transportation Science , OR Spectrum , and Urban Science Active in industry partnerships through the European Supply Chain Forum (75+ multinationals) Labs/Teams: EAISI Mobility (Eindhoven AI Systems Institute) CIRRELT (Montreal, Canada) collaborating member

Mehdi DastaniView profile

Professor

• Artificial Intelligence
• Multi-Agent Systems
• Formal Methods in AI
• +5 more

Prof. Mehdi Dastani is a Professor and chair of the Intelligent Systems group within the Department of Information and Computing Sciences at Utrecht University's Faculty of Science. He leads the Master's program in Artificial Intelligence and focuses on formal and computational models in AI, particularly multi-agent systems. His research integrates insights from philosophy, psychology, and law to develop autonomous agents that reason about social and cognitive concepts like norms, emotions, and responsibility. Dastani has held academic roles at Utrecht University since 2001, including postdoctoral research and faculty positions. Education: M.Sc. Computer Science (University of Amsterdam, 1991), M.Sc. Philosophy (University of Amsterdam, 1992), Ph.D. in Humanities (University of Amsterdam, 1998). His work spans theoretical and applied projects, including grants for initiatives like Golden Agents (simulating Golden Age creative industries) and traffic control systems using virtual organizations. He is actively involved in academic committees, editorial boards, and organizing international conferences like AAMAS and PRIMA. Research Interests: Multi-Agent Programming, Normative Systems, Autonomous Agents, Cognitive Robotics, and Human-Centered AI. His projects address challenges like norm enforcement, decision-making in complex systems, and ethical AI integration with societal needs. Advising & Grants: Supervised numerous PhD students (e.g., Birna van Riemsdijk, Bas Testerink) and secured grants for projects such as 'Controllable AI: Human-Centered Approach'. His work includes collaborations on urban governance, autonomous driving, and AI tools for literacy support in children. Labs & Teams: Leads the Intelligent Systems group, contributing to agent-based simulations, ethical AI frameworks, and interdisciplinary collaborations with social scientists and urban planners.

• Mobile Generative AI
• Edge General Intelligence
• Quantum Computing and Networking
• +3 more

Roles & Affiliations: Professor and President's Chair Professor in Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. Member of the IEEE and IET, with roles in editorial boards of major journals like IEEE Transactions on Network Science and Engineering and IEEE Communications Surveys & Tutorials. Current positions: Editor-in-Chief of IEEE Transactions on Network Science and Engineering, Area Editor in multiple journals including IEEE Communications Surveys and Tutorials. Education: Ph.D. (2008) and M.Sc. (2005) in Electrical and Computer Engineering from the University of Manitoba, Canada. B.Eng. (1999) in Computer Engineering from King Mongkut's Institute of Technology Ladkrabang, Thailand. Research Interests: Focuses on mobile generative AI, edge general intelligence, quantum networking, incentive mechanisms, and wireless communication systems. Explores applications in 6G, IoT, UAV networks, and secure communication. Recent Articles & Trends: 15 most recent articles highlight advancements in generative AI for wireless networks, quantum computing integration, secure communication protocols, and AI-driven network optimization. Key themes include semantic communication frameworks, RIS-aided systems, and federated learning in edge networks. Awards: Over 20+ prestigious awards including IEEE Fellow (2017), IET Fellow (2022), Stuart Meyer Memorial Award (2024), and multiple best paper awards at top conferences like IEEE WCNC and IEEE ICC. Advising & Grants: Advisor to numerous students (not listed explicitly). Active in funding initiatives for AI in wireless systems, quantum networks, and low-altitude economy networking. Leads projects on GenAI for networking and 6G innovations. Labs & Teams: Research focuses on CCDS labs at NTU, collaborating on projects like GenAI for ISAC, mobile edge computing, and secure federated learning systems.

Yinglong HeView profile

Lecturer

• Intelligent Transportation Systems
• Energy Management & Decarbonisation
• Vehicle & Powertrain Dynamics
• +7 more

Dr. Yinglong He is a Lecturer in Automated Electrified Transport (AcT) Systems at the School of Mechanical Engineering Sciences, University of Surrey, UK, and an Honorary Assistant Professor at the School of Engineering, University of Birmingham. His research focuses on intelligent transportation systems, energy management, vehicle dynamics, and AI-driven optimisation. He has held positions including Postdoctoral Research Associate at the University of Cambridge and Technology Expert at the European Commission's Joint Research Centre (JRC). Research interests include autonomous vehicle control, traffic simulation, hybrid/electric vehicle dynamics, and sustainable transport solutions. Notable contributions include advancing microscopic traffic models for automated vehicles and optimising energy systems for hybrid powertrains. His work integrates machine learning, multi-agent systems, and data-driven approaches to address challenges in transport decarbonisation and safety. Recent publications highlight advancements in hybrid vehicle dynamics simulation, lithium-air battery modelling, and energy mapping of urban buildings. He has received the Chinese Government Award for Outstanding Self-Financed Students (2022) and is a Fellow of the Institute for Sustainability (IfS). His expertise spans interdisciplinary collaborations in automotive engineering, energy systems, and smart infrastructure.

Akshay KrishnamurthyView profile

Adjunct Assistant Professor

• Machine Learning
• Statistics
• Reinforcement Learning
• +4 more

Akshay Krishnamurthy is an Adjunct Assistant Professor at the University of Massachusetts Amherst and a Senior Principal Research Manager at Microsoft Research NYC. His research focuses on machine learning and statistics, particularly interactive learning frameworks, reinforcement learning, and generative AI. He holds a PhD from Carnegie Mellon University and a B.Sc. from UC Berkeley. Education: PhD in Computer Science, Carnegie Mellon University (2015) B.Sc. in Electrical Engineering and Computer Science, UC Berkeley (2010) Research Interests: His work emphasizes feedback-driven data collection in machine learning, including contextual bandits, reinforcement learning, and their applications to language models and generative AI. Recent focus areas include sample-efficient exploration and decision-making under limited feedback. Awards: National Science Foundation Graduate Research Fellowship (2010) Best Student Paper Award at Asilomar Conference (2013) Grants & Collaborations: Active in interdisciplinary collaborations, including organizing workshops on foundations of post-training in generative AI. His research bridges theoretical guarantees with practical applications in reinforcement learning and decision-making systems. Labs/Teams: Leads research initiatives at Microsoft on generative AI, reinforcement learning, and scalable machine learning systems.

• Structural Engineering
• Architectural Science
• Building Energy Management
• +3 more

Professor Gianluca Ranzi is a Professor in the School of Civil Engineering at the University of Sydney, serving as Chairman of the Centre for Advanced Structural Engineering. His expertise spans structural engineering, architectural science, and heritage conservation, with a focus on sustainable building technologies. He leads research on composite materials, energy-efficient structures, and the mitigation of urban heat islands. Research Interests: His work addresses the behavior of concrete and composite steel-concrete structures, building energy management systems, and heritage conservation strategies for twentieth-century concrete structures. He develops adaptive systems to enhance indoor comfort and building functionality while reducing energy consumption. Publications: Ranzi has authored/edited key texts including Design of Prestressed Concrete to Eurocode 2 (2017) and Structural Analysis: Principles, Methods and Modelling (2015). His recent articles explore topics like lithium slag composites, P2P energy trading, and dynamic characterization of historic structures. Teaching: He teaches courses such as CIVL3511/CIVL9511 (Basics of Integrated Building Engineering) and CIVL5531 (Advanced Integrated Building Engineering). Supervises PhD/Master's students on projects like composite brick-concrete construction and crack control in shotcrete linings. Affiliations: Member of Standards Australia committees (BD-002, BD-032), American Concrete Institute (ACI), and the International Association for Bridge and Structural Engineering (IABSE).

Adlen KSENTINIView profile

Professor

• Mobile and Wireless Networks
• Software Defined Networking (SDN)
• Mobile Edge Computing (MEC)
• +7 more

Adlen KSENTINI is a Professor at EURECOM's Communication Systems department, specializing in advanced networking technologies. His research focuses on Mobile and Wireless Networks, Software Defined Networking (SDN), Mobile Edge Computing (MEC), Network Function Virtualization (NFV), and Content Delivery Networks (CDN), with an emphasis on performance evaluation and network virtualization. He has contributed to projects like AC3 and 6G-BRICKS, exploring cloud-edge continuum integration and 6G infrastructure. Key research interests include virtualized mobile core networks, carrier cloud systems, and AI-driven network management. He has received Best Paper Awards at IEEE WCNC 2018 and IWCMC 2016 for works on network slicing and LTE modeling accuracy. His work often integrates machine learning for optimization, sustainability, and security in 5G/6G networks. Distinctions: Two Best Paper Awards Labs/Teams: Involved in EU-funded projects like AC3 and 6G-BRICKS Grants: Not explicitly listed, but active in collaborative research initiatives

• Artificial Intelligence
• Game AI
• Procedural Content Generation
• +4 more

Julian Togelius is an Associate Professor at the Department of Computer Science and Engineering, Tandon School of Engineering, New York University. He co-directs the NYU Game Innovation Lab and serves as Editor-in-Chief of IEEE Transactions on Games. His research focuses on AI techniques for game design and games as testbeds for AI development, including procedural content generation, evolutionary algorithms, and player modeling. He has organized major competitions like the General Video Game AI Competition and the Mario AI Championship. Research Interests: Julian explores AI-driven game design, procedural content generation (PCG), evolutionary computation, and the intersection of games with broader AI challenges. His work spans automatic level design, opponent AI, and using games to benchmark general intelligence. He emphasizes data-driven models of player experience and integrating machine learning into game development. Organizational Activities: He has held roles including General Chair of IEEE Computational Intelligence and Games (2017), co-organizer of the General Video Game Playing Competition, and editor roles in key journals. His work also extends to music generation (MetaCompose) and data-driven game design (e.g., 'Data Adventures' from open datasets). Professional Contributions: Julian has advised numerous PhD students focusing on AI and games, published over 160 peer-reviewed works, and authored/co-authored books like Artificial Intelligence and Games (2018) and Procedural Content Generation in Games (2016). His research bridges academic rigor with practical game development, emphasizing computational creativity and interactive systems.

Donald C. WunschView profile

Professor

• Neural Networks
• Reinforcement Learning
• Adaptive Resonance Theory
• +6 more

Donald C. Wunsch is the Mary K. Finley Missouri Distinguished Professor in Electrical and Computer Engineering at Missouri University of Science & Technology (Missouri S&T), where he directs the Applied Computational Intelligence Laboratory. He previously served as Interim Director of S&T’s Intelligent Systems Center and holds courtesy appointments in Computer Science, Systems Engineering, and Engineering Management. His research focuses on neural networks, reinforcement learning, adaptive resonance theory, bioinformatics, and robotics. Wunsch is an IEEE Fellow, INNS Fellow, and recipient of the 2015 INNS Gabor Award and 2019 Ada Lovelace Service Award. He has led numerous professional organizations, including the INNS Board of Governors and IJCNN conferences. Education: Executive MBA, Washington University in St. Louis (2006) Ph.D. in Electrical Engineering, University of Washington (1991) M.S. in Applied Mathematics, University of Washington (1987) B.S. in Applied Mathematics, University of New Mexico (1984) Research Interests: Donald’s work spans adaptive resonance systems, reinforcement learning architectures, neurofuzzy regression, robotic swarms, and bioinformatics. He emphasizes practical applications in energy systems (e.g., pumped storage hydro optimization), cybersecurity, and medical data analysis. Recent projects include Hamiltonian-driven adaptive dynamic programming and cluster validity indices for streaming data. Awards & Recognition: 2015 INNS Gabor Award INNS Senior Fellow (2007–2013) NSF CAREER Award 2019 INNS Ada Lovelace Service Award Labs & Leadership: As director of the Applied Computational Intelligence Lab, he oversees research in AI/AS applications for critical infrastructure and smart grids. He also chairs the Missouri S&T Information Technology and Computing Committee and actively contributes to interdisciplinary initiatives like the University of Missouri Bioinformatics Consortium.

• Distributed Decision Making
• Cyber-Physical Systems
• Control Systems
• +5 more

Vijay Gupta is the Elmore Professor of Electrical and Computer Engineering and Associate Head of Graduate and Professional Programs at Purdue University's College of Engineering. His research focuses on distributed decision-making systems, combining data-driven and model-driven approaches for infrastructure networks like power grids, transportation systems, and water distribution networks. Key areas include compositional control, cyber-physical security, and incentive design in distributed estimation and control. Education: B.Tech from Indian Institute of Technology Delhi, M.S. and Ph.D. from California Institute of Technology, all in Electrical Engineering. Prior roles include faculty positions at Notre Dame and research roles at United Technologies Research Center. Research emphasizes resilient control strategies for large-scale systems, with recent work addressing secure estimation under adversarial attacks, model reduction techniques, and reinforcement learning frameworks for decentralized control. His publications span control theory, cyber-physical systems, and optimization algorithms. Grants and collaborations are not explicitly detailed here, but his work reflects significant engagement with foundational and applied research challenges in networked systems. No specific awards are listed in the provided texts.

Dongming GanView profile

Associate Professor

• Robotics
• Human-Robot Interaction
• Mechanism Design
• +5 more

Dr. Dongming Gan is an Associate Professor in the School of Engineering Technology at Purdue University, part of the Purdue Polytechnic Institute. His research focuses on robotics, mechanism design, and human-robot interaction, with an emphasis on compliant systems and wearable devices. He holds PhDs in Robotics and Mechatronics from King’s College London and Beijing University of Posts and Telecommunications. Prior roles include postdoctoral work at the Italian Institute of Technology and faculty positions at Khalifa University. He has authored over 130 journal/conference papers and six patents. His work includes advancements in variable stiffness actuators, soft robotics, and sensor integration for safe human-robot collaboration. Notable awards include the 2023 Freudenstein Young Investigator Award (ASME) and ASME Fellow status. Current leadership roles include serving as an Associate Editor for Mechanism and Machine Theory, ASME Journal of Mechanisms and Robotics, and Robotica. He also chairs major conferences like ASME IDETC-CIE 2025 and IEEE/IFToMM ReMAR 2024. Recent grants total over $900K, including NSF funding for variable stiffness actuators and safe human-robot interaction. Research interests span robotics design, industrial automation, and bio-inspired systems. His lab (C3RL) develops innovative robotic solutions for healthcare, manufacturing, and human-robot coexistence scenarios.

Ping WangView profile

Professor

• Chinese Intellectual History
• Literature
• Medieval Philology
• +3 more

Ping Wang is a Professor in the Department of Asian Languages & Literature at the University of Washington, serving as Graduate Program Coordinator and Graduate Admissions & Education Committee Chair. They hold a Ph.D. in Chinese Language and Literature from the University of Washington (2006). Their research focuses on Chinese Intellectual History, Medieval Philology, Poetry and Poetics, and Translation Studies. Recent research trends include interdisciplinary approaches to classical texts and modern translation methodologies. The listed articles highlight contributions to computational linguistics and AI, though primary disciplinary focus remains humanities. No specific awards are listed, though the department's 'Awards & Honors' page may contain institutional recognitions. Advising emphasizes graduate education coordination rather than individual student mentorship. Active in departmental administration and curriculum development. Research affiliations include the Bilingual and Biliteracy Research Lab and the Early Buddhist Manuscript Project. Office located in GWN M246 with regular Thursday office hours.

• Robotics Perception
• Alternative Sensing
• Inertial Fusion
• +6 more

Teresa Vidal-Calleja is an Associate Professor and Research Director at the Robotics Institute, University of Technology Sydney (UTS). She holds a Deputy Head of School (Research) role in the School of Mechanical and Mechatronic Engineering. Her research focuses on robotics perception, alternative sensing, inertial fusion, SLAM, and applications in manufacturing, agriculture, mining, and construction. Education: B.Sc. Mechanical Engineering (UNAM, 2000), M.Sc. Electrical Engineering (CINVESTAV-IPN, 2002), Ph.D. Automatic Control (Polytechnic University of Catalonia, 2007). Postdoctoral Experience: LAAS-CNRS (France), Australian Centre for Field Robotics (Sydney). Research Interests: Teresa’s work spans robotics perception, sensor fusion, autonomous navigation, and collaborative robotics. She leads projects on next-gen infrastructure robotics (ARC Discovery Grant) and is co-lead of the Australian Cobot Centre. Her innovations target hazardous environments, infrastructure maintenance, and human-robot collaboration. Funded Research: Includes grants for robotic sensors, satellite docking systems, and multi-robot collaboration. Recent projects involve Navantia, the NSW Space Research Network, and industry partnerships. Professional Roles: IEEE Senior Member, Treasurer of the Australian Robotics and Automation Association, and Associate Editor for IEEE Transactions on Robotics and other journals. She chairs conferences like the Australasian Conference on Robotics and Automation. Labs/Teams: UTS Robotics Institute, collaborating with global institutions like ETH Zürich and DLR. Her work integrates robotics with industries such as agriculture and construction, emphasizing sustainability and safety.