Find Academic Supervisors

Johannes LercherView profile

Professor

• Catalysis
• Sustainable Energy
• Chemical Engineering
• +3 more

Prof. Johannes A. Lercher is a retired professor (as of April 2023) at the Technical University of Munich (TUM), holding the Chair of Chemical Technology II within the Department of Chemistry. His research focuses on heterogeneous catalysis, particularly understanding catalytic processes at solid-liquid and solid-gas interfaces, with applications in sustainable energy production, CO₂ conversion, and catalytic upcycling of polymers. He has held academic positions at the University of Twente (Netherlands) and the Pacific Northwest National Laboratory (USA), and has been Editor-in-Chief of the Journal of Catalysis . His honors include the Alwin Mittasch Prize (2021), ENI Award (2016), and Kozo Tanabe Prize (2013). His recent work emphasizes low-temperature polymer upcycling, methane activation, and bioinspired catalyst design, leveraging advanced spectroscopic and operando techniques. Despite retirement, his contributions to catalysis research remain impactful. Education: PhD (1980) and Habilitation (1985), Vienna University of Technology Visiting Lecturer, Yale University (1982) Research Interests: Heterogeneous catalysis, catalytic interfaces, sustainable energy carriers, CO₂ valorization, and polymer waste upcycling. Key areas include: Design of catalysts for selective hydrocarbon synthesis Mechanistic studies using advanced spectroscopy Development of scalable catalytic processes for industrial applications Recent Trends in Publications: Focus on low-temperature polymer recycling (e.g., PVC and polyolefin upcycling), methane activation via novel catalysts (e.g., Co 2+ in ZSM-5), and bioinspired catalytic strategies. His work bridges fundamental catalysis with industrial relevance, emphasizing sustainability and energy efficiency. Awards and Recognition: Member, Academia Europaea and US National Academy of Engineering Recipient of multiple international catalysis awards (see full list above) Grants and Labs: Led the Institute for Integrated Catalysis (Pacific Northwest National Lab, 2011–present). His research groups have pioneered studies on zeolite-confined reactions and interfacial catalysis, with collaborations spanning academia and industry. Labs/Teams: Active in the TUM Department of Chemistry and international networks focused on catalytic innovation for a carbon-neutral economy.

Foong ShaohuiView profile

Associate Professor

• Robotics
• Electronics
• Unmanned Aerial Vehicles (UAVs)
• +9 more

Dr. Foong Shaohui is an Associate Professor and Associate Head at the Engineering Product Development (EPD) pillar of the Singapore University of Technology and Design (SUTD), with prior experience as a Visiting Assistant Professor at MIT's Mechanical Engineering department (2011). He leads the Aerial Innovation Research (AIR) Laboratory @ SUTD and actively collaborates with Singapore's Ministry of Defence (MINDEF) and medical institutions like National University Hospital (NUH) and Changi General Hospital (CGH). PhD, MS, and BS in Mechanical Engineering from Georgia Institute of Technology (2005-2010) Research Interests span multiple domains: Robotics & UAVs : Nature-inspired aerial craft design (Project MONOCO), hybrid flight dynamics, and transformable rotorcraft Medical Device Innovation : Magnetic localization systems for nasogastric tubes and ventriculostomy procedures Engineering Education : Design-Centric pedagogy and pre-university Aerial Craft Workshops Autonomous Systems : Deep tunnel sewer inspection drones (NRF/PUB funded) and soft robotics Scientific Contributions include patented magnetic localization technologies (licensed to Medergo Pte. Ltd.), over 20 peer-reviewed publications, and 5 granted patents. His work bridges aerospace engineering with biomedical applications through innovative mechatronic solutions. Best Application Paper Award at SCIS & ISIS (2014) Research Grants include projects funded by Singapore's National Research Foundation (NRF), Public Utilities Board (PUB), and National University Hospital partnerships. He mentors PhD/Master's students through interdisciplinary research in aerial robotics and medical device development.

Xianguo LiView profile

Professor

• Fuel Cells
• Energy Systems
• Thermal Fluid Science
• +7 more

Xianguo Li is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, Canada. He holds prestigious fellowships including Fellow of the Canadian Academy of Engineering (FCAE), Fellow of the Engineering Institute of Canada (FEIC), and Fellow of the Canadian Society for Mechanical Engineering (CSME). His primary research focuses on thermal fluid science, energy systems, and fuel cell technology, with a strong emphasis on green energy solutions. **Education**: 1989: Doctorate in Mechanical Engineering, Northwestern University, USA 1986: Master's in Mechanical Engineering, Northwestern University, USA 1982: Bachelor's in Thermal Energy Engineering, Tianjin University, China **Research Interests**: His work spans fuel cells, spray dynamics, fluid dynamics, heat and mass transfer, power generation, and renewable energy systems. He leads the Fuel Cell and Green Energy Lab, advancing innovations in energy storage, propulsion systems, and sustainable technologies. **Awards**: Outstanding Performance Award (University of Waterloo, 2007) Frank Walk Service Award (2001) Best Paper Award (2003) Recipient of the Simpson Fellowship (1988) **Advising & Grants**: He supervises graduate students and research associates in projects funded by NSERC, Auto 21, CFI, and industry partners. His lab collaborates on fuel cell durability, thermal management, and green energy policy initiatives. **Editorial Roles**: Founding Editor-in-Chief of the International Journal of Green Energy , Field Chief Editor of Frontiers in Thermal Engineering , and serves on dozens of editorial boards. He chairs major conferences like the International Green Energy Conference and the World Fuel Cell Conference series.

Norbert LutkenhausView profile

Professor

• Quantum Communication
• Quantum Key Distribution (QKD)
• Quantum Information Processing
• +4 more

Prof. Norbert Lütkenhaus is a Professor and Executive Director of the Institute for Quantum Computing (IQC) at the University of Waterloo, cross-appointed to the Department of Applied Mathematics. He holds affiliations with Perimeter Institute and the Centre for Applied Cryptographic Research. His research focuses on quantum communication theory, particularly quantum key distribution (QKD) and quantum repeaters. He has pioneered methods to bridge abstract quantum protocols with practical optical implementations, emphasizing secure key rate calculations and overcoming quantum channel limitations. Education: PhD (2003) in Physics from University Erlangen-Nürnberg, MSc (1993) and BSc (1990) from Ludwig-Maximilians-Universität München and RWTH Aachen, respectively. Awards include the 2015 American Physical Society Outstanding Referee Award and a 2009 University of Waterloo Excellence Award. Research interests span QKD protocols (e.g., decoy-state BB84, phase-error mitigation), quantum repeater architectures, and entanglement verification. He develops numerical tools for key rate analysis and addresses implementation security loopholes. His work includes theoretical frameworks for long-distance quantum communication and practical QKD system optimizations. Teaching includes courses on quantum information processing (PHYS 768/QIC 890) and mechanics (PHYS 115). He contributes to international standards via ETSI’s QKD-ISG and the QCrypt steering committee. His patents cover QKD system designs and phase-randomization techniques.

• Service Marketing
• Value Co-Creation
• Relationship Marketing
• +2 more

Christian Grönroos is Professor of Marketing at Hanken School of Economics, recognized among the top marketing researchers globally. His pioneering work established service marketing theory and the service logic paradigm. Research focuses on value co-creation frameworks, relationship marketing evolution, and service-driven business model innovation. Publications have transformed understanding of customer management and service productivity. Awards include the Don Schultz Award (2025) and AMS-Parasuraman Best Paper Award. Recent work examines service-informed marketing reform and employee alignment in brand promise co-creation.

Yongmin LiuView profile

Professor

• Nano Optics
• Nanomaterials Engineering
• Plasmonics
• +5 more

Yongmin Liu is a Professor in Mechanical and Industrial Engineering and Electrical & Computer Engineering at Northeastern University, and a member of the Cross-College Magnetics Center. He holds a PhD in Applied Science and Technology from UC Berkeley (2009), with earlier degrees from Nanjing University. His research focuses on nano-optics, metamaterials, plasmonics, and their applications in optical devices and systems. His interdisciplinary work bridges engineering, physics, and AI, with notable contributions to metasurface design and optical neural networks. Education: PhD, Applied Science and Technology, UC Berkeley (2009) M.S. and B.S., Physics, Nanjing University (2003, 2000) Research Interests: Nano-optics, nanoscale materials engineering, metamaterials, plasmonics, and applied physics. His group develops novel optical materials and devices for applications like super-resolution imaging, efficient light harvesting, and biomedical detection. Recent projects include AI-driven photonic materials design and meta-optical neural networks. Key Achievements: Recipient of the Søren Buus Outstanding Research Award (2024) NSF CAREER Award (2017) and ONR Young Investigator Award (2016) Elected SPIE Fellow (2023) and Optica Fellow (2023) Lab & Collaborations: Head of the Yongmin Liu Research Group, collaborating with institutions like Georgia Tech and Purdue University. Recent grants include a $1.5M NSF DMREF grant for AI-driven photonic materials and a $468K NSF grant for meta-optical neural networks.

Michael UlbrichView profile

Professor

• Nonlinear Optimization
• Optimal Control
• Numerical Analysis
• +3 more

Prof. Dr. Michael Ulbrich is a full professor and Chair of Mathematical Optimization at the Technical University of Munich (TUM), within the School of Computation, Information and Technology. He has held this position since 2006 and previously served as Dean of Studies (2007–2010) and Vice Dean of the Faculty of Mathematics (2012–2015). His research focuses on nonlinear optimization, optimal control, and numerical analysis, with applications in fluid dynamics, shape optimization, and PDE-constrained systems. He leads projects in the DFG SPP 1962 and IGDK 1754, and has received prestigious awards including the Howard Rosenbrock Prize (2015) and the Doctoral Award from the TUM Association of Friends (1996). Ulbrich is Editor-in-Chief of Optimization and Engineering and contributes to multiple journals. His work bridges theoretical foundations and practical applications, including CO2 sequestration, fluid-structure interaction, and distributed optimization algorithms. Education: PhD (1996), Habilitation (2002) in Mathematics at TUM. Research stays at Rice University (USA) under DFG funding. Research Areas: Semismooth Newton methods, PDE-constrained optimization, optimal control of Navier-Stokes equations, and distributed parameter systems. Awards: Rosenbrock Prize, Teaching Excellence Awards, and recognition for doctoral work. Leadership Roles: Department Head of Mathematics (2022–), Member of TUM Senate (2019–2022), and Co-Chair of GAMM 2018. Ulbrich has authored influential textbooks like Semismooth Newton Methods for Variational Inequalities and Nichtlineare Optimierung . His recent projects include OptiGeoS (2024–2026) and collaborations on nonsmooth optimization and stochastic algorithms. His academic contributions span over 100 publications, emphasizing both algorithmic innovation and rigorous mathematical analysis.

LI ZhiView profile

Associate Professor

• Biocatalysis
• Green Chemistry
• Sustainable Manufacturing
• +4 more

Associate Professor LI Zhi leads the Chemical & Biomolecular Engineering Department at the National University of Singapore (NUS). His research focuses on advanced biocatalysis for sustainable manufacturing, bio-based fuels, and functional materials. He holds a PhD in Organic Chemistry from the University of Vienna (1991), an MEng from Chinese Academy of Forestry (1985), and a BSc from Nanjing University (1982). Institutional Affiliations: NUS Faculty of Engineering, NUS ChBE Department. His lab actively collaborates with global institutions like A*STAR and the Singapore Catalysis Society. Research highlights include enzyme engineering for cascade reactions, CO₂ utilization, and biomaterial synthesis. Research Interests: Discovery of novel biocatalysts, engineering of biocatalytic systems, renewable feedstock utilization, and smart material development. Recent work emphasizes cascade biotransformations for chiral chemicals and sustainable processes. Lab Activities: Hosted international conferences (e.g., Southeast Asia Catalysis Conference 2019), collaborations with industry leaders (GSK, Pfizer), and visits from distinguished researchers like Prof. Zhao Huimin. Student milestones include PhD completions (e.g., Wang Wen, Joel Choo Ping Syong) and postdoc contributions across institutions. Grants & Labs: Active in grants related to biocatalysis and green chemistry. Lab members include researchers like Dr. Nicholas Goh and PhD students Li Li. Infrastructure includes advanced facilities for biotransformations and material synthesis.

Thomas BlumensathView profile

Professor

• Signal Processing
• Image Processing
• X-ray Tomography
• +6 more

Professor Thomas Blumensath is a Professor of Signal and Image Processing at the University of Southampton and a Fellow at the Alan Turing Institute. He is the Academic Lead in Image Processing and Reconstruction at the University's μ-VIS X-ray Imaging Centre and Director of Research at the Institute of Sound and Vibration Research (ISVR). His research focuses on advanced algorithms for solving inverse problems in tomographic imaging, combining machine learning, optimization, and statistical methods. Key areas include X-ray tomography strategies, GPU-accelerated reconstruction, and multimodal imaging applications. Education: B.Sc. (Hons) Music Technology and Audio System Design, University of Derby (2002) PhD in Electronic Engineering (Bayesian Signal Processing), University of London (2006) Research Interests: Professor Blumensath's work spans theoretical and applied signal/image processing, with emphasis on tomographic imaging techniques. His current projects address efficient reconstruction methods, spectral X-ray CT, and applications in manufacturing and plant science. He collaborates with advanced imaging facilities like Diamond Light Source and ISIS neutron imaging beamline. Key Contributions: His research bridges computational methods (e.g., compressed sensing) with practical imaging challenges, including limited-angle tomography and stereo imaging strategies. He leads the National Research Facility for Lab X-ray CT and has developed the TIGRE reconstruction toolbox. Grants & Projects: Active funding includes EPSRC projects on tomographic sensitivity monitoring and CT-based manufacturing inspections. Completed projects cover constrained reconstruction, AM process verification, and industrial CT metrology. Awards: Alan Turing Institute Fellowship Teaching & Leadership: He teaches modules on machine learning, biomedical image processing, and robotics. Leads the BEng Control Engineering program at the Joint Education Institute with Harbin Engineering University. Labs/Teams: Active in the Signal Processing, Audio and Hearing research group (SPAH) and the Institute for Life Sciences. Oversees the μ-VIS X-ray Imaging Centre's research initiatives.

Tulika MitraView profile

Professor

• Hardware-Software Co-design
• Real-Time Embedded Systems
• Energy-Efficient Computing
• +7 more

Professor Tulika Mitra is the Dean of the School of Computing and Vice Provost (Special Projects) at the National University of Singapore (NUS). She holds the Provost’s Chair Professor in the Department of Computer Science and has been instrumental in shaping academic policies and strategic initiatives at NUS since joining in 2001. PhD in Computer Science, Stony Brook University (2000) M.E. in Computer Science, Indian Institute of Science (1997) B.E. in Computer Science, Jadavpur University (1995) Her research focuses on hardware-software co-design for energy-efficient computing systems, particularly in real-time embedded systems, heterogeneous architectures, and AI accelerators. She leads major research programs such as the NRF Competitive Research Programme on Low-Power Edge Accelerators and the MOE Tier-3 Programme on Green AI , collaborating with industry leaders like ARM, AMD, and Meta. Her recent publications highlight innovations in CGRA optimization , sparse attention mechanisms , photonic-digital hybrid architectures , and low-power ML inference . These works often integrate compiler techniques, architectural design, and real-time constraints for edge computing applications. Scientific Awards : ESWEEK Test-of-Time Award (2022), ACM SIGDA Distinguished Service Award, IEEE CEDA Outstanding Service Recognition Award, Teaching Excellence Award (2006), and multiple best paper recognitions. Education Leadership : Spearheaded the Computer Engineering (CEG) Programme at NUS, a joint initiative between Engineering and Computing. As a mentor , she has supervised over 25 PhD students , many now in prominent academic or industrial roles. Her research group eCO Lab focuses on embedded computing challenges, while her grant collaborations include projects on 5G base stations, reconfigurable architectures, and IoT-optimized SoCs.

Levent Burak KaraView profile

Professor

• Machine Learning
• Artificial Intelligence
• Computational Design
• +12 more

Levent Burak Kara is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in the Robotics Institute. He is a leading researcher in AI-driven computational design, additive manufacturing, and intelligent engineering systems, leading the Visual Design and Engineering Lab (VDEL) at CMU. Education: B.S., Mechanical Engineering, Middle East Technical University (1998) M.S., Mechanical Engineering, Carnegie Mellon University (2000) Ph.D., Mechanical Engineering, Carnegie Mellon University (2005) His research focuses on integrating machine learning, optimization, and geometric modeling to revolutionize engineering design and manufacturing. Key areas include topology optimization, CAD intelligence, digital twins, generative design, bioengineering, and electronic design automation. His work enables automation of traditionally labor-intensive design processes using deep learning and reinforcement learning. His recent publications reveal a strong trend toward physics-informed surrogate modeling, real-time simulation, manufacturability prediction, and AI-driven automation in mechanical, biomedical, and electronic systems. These works frequently appear in top journals such as Journal of Mechanical Design and Journal of Applied Mechanics , and at premier conferences like NeurIPS and DAC. Scientific Awards: National Science Foundation CAREER Award ASME Design Automation Society Young Investigator Award Google AI for Social Good Impact Scholar Kara advises several Ph.D. students and has secured significant funding from federal agencies such as the NSF and the U.S. Army Research Laboratory, as well as collaborations with industrial leaders including Cadence Design Systems and NVIDIA. His research is also supported by CMU’s NextManufacturing Center and the Critical Technology Initiative. He is actively involved in developing intelligent design systems that leverage AI to automate product design, optimize manufacturing processes, and improve medical diagnostics, particularly in oral cancer screening and organ preservation. His lab, VDEL, is a hub for innovation in AI-enabled engineering.

John F. CannyView profile

Professor

• Artificial Intelligence
• Robotics
• Human-Computer Interaction
• +5 more

John F. Canny is the Paul and Stacy Jacobs Distinguished Professor of Engineering at the University of California, Berkeley, in the Department of Electrical Engineering and Computer Science (EECS). He joined the faculty in 1987 and is affiliated with the Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Center for New Media (BCNM), and other research institutes. His research focuses on artificial intelligence, robotics, human-computer interaction, and computational geometry. Canny is renowned for developing the Canny edge detector and contributions to motion planning, privacy-preserving algorithms, and real-time simulation. Education: B.Sc. in Computer Science and Theoretical Physics (Adelaide University, 1979), B.E. (Hons) in Electrical Engineering (Adelaide University, 1980), M.S. and Ph.D. in Electrical Engineering (MIT, 1983 and 1987). Research Interests: His work spans AI, robotics (including universal planar manipulation), HCI (e.g., MultiView video conferencing), and security (privacy in collaborative filtering). He has pioneered algorithms for edge detection, non-linear FEM simulation, and computational algebra. Awards: ACM Fellow (2020), Okawa Research Grant (2003), AAAI Classic Paper Award (2002), NSF PYI (1989), Packard Fellowship (1988), and ACM Doctoral Dissertation Award (1987). Advising & Grants: Advised over 30 Ph.D. students, many of whom hold prominent roles in academia and industry. His grants include NSF and Packard funding for foundational research in robotics and computational methods. He currently teaches CS188: Introduction to Artificial Intelligence. Labs/Teams: Leads research at the Berkeley Institute of Design (BiD), focusing on RISC robotics, activity-based computing, and privacy-enhanced telepresence systems.

John DeNeroView profile

Teaching Professor

• Artificial Intelligence (AI)
• Computer Science Education
• Data Science
• +3 more

John DeNero is the Giancarlo Teaching Fellow and Associate Teaching Professor in UC Berkeley's Electrical Engineering and Computer Sciences (EECS) department. He joined UC Berkeley in 2014 to focus on undergraduate education in computer science and data science. He teaches and co-develops introductory courses like CS 61A (Computer Science) and Data 8 (Data Science), which serve thousands of students annually. His research spans natural language processing and education innovation, with notable contributions to textbooks like Composing Programs and Computational and Inferential Thinking . Education: Ph.D. in Electrical Engineering and Computer Science, UC Berkeley (2010) M.A. in Philosophy, Stanford University (2002) B.S. in Mathematical & Computational Science and Symbolic Systems, Stanford University (2001) Research interests focus on advancing AI education and curriculum design. His work emphasizes scalability, equity, and student success in large courses. Notable contributions include the Pac-Man projects for AI education and the Berkeley Data Science Education Program. Recent trends in publications highlight AI-assisted education tools, machine translation improvements, and large-scale student feedback systems. Awards include the UC Berkeley Distinguished Teaching Award (2018) and multiple accolades for teaching excellence. Advising and grants: While currently not taking new students, his team supports massive course infrastructures. Labs include the Berkeley Artificial Intelligence Research (BAIR) Lab and contributions to Data Science undergraduate studies.

Qingguo LiView profile

Professor

• Biomechanical system design
• Energy harvesting
• Wearable sensors
• +4 more

Qingguo Li is a Professor and Associate Head at the Department of Mechanical and Materials Engineering , Queen's University , and a member of the Ingenuity Labs Research Institute . He specializes in biomechanical system design, energy harvesting, wearable sensors, gait analysis, and load carriage systems. His research integrates robotics, biomedical engineering, and sensor technology to develop human-centric devices and mobility aids. Current Roles : Professor, Associate Head, Queen's University Research Institute : Ingenuity Labs Research Institute Lab : Bio-Mechatronics and Robotics Laboratory His work focuses on biomechanical energy harvesting , IMU-based motion analysis , and assistive device development . Key applications include stroke rehabilitation, gait monitoring, and wearable power generation systems. Articles span cable-driven robots , smart walkers , and 3D printing mechanisms , emphasizing human-robot interaction and dynamic modeling . The lab explores sensor calibration , adaptive control algorithms , and human movement optimization . Areas of impact include rehabilitation engineering , load carriage stability , wearable sensor accuracy , and assistive robotics . His team develops solutions for gait asymmetry detection , post-stroke mobility , and low-cost energy systems , leveraging machine learning and kinetic modeling .

Alyas WiditaView profile

Assistant Professor

• Urban Design
• Transportation Planning
• Urban Analytics
• +11 more

Dr. Alyas Widita is an Assistant Professor in the Urban Design program at Monash University, Indonesia. He is actively involved in research and teaching, focusing on urban planning, transportation, and smart city technologies. He serves as the Program Coordinator for Urban Design and teaches courses such as Urban Design Studio: Smart City and Smart City Technologies. Education: Ph.D. in City and Regional Planning, Georgia Institute of Technology, United States Dr. Widita's research centers on the built environment, transportation systems, and urban analytics, with a strong emphasis on developing Asian cities. His work explores congestion impacts of mass transit, ride-hailing effects on vehicle ownership, rural-urban migration, walking behavior, and spatial patterns of MSMEs. He employs advanced data analytics and causal evaluation methods to inform urban policy. His recent publications span high-impact journals such as Transport Reviews , Journal of Planning Education and Research , and Travel Behaviour and Society . The research trend shows a consistent focus on data-driven urban policy, sustainable mobility, and equity in urban development across Indonesia and Southeast Asia. Scientific Awards and Recognition: No specific awards listed, but research widely cited and featured in media outlets. Dr. Widita has secured and contributed to multiple research projects funded by international and national agencies, including the World Bank, Korea Transport Institute (KOTI), Central Bank of Indonesia, and Georgia Department of Transportation. He is currently leading or co-leading projects on Jakarta’s subsidence, flood risk management using remote sensing, and the Citarum River revitalization. He collaborates extensively with researchers across disciplines and institutions. His work contributes to UN Sustainable Development Goals, particularly those related to sustainable cities and communities. He is accepting PhD students interested in the built environment, transportation, and urban analytics in developing Asia. He is involved in key labs and research teams including the Citarum Action Research Program (CARP), Intelligent and Dynamic Remote Sensing for Flood Risk, and interdisciplinary urban analytics initiatives at Monash Indonesia.