Find Academic Supervisors

• Neural Networks
• Genetic Algorithms
• System Identification and Control
• +7 more

FURUZUKI, Takayuki is a Professor at Waseda University's Faculty of Science and Engineering, Graduate School of Information, Production, and Systems. He holds a PhD from Kyushu Institute of Technology and maintains the NCLab research group (http://nclab.w.waseda.jp/nclab/). His professional memberships include the Institute of Electronics, Information and Communication Engineers, Institute of Electrical Engineers of Japan, Society of Instrument and Control Engineers, and IEEE. His educational background includes a PhD in Information Science from Kyushu Institute of Technology (1994-1997), a Master's degree in Electronics Engineering from Sun Yat-Sen University (1983-1986), and a Bachelor's degree in Electrical & Electronic Systems Engineering from Sun Yat-Sen University (1979-1983). Professor FURUZUKI's research spans neural networks, genetic algorithms, system identification and control, complex systems, bioinformatics, and combinatorial optimization. His work integrates soft computing techniques with medical informatics and control systems engineering, developing innovative approaches for problems ranging from brain tumor segmentation to music information retrieval. His research methodology often combines theoretical foundations with practical applications in healthcare, energy systems, and intelligent transportation. His recent publication record shows a strong focus on sequential recommendation systems, graph neural networks for medical imaging, music information retrieval, and power systems analysis. The consistent thread across his work is the application of advanced machine learning techniques to solve complex, real-world problems across diverse domains, with particular emphasis on handling missing data, improving model efficiency, and enhancing prediction accuracy. His scientific achievements have been recognized with several prestigious awards: ISCIIA2008 Excellent Paper Award (2008) Institute of Electrical Engineers of Japan Excellent Paper Award (2001) Guangdong Province Higher Education Science and Technology Progress Second Prize (1991) Guangdong Province Higher Education Science and Technology Progress Second Prize (1989) Chinese Ministry of Education Scientific and Technological Achievements Second Prize (1986) Professor FURUZUKI has maintained continuous research activity since joining Waseda University in 2003, with significant contributions to multiple research projects spanning neural computation, soft computing, and system engineering. His work demonstrates strong international collaboration, with publications involving researchers from various institutions worldwide. His research output includes over 410 papers with 3,623 citations and an h-index of 23 according to Scopus data. The NCLab research group, which he leads, focuses on neural computation and related areas, providing a platform for interdisciplinary research that bridges theoretical foundations with practical applications in healthcare, energy systems, and intelligent transportation. His laboratory environment fosters innovation in machine learning algorithms and their application to real-world problems, with particular emphasis on developing efficient, robust solutions for complex data analysis tasks.

• Biomaterials
• Biomedical Engineering
• Non-clinical testing methodology for Medical Devices
• +3 more

Professor Kiyotaka Iwasaki at Waseda University's Faculty of Science and Engineering is a leading figure in biomedical engineering with a focus on cardiovascular device development , tissue engineering , and regulatory science . His career spans over two decades at Waseda University, including roles as Associate Professor (2006-2014) and positions at Harvard Medical School's Laboratory for Tissue Engineering. Holding a Doctor of Engineering from Waseda, he serves on numerous international regulatory committees and has contributed to ISO/TC194 standards for medical devices. 1993-2002: Waseda University Education in Mechanical Engineering 2001-2004: Research Associate at Waseda University 2004: Research Scientist at Harvard Medical School 2018-Present: Professor at Waseda University His research interests include Non-clinical testing methodologies for medical devices Regulatory science frameworks Tissue engineering for ligament and cardiac applications Cardiovascular biomedical engineering His scientific contributions reveal through Development of decellularized tissue grafts for orthopaedic surgery Innovations in 3D cardiac tissue engineering using fibrin-based cell sheet stacking Pioneering bioresorbable stent technology with magnesium alloys Creation of biomechanical simulators for valvular disease modeling His awards span from the 2021 Japanese Ministerial Science Commendation 2020 JSME Standards Award 2018 ARIA Innovation Award 2001 ASAIO Fellowship While his publications demonstrate expertise in Vascular and cardiac device testing Bioresorbable stent evaluation Machine learning in medical device regulation Decellularized tissue applications

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +5 more

Goran Oreški is an Associate Professor and Head of the Laboratory at the Faculty of Informatics in Pula (University Jurja Dobrile, Croatia), where he has been employed since 2019. He teaches courses on databases, object-oriented programming, data warehousing, and artificial intelligence at both undergraduate and graduate levels. Education: Ph.D. in Informatics (2016), Faculty of Organization and Informatics Industry Experience: 9 years as software architect and programmer in banking sector Research Focus: Artificial Intelligence systems, classical machine learning algorithms, and deep learning architectures. His work bridges theoretical advancements with practical applications in autonomous vehicles, traffic monitoring, and financial risk assessment. Recent Publication Trends: 2023-2025 works emphasize generative AI for synthetic credit data, traffic object segmentation with monocular cameras, and context-aware detection models (YOLO*C). Earlier works focus on genetic algorithms and ensemble learning for imbalanced datasets. Awards: Google RFP Award for autonomous vehicle research Highly Cited Paper (Web of Science, top 1%) Best Paper at CECIIS conference Leadership: Director of FIPU Laboratory since 2022, leading projects like ai.Shuttle (autonomous mini-bus) and CenAI (industry collaboration with Cenosco).

Ruohui ChenView profile

Assistant Professor

• Biostatistics
• Data Science
• Large-scale Healthcare Data Analysis
• +13 more

Ruohui Chen, PhD, is an Assistant Professor in the Department of Preventive Medicine (Biostatistics and Informatics) at Northwestern University's Feinberg School of Medicine, where he develops advanced biostatistical methodologies and leads collaborative research in oncology and chronic disease. His educational background includes: PhD from University of California San Diego (2023) Dr. Chen specializes in large-scale healthcare data analysis, functional/longitudinal data methods, predictive modeling, and causal inference. His collaborative work addresses cancer treatment disparities, Alzheimer's disease mechanisms, kidney disease progression, and activity pattern impacts on health outcomes through rigorous statistical frameworks. His 2025 publications demonstrate cross-disciplinary applications: analyzing socioeconomic factors in bone cancer prognosis, testing physical activity interventions for cardiovascular health in postmenopausal women, evaluating novel lymphoma immunotherapies, and optimizing aspirin dosing for colorectal cancer prevention. These studies consistently bridge methodological innovation with clinical oncology and public health challenges. No major scientific awards are documented in the current profile. Professional activities include editorial board service for Taylor & Francis (2024-present) and American Statistical Association membership (2016-present), with prior leadership as UC San Diego chapter president (2020-2023). Research grant details and student mentorship information are not provided. Dr. Chen operates within collaborative oncology research networks at Feinberg, though specific laboratory structures are not detailed in available materials.

Constantine E. KontokostaView profile

Professor

• Urban Science
• Urban Informatics
• Urban Planning
• +6 more

Constantine E. Kontokosta is Professor of Urban Science and Planning at NYU Marron Institute of Urban Management, Director of Civic Analytics and Urban Intelligence Lab, with cross-appointments at Center for Urban Science and Progress (CUSP) and Department of Civil and Urban Engineering. He serves as affiliated faculty at Wagner School of Public Service and previously held leadership roles including inaugural Deputy Director of CUSP. His educational background includes: PhD, Urban Planning (Minor: Econometrics) from Columbia University MPhil, Urban Planning from Columbia University MS, Urban Planning; Quantitative Analytics from Columbia University MS, Real Estate Finance and Economics from New York University BSE, Systems Engineering - Civil from University of Pennsylvania Kontokosta leverages large-scale data and computational methods to advance urban energy/climate policy, neighborhood dynamics, and bias detection in public decision-making. His research integrates urban planning with data science to develop equitable solutions for sustainable development, with recent projects analyzing COVID-19 disparities through mobility data and creating methods to reduce building emissions. The work emphasizes evidence-based policy, information transparency, and uncovering algorithmic discrimination. His honors include the IBM Faculty Award, UN Data for Climate Action Challenge Award, Goddard Junior Faculty Fellowship, and multiple best paper awards. Key recognitions: 2023 Best Paper Award (ICLR Climate Workshop) 2021 Article of the Year (Journal of American Planning Association) 2017 Microsoft Azure Research Award 2014 IBM Faculty Award 2012 Fellow of Royal Institution of Chartered Surveyors Funded by National Science Foundation, MacArthur Foundation, Sloan Foundation, U.S. Department of Transportation, NYC Mayor’s Office of Sustainability, Lincoln Institute, and HUD, Kontokosta has served on UNEP Sustainable Buildings Council, Royal Institution of Chartered Surveyors Americas Board, and Suffolk County Planning Commission. His entrepreneurial ventures translate research into practical urban solutions. He leads the Urban Intelligence Lab focused on data-driven urban methodologies and Civic Analytics program advancing evidence-based policy through transparent knowledge democratization, with research featured in Nature Communications, PNAS, and major media outlets.

Roman KremsView profile

Professor

• Quantum Physics
• Machine Learning
• Quantum Chemistry
• +3 more

Roman Krems is a Professor and Distinguished University Scholar at the University of British Columbia (UBC) in the Department of Chemistry, with affiliations to the Stewart Blusson Quantum Matter Institute. His research focuses on the intersection of quantum physics, machine learning, and chemistry, particularly in quantum materials and quantum technologies such as quantum computing and sensing. Key Roles: Professor at UBC (2013–present), Distinguished University Scholar (2017–present) Education: Ph.D. from Göteborg University (2002), Postdoctoral Fellow at Harvard-MIT Center for Ultracold Atoms (2003–05) Research Interests include: Quantum machine learning (QML) for solving complex physics problems Quantum scattering theory in electromagnetic fields Applications of quantum computing to chemistry Developing machine learning algorithms for quantum dynamics Recent publications highlight advancements in extrapolating quantum observables, Gaussian process models for collision dynamics, and quantum walks in disordered systems. His work bridges theoretical physics, computational methods, and experimental applications in cold molecule research. Scientific Awards include the UBC Killam Teaching Prize (2017), election as Fellow of the American Physical Society (2015), and the Keith Laidler Award (2013). He has held editorial board positions for journals such as Machine Learning: Science & Technology and New Journal of Physics . Research Group members include graduate students and postdocs working on quantum technologies, machine learning, and molecular scattering. He also contributes to outreach through invited talks and seminars at institutions like MIT and Lawrence Berkeley National Laboratory.

Oliver StaadtView profile

Professor

• Virtual Reality
• Augmented Reality
• Computer Graphics
• +7 more

Prof. Dr. sc. techn. ETH Oliver Staadt is Full Professor of Computer Science and Chair of Visual Computing at the University of Rostock , Germany. Since 2023 he also serves as Director of the Institute for Visual and Analytic Computing within the Faculty of Computer Science and Electrical Engineering . Previously he was Dean (2016–2018) and Vice Dean (2010–2016) of the same faculty. Education Ph.D. in Computer Science, ETH Zürich (2001) M.Sc. in Computer Science, TU Darmstadt (1994) Research Interests Prof. Staadt’s research spans virtual and augmented reality , computer graphics , visualization , telepresence , immersive analytics , and human–computer interaction . A particular focus lies on real-time rendering and display technologies for large high-resolution display systems, depth-image enhancement for RGB-D sensors, and interaction techniques that leverage spatial cognition and eye-tracking. His work is frequently applied to collaborative settings and microgravity environments, including experiments aboard parabolic flights and the International Space Station. Recent Publication Trends Between 2019 and 2021 his output centers on foveated rendering , AR viewpoint guidance , collaborative analytics on wall-sized displays , and embodied interaction metaphors . Earlier work addressed bandwidth-efficient telepresence, depth-image filtering, and physically-based animation. The corpus reveals a steady evolution from fundamental graphics algorithms toward applied immersive systems. Scientific Awards & Honors Fellow of the Eurographics Association Associate Editor, IEEE Transactions on Visualization and Computer Graphics (past) Associate Editor, Computers & Graphics (past) Associate Editor, Computer Animation and Virtual Worlds (past) Associate Editor, Frontiers in Virtual Reality (current) Chair, Expert Group on Virtual & Augmented Reality, German Informatics Society (2013–2020) Advising & Funding He has successfully supervised more than ten PhD graduates whose dissertations range from collision detection and physically-based animation to 3D interaction in microgravity and predictive user modeling. Current PhD researchers include Bipul Mohanto, Mana Takhsha, and Sven Kluge. His projects are supported by national and EU programs such as EVOCATION, SMOOTH, ARGuide, 3DPick, DIVA, and Telepresence. Labs & Teams Prof. Staadt leads the Visual Computing Group at Rostock, operating state-of-the-art facilities including large tiled display walls, VR/AR laboratories, and motion-capture systems. The institute hosts interdisciplinary collaborations with partners in visualization, computer vision, psychology, and aerospace engineering.

Rainer HinzView profile

Senior Lecturer

• Positron Emission Tomography (PET)
• Radiation Therapy
• Neuroinflammation
• +4 more

Dr. Rainer Hinz is a Senior Lecturer in Functional Imaging at the University of Manchester, affiliated with the Division of Informatics, Imaging & Data Sciences within the Research School of Cancer and Enabling Sciences. He specializes in developing and applying positron emission tomography (PET) techniques for radiation therapy monitoring, oncology, neurology, and psychiatry research. Education: Diplom-Ingenieur (Electrical Engineering) from Chemnitz University of Technology (1995) Doktor-Ingenieur (Biomedical Engineering) from Dresden University of Technology (2000) Research focuses on PET methodologies for disease progression monitoring, particularly in Alzheimer’s, multiple sclerosis, and oncological applications. He contributes to advancing PET imaging standards, collaborating on projects like the CRUK Imaging Centres. His work aligns with UN SDGs related to health and innovation. Publications emphasize neuroinflammation biomarkers, PET tracer applications, and imaging analytics. He actively supervises postgraduate research and contributes to interdisciplinary grants and teaching in advanced imaging techniques.

C. Rhett JacksonView profile

Professor

• Water Quality
• Hydrology
• Environmental Engineering
• +4 more

Dr. C. Rhett Jackson serves as the Associate Dean of Academic Affairs and holds the John Porter Stevens Distinguished Professorship in Water Resources at the University of Georgia's Warnell School of Forestry and Natural Resources. His research focuses on the impacts of land use (forestry, agriculture, urbanization) on water quality and aquatic habitats, with particular emphasis on riparian vegetation, stream temperatures, and hydrological processes. He leads trans-disciplinary projects involving collaborators from environmental engineering, ecology, and geology. Education: PhD in Hydrology (University of Washington), MSE and BSE in Environmental Engineering (Duke University). Affiliations: Institute for Resilient Infrastructure Studies (IRIS), River Basin Center, and Coweeta LTER. Research interests include interflow dynamics, nitrogen cycling in mountain catchments, and the effectiveness of best management practices for nonpoint source pollution. He has authored over 100 peer-reviewed articles and has been recognized for his contributions to environmental science through the Distinguished Professor title. Key labs/centers: Water Resources Area, IRIS, and Coweeta LTER. His work bridges basic hydrologic science with applied water resource management, addressing both rural and urban challenges such as bioenergy crop impacts, karst groundwater interactions, and urban stream restoration.

Frederic BoscheView profile

Professor

• Construction Informatics
• Civil Engineering
• Building Information Modeling (BIM)
• +5 more

Dr. Frederic Bosche is a Reader in Construction Informatics at the University of Edinburgh's School of Engineering, leading the CyberBuild Lab. His research focuses on advancing digital construction technologies, including BIM, sensing systems, and digital twinning to enhance infrastructure management and workforce safety. Education: PhD in Civil Engineering (University of Waterloo), M.Sc. from University of Texas at Austin, and M.Eng. from Ecole Centrale de Lille. Research interests include automated construction processes, data-driven infrastructure lifecycle management, and integrating emerging technologies like AI and IoT into construction workflows. His CyberBuild Lab has pioneered projects in defect detection, roof monitoring, and smart construction inspection. Notable contributions include over 100 publications, 12 research projects (e.g., 'Digital Facility' and 'Monitoring Roofs of Traditional Buildings'), and awards such as the Charles M. Eastman Top PhD Paper Award. He actively engages in public outreach through science festivals and collaborates internationally with institutions like ETH Zurich and Heriot-Watt University.

Bruce A. MaxwellView profile

Teaching Professor

• Computer Vision
• Robotics
• Computer Graphics
• +3 more

Bruce A. Maxwell is a Teaching Professor and Assistant Director of Computing Programs at Northeastern University’s Seattle Campus, following roles as Chair of the Computer Science (CS) Department at Colby College (2013–2020) and leadership in establishing the Khoury College MS CS Align Program at the Roux Institute (2020–2022). His academic journey includes affiliations with Northeastern’s Seattle Campus and ongoing collaboration with Colby CS as a research scientist. He specializes in Computer Vision, Robotics, Computer Graphics, Game Design, and Data Analysis, with notable contributions to concussion management research through the Maine Concussion Management Initiative (MCMI), focusing on sports-related injury analysis and symptom monitoring. His research spans over two decades, with significant work in human-robot interaction, autonomous systems, and educational technology. Notable projects include developing tools for real-time shadow removal in autonomous driving contexts and analyzing cognitive outcomes in student-athletes post-concussion. Maxwell has authored over 50 peer-reviewed publications, emphasizing interdisciplinary approaches bridging computer science, sports medicine, and educational policy. Teaching innovations include integrating thematic elements (e.g., Lord of the Rings) into CS1 coursework and advocating for writing in computer science curricula. He maintains active roles in academic service, including SIGCSE conference contributions and panel discussions on gender equity in tech education. Education: Ph.D. in Robotics from Carnegie Mellon University (1996), M.Phil. in Engineering from Cambridge University (1993). Awards: Recognized for pedagogical contributions but no named awards listed in provided materials. Labs/Teams: Collaborates with the Maine Concussion Management Initiative and Khoury College’s Align Program team.

Wenchao LiView profile

Assistant Professor

• Dependable Computing
• Cyber-Physical Systems
• Electronic Design Automation
• +4 more

Wenchao Li is an Assistant Professor in the Department of Electrical and Computer Engineering at Boston University, directing the Dependable Computing Laboratory. He holds a B.S., M.S., and Ph.D. in Electrical Engineering and Computer Sciences, along with a B.A. in Economics from UC Berkeley. His research focuses on dependable computing, applying formal verification, machine learning, and control theory to cyber-physical systems, electronic design automation, and AI safety. Key research interests include neural network verification, safe reinforcement learning, autonomous systems security, and resilient control strategies for connected vehicles. His work emphasizes provable safety guarantees and defense against adversarial attacks in critical infrastructure systems. Notable awards include the ACM Outstanding Ph.D. Dissertation Award and the Leon O. Chua Award. His lab investigates topics such as neural network repair, secure multi-robot coordination, and formal methods for autonomous systems. He advises students like Jiameng Fan and collaborates on projects funded by grants in AI safety and cyber-physical systems. Labs/Teams: Dependable Computing Laboratory Grants: Focus on formal verification, AI safety, and autonomous systems resilience

Angelica LimView profile

Assistant Professor

• Human Robot Interaction
• Affective Computing
• Multimodal Perception and Learning
• +6 more

Angelica Lim is an Assistant Professor of Professional Practice and Rajan Family Scholar in the School of Computing Science at Simon Fraser University. Her research focuses on Human Robot Interaction, Affective Computing, and Multimodal Perception with applications in healthcare and developmental robotics. She holds a PhD in Informatics from Kyoto University (2014), an M.Sc. from Kyoto University (2012), and a B.Sc. in Computing Science from SFU (2008). Her work bridges robotics and human-centered AI through projects like the ROSIE Lab, exploring emotion-aware systems, socially assistive robots, and VR programs for aging populations. Key contributions include benchmarking emotional speech recognition (BERSting), developing embodied emotion models for robots, and co-designing healthcare technologies with patient partners. Recent publications emphasize ethical AI, multimodal perception systems, and human-robot collaboration in dynamic environments. Teaching includes courses on software engineering, artificial intelligence, and introductory computer science. Her research has been applied in dementia care through VR programs, robotic companionship for older adults, and emotion-aware human-robot communication systems. Current initiatives focus on inclusive HRI design and sim2real methodologies for underrepresented data in affective computing.

Dian TjondronegoroView profile

Professor

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +7 more

Professor Dian Tjondronegoro is a leading academic at Griffith University's Department of Management within the Griffith Business School. He holds roles such as Acting Head of Department and Deputy Head (Research), and is affiliated with the Centre for Work, Organisation and Wellbeing, Griffith Asia Institute, and the Griffith Inclusive Future Beacon. His research focuses on AI ethics, eHealth systems, and digital governance, with over $9M in grants from bodies like the ARC and NHMRC. He has published 145+ peer-reviewed papers and leads initiatives like the 'Governing in the Digital Age' program. A Fellow of the Australian Computer Society and Senior Member of IEEE/ACM, he has won the Gold Disrupters Award (2019) and multiple teaching accolades. Education: PhD in Information Systems (Deakin University, 2005), BIS (QUT, 2001). Research Interests: AI, machine learning, healthcare innovation, responsible AI, workplace design, and digital economy strategies. His articles emphasize AI applications in healthcare monitoring, workplace productivity, and ethical surveillance. Recent work explores post-COVID workplace trends and AI-driven public health solutions. He advises on government policy and innovation through roles like Gold Coast Health's Digital Innovation Advisory Committee. His teaching includes courses on digital strategy and innovation management.

Stefano CAMPOSTRINIView profile

Professor

• Social Statistics
• Public Health
• Healthcare Systems
• +6 more

Stefano CAMPOSTRINI is a Full Professor in the Department of Economics at Ca' Foscari University of Venice, specializing in Social Statistics (STAT-03/B). He serves as a Member of the technical-scientific Committee of the Ca' Foscari Challenge School and the Department of Economics' Committee. His research activities are supported by affiliations with the Research Institute for Social Innovation and the Research Institute for Innovation Management. Professor CAMPOSTRINI's research spans the intersection of statistical methodology, public health, and social policy. His work demonstrates expertise in advanced statistical techniques including Bayesian modeling, spatial analysis, and complex survey methodology. His primary focus areas include healthcare systems analysis, social innovation, public administration, and the economic aspects of health policy. He frequently addresses issues related to comorbidity patterns, healthcare service accessibility, and the application of artificial intelligence in healthcare settings. His publication record from 2021-2025 reveals significant trends in healthcare innovation, with particular emphasis on virtual hospital systems, AI applications in medicine, sustainable healthcare practices, and the statistical analysis of social services like early childhood education. His methodological contributions include novel approaches to analyzing regional health disparities and developing web-based tools for disease prevalence estimation. His research often employs expert consensus methods like Delphi techniques to address complex healthcare organizational challenges. Professor CAMPOSTRINI maintains active involvement in research initiatives through the Research Institute for Social Innovation and the Research Institute for Innovation Management. His work bridges advanced statistical methodology with practical applications in healthcare policy and social service delivery, making significant contributions to evidence-based decision making in public health and social policy domains across Italy and European contexts.