Find Academic Supervisors

• Artificial Intelligence
• Robotics
• Manufacturing Systems
• +5 more

Professor Will Browne is the Chair in Manufacturing Robotics at QUT, collaborating with the ARM Hub and CSIRO to advance robotics in manufacturing, healthcare, and industry. He holds a Doctorate in Engineering from the University of Wales and has over 30 years of expertise in AI, robotics, and Learning Classifier Systems (LCS). His research focuses on transparent AI systems like LCS for Explainable AI (XAI), human-robot collaboration, and advanced manufacturing solutions. He co-leads the $5M SfTI Robotics Spearhead project and is internationally recognized for LCS contributions, including co-authoring the first LCS textbook with Ryan Urbanowicz. Publications emphasize emotion recognition, embodied AI, and scalable machine learning. His work bridges academia and industry through the ARM Hub, fostering innovation in robotics and design-led manufacturing. Key roles include co-track chair at GECCO (2011–2025) and editorial board memberships. Research spans evolutionary computation, robotics control, and energy systems optimization.

• Computer vision
• Machine learning
• Statistical data analysis
• +3 more

Ceyhun Burak Akgül is a Part-Time Lecturer specializing in Computer Vision, Machine Learning, and Statistical Data Analysis. His research focuses on interdisciplinary applications of visual data processing, including medical imaging and 3D object recognition. He maintains a personal website at cba-research.com and can be contacted at cb.akgul@gmail.com . His work spans topics such as image captioning, visual dictionaries, and symbolic feature detection. Key contributions include developing algorithms for action recognition using depth cameras and frameworks for leaf and object recognition. His research also integrates medical applications, such as analyzing Alzheimer’s patient movements and automated diagnosis using imaging data. Akgül’s publications frequently address challenges in 3D shape descriptors, feature selection, and interdisciplinary methodologies. His recent work includes exploring visual dictionaries and improving image processing techniques through model-driven approaches. His academic contributions are evident in journals like the Journal of Visual Communication and Image Representation, and he has participated in competitions like SHREC. Despite his extensive publication record, no formal awards or grants are explicitly mentioned in the provided data.

Michelle ZhuView profile

Professor

• Parallel and Distributed Computing
• Big Data Analytics
• Cloud Computing
• +4 more

Dr. Michelle Zhu is a Professor and Associate Director for Faculty and Academic Affairs at the School of Computing, Montclair State University. She previously held roles as Associate Professor and Director of Undergraduate Programs at Southern Illinois University Carbondale. Dr. Zhu holds a Ph.D. in Computer Science from Louisiana State University and a B.S. in Biomedical Engineering from Zhejiang University. Her research focuses on parallel/distributed computing, big data analytics, and high-performance networking, supported by grants from NSF, DOE, and NVIDIA. She has authored over 150 peer-reviewed publications. Education: Ph.D., Computer Science, Louisiana State University (2005) M.Sc., Computer Science, Louisiana State University (2002) B.S., Biomedical Engineering, Zhejiang University (1996) Her research interests span parallel computing architectures, cloud workflow scheduling, and cybersecurity. She has led initiatives integrating computational thinking into STEM education and developed robotics-based learning tools. Her work has been funded through NSF grants such as the $1.1M "Assimilating Computational and Mathematical Thinking into Earth and Environmental Science" project (2017–2022). Dr. Zhu’s articles explore topics like blockchain-based cloud security, GPU-accelerated Gibbs sampling, and edge computing deployment strategies. She actively contributes to academic governance, serving on Montclair State’s Middle States accreditation committee and the University Academic Assessment Council. Key Grants: NSF MRI: Multimodal Collaborative Robot System (MCROS), $321,737 (2021–2024) DOE: Scalable Application Support Platform for E-Sciences, $389,398 (2009–2013) Service Roles: Curriculum Committee Chair, Computer Science Department Blue Ribbon Task Force for Gen Ed Redesign (2019–2020) She collaborates on robotics projects like MCROS and leads outreach efforts to engage pre-university communities in AI and robotics education.

Hiroyuki OkamuroView profile

Professor

• Entrepreneurship
• Innovation
• Industrial Organization
• +3 more

Hiroyuki Okamuro is a Professor and Dean of the Graduate School of Economics at Hitotsubashi University, where he has held academic positions since 1993. He also serves as a visiting research fellow at the National Institute of Science and Technology Policy (NISTEP) and has held international visiting roles, including at the University of Birmingham (UK) and Wissenschaftszentrum Berlin (Germany). His academic leadership extends to managing the Student Support Center and Harassment Consultation Office at Hitotsubashi, and he has directed the Teikoku Databank Center for Advanced Empirical Research on Enterprise and Economy (CAREE). Education: Okamuro earned a B.A. (1984), M.A. (1986), and Ph.D. in Economics (1992) from Hitotsubashi University and the University of Bonn, Germany. His doctoral studies focused on industrial economics under Prof. Horst Albach. Research Interests: He specializes in entrepreneurship, innovation, industrial organization, and small business economics, with a focus on policy evaluation and university-industry collaboration. Key areas include SME innovation dynamics, R&D consortium governance, and regional policy effectiveness in fostering startup ecosystems. Scientific Awards: He received the 63rd Economist Award (2023) for contributions to R&D policy research. His work bridges theoretical and empirical approaches, emphasizing microeconomic data analysis to inform policy. Advising & Grants: Okamuro has led major research projects such as JSPS Kakenhi Basic Research B (2015–2017) and the Volkswagen Foundation study on innovation systems (2007–2011). He advises on grant initiatives like the Teikoku Databank CAREE and collaborates internationally via the Erasmus Mundus Program. His roles include Head of the Harassment Consultation Office and Dean of the Graduate School, reflecting his commitment to academic governance and student support. Labs & Teams: He is affiliated with The Circle Lab and the Teikoku Databank CAREE . His interdisciplinary teams analyze long-term SME databases, such as the prefecture-specific 'Teikoku Bank Company Summary,' to study post-war industrial policies and contemporary innovation challenges.

• Differential Privacy
• Algorithms
• Theoretical Computer Science
• +3 more

Teresa Anna Steiner serves as an Assistant Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark, specializing in algorithmic research with emphasis on privacy-preserving computational methods and theoretical computer science. Her research centers on differential privacy mechanisms, where she investigates trade-offs between data utility and privacy guarantees through rigorous analysis of noise injection techniques like Laplace and Gaussian distributions. She extends this work to dynamic graph databases requiring real-time privacy protections and develops novel text indexing approaches for regular expression pattern matching, contributing to foundational advancements in algorithm design for sensitive data environments. Recent 2025 publications reveal a cohesive research trajectory focused on practical implementations of differential privacy across diverse data structures, with particular attention to variance optimization in noise mechanisms, edge-level privacy in evolving graphs, and efficient indexing for textual pattern recognition. These works collectively address critical challenges in balancing computational efficiency with robust privacy guarantees in modern data systems. No scientific awards were documented in the available information. Details regarding student advising or research grant funding were not specified in the provided materials.

• Database Management
• Spatial-Textual Data Processing
• Heterogeneous Data Usability
• +6 more

Professor Zhifeng Bao is a faculty member at RMIT University's School of Computing Technologies. His research focuses on enhancing data usability across heterogeneous domains, including structured, unstructured, and spatial-temporal data. His work spans database management, keyword search optimization, social network analysis, and spatio-textual data processing. He coordinates the course COSC1169: Intranet and Internet Data Engineering and supervises PhD/Masters students in projects such as trajectory data processing, data asset valuation, and edge computing optimization. Research interests emphasize improving data accessibility and efficiency through methodologies like query relaxation, visual analytics, and provenance tracking. His recent projects include cost-effective edge node placement, traffic accident risk prediction, and differentially private federated learning. Teaching and supervision activities highlight a commitment to bridging theory and practical data engineering challenges.

Ariel GenadtView profile

Lecturer

• Modern and Contemporary Architecture
• Japanese Architecture
• Architectural Resilience
• +3 more

Ariel Genadt is a Lecturer in Architecture at the Stuart Weitzman School of Design, University of Pennsylvania. His work bridges research, teaching, and practice, focusing on modern and contemporary Japanese architecture, architectural resilience, and the intersection of technology, sustainability, and cultural expression. He holds a PhD in Architecture from the University of Pennsylvania (2016), with certificates in Ecological Architecture and University Teaching, alongside degrees from the Architectural Association (London) and Technion (Israel). Education: PhD in Architecture, University of Pennsylvania (2016) Master of Arts in Histories and Theories, Architectural Association, London (2004) Bachelor of Architecture, Technion, Israel (1997, cum laude) Research Interests: Japanese architectural history and practice Sustainable and resilient design Material innovation and tectonic expression Cultural preservation and reinterpretation Genadt's publications and exhibitions explore themes like architectural resilience in Japan, material assemblies, and cultural narratives in urban spaces. His curatorial work includes the Critical Abstractions: Modern Architecture in Japan exhibition (2018) and the 50 Years in Books by Penn Architecture PhDs database (2016). He has practiced globally, collaborating on projects in France, Israel, China, and beyond, and has taught at institutions including Swarthmore College and the Technion. His teaching spans courses on architectural theory, climate-responsive design, and Japanese modern architecture. Notable courses include ARCH 7120: Architectural Envelopes and ARCH 7110: Modern Architecture in Japan . He has advised the Master of Architecture thesis program and led design-build workshops at Tokyo University. Genadt’s professional affiliations include roles as a Fellow Researcher at the Japan Society for the Promotion of Science (Kengo Kuma Lab, 2012) and a visiting scholar at Fondazione Renzo Piano (2013). His work emphasizes cross-cultural dialogue and the role of architecture in addressing environmental and social challenges.

Niko SiltalaView profile

Lecturer

• Production System Design
• Robotics
• Manufacturing Automation
• +3 more

Niko Siltala is a University Instructor at Tampere University's Department of Automation Technology and Mechanical Engineering. He holds a Doctor of Science (Technology) in Mechanical Engineering (2016) and a Master of Science (Technology) in Automation Engineering (2001). His research focuses on production system design, reconfiguration, robotics, and virtual reality applications in safety training. He has contributed to the development of semantic rules for capability matchmaking, which supports rapid system design and reconfiguration. Key research areas include: Manufacturing automation and system adaptability Human-robot collaboration and safety protocols Virtual reality-based training solutions Formal resource descriptions for modular systems His work aligns with UN Sustainable Development Goals, particularly in advancing quality education (SDG 4) through innovative robotics education tools. He has received the Distinguished Committee Service Award (2004) and contributed to grants such as the K.F. ja Maria Dunderbergin testamenttisäätiö (2014). He has collaborated on projects like the D-BEST methodology for pilot lines and the ODIN project for scalable production systems. His activities include organizing conferences, presenting at international forums, and developing web-based tools for manufacturing system planning.

• Computer Vision
• Robotics
• Human-Computer Interaction
• +4 more

Włodzimierz Kasprzak is a Professor at the Institute of Control and Computation Engineering, Faculty of Electronics and Information Technology, Warsaw University of Technology. His research focuses on computer vision, robotics, human-computer interaction, and machine learning. He has contributed to advancements in human action classification, skeleton-based feature analysis, and multimodal interface design. Research Highlights: Development of lightweight classification models for human actions in video using skeleton-based features. Advances in multi-stream fusion techniques for image and video analysis. Design of embodied agent systems for cybersecurity event visualization and control. Awards and Recognition: 2024: Individual First Class Rector's Award for Scientific Achievements (2022-2023) 2021: Medal of the Commission of National Education 2011: Golden Cross of Merit His work integrates theoretical contributions with practical applications in robotics, surveillance systems, and human-centered technologies.

Koushik SenView profile

Professor

• Software Engineering
• Programming Languages
• Formal Methods
• +8 more

Koushik Sen is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He holds a B.Tech from IIT Kanpur and M.S./Ph.D. from UIUC. His research focuses on Software Engineering, Programming Languages, and Formal Methods, emphasizing tools like DART, CUTE, and Jalangi for improving software reliability. He leads projects such as CORVETTE and Sky Computing Lab, and collaborates with Samsung Research America on JavaScript analysis. Sen has received prestigious awards including the Sloan Fellowship and ACM SIGSOFT Impact Award. Education: B.Tech, Indian Institute of Technology, Kanpur M.S. and Ph.D., University of Illinois at Urbana-Champaign Research Interests: Software Testing, Verification, Symbolic Execution, Security, and Quantum Computing. His work bridges automated testing (e.g., concolic testing) with machine learning for bug detection and program synthesis. Projects include Hindsight Logging for ML reproducibility and quantum circuit optimization (QFAST). Awards: NSF CAREER, IFIP Manfred Paul, ACM SIGSOFT Distinguished Paper (multiple), and Sloan Fellowship. Advising: Supervised over 30 students/postdocs, leading to faculty roles at UBC, CMU, and industry positions at Google, Facebook, and Samsung. Labs/Teams: Berkeley Center for Responsible, Decentralized Intelligence (RDI), EPIC Data Lab, and Sky Computing Lab. Active in quantum computing and hardware fuzzing (RTL-FuzzLab).

• Database Systems
• Operating Systems
• Distributed Systems
• +3 more

Athinagoras Skiadopoulos is a computer systems researcher at Stanford University's School of Engineering, Department of Computer Science, focusing on the intersection of database systems and operating systems. His work centers around the innovative DBOS (Database-oriented Operating System) project and large-scale machine learning infrastructure, collaborating with prominent researchers including Christos Kozyrakis and Michael Stonebraker. His primary research interests include: Database-oriented Operating Systems (DBOS) Distributed systems for large-scale machine learning Resource management and optimization in data-intensive systems Transaction processing and data governance High-performance networking for accelerated computing Fault tolerance in distributed training systems Skiadopoulos's research trajectory shows a clear evolution from foundational DBOS architecture toward applications in large-scale machine learning systems. His early publications established the DBOS framework for operating system design using database principles, while his recent work addresses critical challenges in distributed training of massive neural networks. Systems like ReCycle and SlipStream demonstrate innovative approaches to pipeline adaptation and failure recovery during distributed training. His most recent 2025 work on accelerating Mixture-of-Experts training represents the cutting edge of efficient large model training infrastructure. Through his research, Skiadopoulos has established himself in both the database and systems research communities, with publications in premier venues including SOSP, OSDI, VLDB, and CIDR. His work consistently bridges theoretical database concepts with practical systems implementations, demonstrating how database techniques can solve real-world systems challenges in modern computing environments.

Ahmed Al-JaishiView profile

Adjunct Professor

• Randomized clinical trials
• Cluster Randomized Trials
• Health Services Research
• +2 more

Dr. Ahmed Al-Jaishi is an Adjunct Professor in the Department of Epidemiology and Biostatistics and a Research Scientist at the Schulich School of Medicine & Dentistry at Western University. He also holds positions as an Adjunct Scientist with ICES and Senior Epidemiologist at the Public Health Agency of Canada. Education: Ph.D. in Health Research Methodology, McMaster University (2021) M.Sc. in Epidemiology and Biostatistics, Western University (2013) B.Sc. in Biological Sciences, University of Guelph (2010) His research focuses on methodologies for pragmatic randomized controlled trials, with specialization in cluster-randomized designs. Primary research domains include: Clinical trial design and registry-based methodologies Health services research in nephrology (particularly hemodialysis) Population-based epidemiological studies Statistical methods for cluster trials Recent publications demonstrate strong thematic focus on hemodialysis care innovations, COVID-19 impacts on vulnerable populations, autism spectrum disorder epidemiology, and advanced statistical methodologies. Articles frequently utilize registry data, cluster-randomized designs, and health administrative databases across Canadian and international contexts. Dr. Al-Jaishi is actively engaged in training future epidemiologists and biostatisticians through hands-on mentorship in advanced research methodologies.

Thamy PogrebinschiView profile

Researcher

• Democratic Innovations
• Citizen Participation
• Digital Technology in Democracy
• +4 more

Thamy Pogrebinschi is a senior researcher at the WZB Berlin Social Science Center and faculty member at the Berlin Graduate School of Social Sciences (BGSS) of Humboldt University Berlin, where she supervises PhD students. Her academic affiliations include the Center for Civil Society Research at WZB and multiple visiting positions at Oxford University (2022-2023), Harvard Kennedy School (2017-2018), LUISS University Rome (2015), and Goethe University Frankfurt (2013-2014). Her research centers on democratic innovations and new forms of citizen participation in Latin America, with growing focus on digital technology's impact on civil society and collective intelligence. She pioneered the LATINNO project (2015-2021), creating the largest database of democratic innovations across 18 Latin American countries, cataloging 3,600 cases involving deliberation, citizen representation, and digital engagement. Current work examines civil society responses to disinformation in polarized contexts and collective intelligence in endangered democracies. Her 2023 monograph Innovating Democracy? The Means and Ends of Citizen Participation in Latin America (Cambridge University Press) presents the first large-N cross-country study of democratic innovations, introducing a comprehensive typology. Research appears in Comparative Politics , European Journal of Political Research , and Critical Policy Studies across four languages. 50+1 Influential Researchers Whose Work Could Help Shape 21st Century Politicians (Apolitical Foundation, 2022) As principal investigator of LATINNO (funded by Open Society Foundations), she led a 30+ member team analyzing democratic innovations. Current projects on disinformation combat receive institutional support through WZB's Center for Civil Society Research. She advises PhD candidates at BGSS while maintaining active collaborations with Latin American civil society organizations. Her laboratory comprises the LATINNO network and current disinformation research consortium, coordinating researchers across Brazil, Colombia, Mexico, and Peru to analyze digital threats to democracy and develop civil society countermeasures through collective intelligence frameworks.

Joanna Cecilia da Silva SantosView profile

Assistant Professor

• Software Engineering
• Software Security
• Code Generation
• +4 more

Joanna Cecilia da Silva Santos is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame , where she leads the Security and Software Engineering research lab (S 2 E) . She earned her Ph.D. and M.Sc. in Computing and Information Sciences from Rochester Institute of Technology (RIT) and a B.Sc. in Computer Engineering from Federal University of Sergipe (UFS) . Research Interests: Her work focuses on the intersection of Software Engineering and Software Security , with specific emphasis on Code Generation , Program Analysis , Software Architecture , and Quantum Software Engineering . Recent projects include evaluating large language models for code generation, detecting regular expression denial-of-service vulnerabilities, and creating taint-based analysis tools for Java security. 2025: Code generation benchmarks, LLM performance in programming assignments 2024: Frameworks for secure code generation, ReDoS analysis, static analysis of deserialization 2023: GitHub Copilot complexity prediction, vulnerability characterization 2022: Transformer-based code smell detection, security evaluation datasets Scientific Awards: 2017 Best Paper Award at ICSA 2020 JOBS Workshop Research Pitch Competition Winner 2023 Distinguished Reviewer at ESEC/FSE 2014 CAPES Scholarship for Masters at RIT 2013 3rd Place Paper at XIII ERBASE Her research group engages in empirical studies of code vulnerabilities, automated security tools, and educational applications of language models, with funding reflected in multiple peer-reviewed publications.

Yiguo XueView profile

Professor

• Geotechnical Engineering
• Structural Engineering
• Tunnel Engineering
• +2 more

Yiguo Xue is a Professor and PhD Tutor at the Geotechnical and Structural Engineering Center, School of Civil Engineering, Shandong University. He has contributed extensively to tunnel engineering, subsea infrastructure, and slope stability analysis through advanced prediction models and numerical simulations. Research Interests: New tunnel geological condition prediction technologies Subsea tunnel and underground energy storage systems High slope stability evaluation Engineering exploration methods His recent work focuses on tunnel safety, subsea structural mechanics, and AI-driven hazard prediction models. Publications highlight his expertise in rockburst analysis, water inrush risk, and excavation optimization using machine learning and numerical frameworks. Scientific Awards: Recipient of China's Top 100 Most Influential Domestic Academic Paper Award (2008 paper on tunnel geological hazard forecasting) He has secured multiple national invention patents for tunnel monitoring devices (e.g., vibration sensors, collapse prediction systems) and developed specialized software for displacement prediction and rock classification.