Find Academic Supervisors

Emie YiannakaView profile

Professor

• Agricultural Economics
• Agri-food Sector
• Innovation Economics
• +5 more

Emie Yiannaka is a Professor in the Department of Agricultural Economics at the University of Nebraska-Lincoln, affiliated with the College of Agricultural Sciences and Natural Resources. Her research focuses on the economic impacts of new technologies and policies in the agri-food sector, including genetically modified products, food fraud, and consumer behavior. Ph.D. in Agricultural Economics, University of Saskatchewan (2002) M.Sc. in Agricultural and Resource Economics, Mediterranean Agronomic Institute at Chania, Greece (1996) M.A. in Agricultural Policy, Mediterranean Agronomic Institute at Chania, Greece (1995) B.Sc. in Agricultural Economics, Aristotle University of Thessaloniki, Greece (1994) Her research spans topics such as innovation economics, intellectual property strategies, consumer acceptance of food technologies, and the economic effects of corporate social responsibility. Recent work examines food fraud deterrence, information avoidance behavior, and ecosystem services valuation. She has published extensively in journals like Journal of Agricultural and Resource Economics , PLOS ONE , and American Journal of Agricultural Economics . Yiannaka has taught courses including Agricultural Marketing in Multinational Environments, Applied Welfare Economics, and Innovation Strategies. She has mentored numerous advisees, including Mavroutsikos C., Deka A., Britwum K., and Meerza S.I.A., who co-authored key publications on food fraud and consumer behavior.

Jana OzoliņaView profile

Researcher

• Workplace Conflicts
• Constructive Conflict Resolution
• Organizational Psychology
• +3 more

Jana Ozoliņa is a Research Assistant and Doctoral Student at the Faculty of Engineering Economics and Management (FEEM) of Riga Technical University (RTU). She holds dual Master’s degrees in Entrepreneurship and Management and Engineering Sciences in Road Transport, reflecting her interdisciplinary expertise. Education: Master’s in Entrepreneurship and Management, Bachelor’s in Tax Economics, Master’s in Road Transport (Engineering Sciences) Research Focus: Workplace conflicts, constructive conflict resolution, mobbing, bossing, and organizational psychology. Publications: Recent works examine employee motivation, generational gaps in collaboration, and interpersonal conflict strategies. Contact: jana.ozolina@edu.rt.lv , jana.ozolina@rtu.lv

• Robotics
• Control Systems
• Rehabilitation Robotics
• +4 more

Timothy Bretl is a Professor of Aerospace Engineering at the University of Illinois at Urbana-Champaign, holding the Severns Faculty Scholar position since 2021. He also serves as Associate Head of the Aerospace Engineering department. His research focuses on robotics, control systems, rehabilitation robotics, and engineering education. Bretl earned his Ph.D. from Stanford University (2005), with prior degrees from Swarthmore College. He holds affiliate roles across multiple departments, including Neuroscience, Coordinated Science Laboratory, and Computer Science. Education: Ph.D. in Aeronautics and Astronautics, Stanford University (2005) B.A. in Mathematics and B.S. in Engineering, Swarthmore College (1999) His research spans engineering education innovations, robotic manipulation, and brain-machine interfaces. Notable awards include the NSF CAREER Award (2010), Best Manipulation Paper (2012), and multiple teaching honors like the Rose Award for Teaching Excellence (2016). Bretl’s work integrates theoretical foundations with practical applications in prosthetics, autonomous systems, and educational technology. He has advised numerous projects on robotics, control systems, and human-robot interaction. His lab explores advanced topics like elastic rod manipulation, magnetic positioning, and curriculum reform in STEM education. Collaborative projects include partnerships with industry and interdisciplinary teams at the Beckman Institute.

Endadul HoqueView profile

Assistant Professor

• Computer Networks Security
• IoT Systems Security
• Vulnerability Detection
• +3 more

Endadul Hoque is an Assistant Professor in the Department of Electrical Engineering and Computer Science at Syracuse University (SU), leading the SYNE Lab. Previously, he held a similar position at Florida International University (FIU). He earned his Ph.D. in Computer Science from Purdue University in 2015, with postdoctoral research at Northeastern University. His research focuses on cybersecurity, particularly in automated vulnerability detection, network/system security, and IoT defense mechanisms. He draws on program analysis, formal verification, and fuzz testing. Key honors include the NSF CAREER Award (2024) and a Google Research Scholar Award (2022). His work has been published in top venues like ACM CCS, NDSS, and IEEE S&P. He actively seeks students for PhD/MSc positions in security, IoT, and program analysis. His grants include NSF funding for IoT policy enforcement and context-sensitive fuzzing. Education Ph.D., Computer Science, Purdue University, 2015 M.S., Computer Science, Marquette University, 2010 B.S., Computer Science and Engineering, Bangladesh University of Engineering and Technology, 2008 Research Interests Dr. Hoque’s work spans secure network systems, IoT security, vulnerability detection, and automated reasoning methods like SMT solving and symbolic execution. Recent innovations include VetIoT (runtime IoT defense validation) and LLM-driven security tools like iConPAL. He emphasizes practical defenses and user-centric security solutions, such as the SeQR enterprise Wi-Fi configurator. Awards NSF CAREER Award (2024) Google Research Scholar Award (2022) NDSS Distinguished Paper (2018) Grants & Service He leads NSF-funded projects on IoT policy enforcement and context-sensitive fuzzing. Served on program committees for S&P, SecDev, and DSN. Teaches courses on systems security and operating systems at SU and FIU. Lab/Team SYNE Lab at Syracuse University focuses on securing networked systems through automated analysis, runtime verification, and resilient protocols.

Peter M. SengeView profile

Senior Lecturer

• Organizational Learning
• Systems Thinking
• Leadership Development
• +4 more

Peter M. Senge is Senior Lecturer at MIT Sloan School of Management, founding chair of SoL (Society of Organizational Learning), and co-founder of the Academy for Systemic Change. His work centers on promoting shared understanding of complex issues and shared leadership for healthier human systems, with major cross-sector projects focused on global food systems, climate change, regenerative economies, and the future of education. Peter M. Senge's educational background includes: BS in Engineering from Stanford University MS in Social Systems Modeling from MIT Sloan School of Management PhD in Management from MIT Sloan School of Management Peter Senge is best known for pioneering work in organizational learning and systems thinking. His research focuses on how organizations can develop the capacity to learn collectively, understand complex systems, and create sustainable change. He explores how shared understanding of complex issues can lead to shared leadership for healthier human systems across multiple sectors. His work bridges theory and practice, emphasizing practical applications of systems thinking in real-world organizational contexts, particularly in sustainability initiatives and cross-sector collaboration. Peter Senge's publications reveal consistent themes in organizational learning, systems thinking, and sustainable development. His work has evolved from foundational theories of learning organizations toward practical applications for addressing global challenges through systemic change. The articles demonstrate increasing focus on collaborative approaches to complex problems like sustainability, with emphasis on relational dynamics and cross-sector partnerships. Peter Senge has received significant recognition for his contributions to management theory and practice: Named one of the 24 people with greatest influence on business strategy by Journal of Business Strategy Recognized by Harvard Business Review as author of one of seminal management books of last 75 years Recognized by Financial Times as author of one of five most important management books Named to '1000 Talents' Program (Renzai) in China Through the Society for Organizational Learning (SoL) and the Academy for Systemic Change, Senge has created platforms for sharing knowledge and fostering collaboration across organizational boundaries. His work extends beyond traditional academic boundaries into practical applications with organizations worldwide, focusing on developing the capacity for systemic change. While specific grant information isn't detailed in the provided text, his involvement in major cross-sector projects suggests significant collaborative funding initiatives. Peter M. Senge co-founded the Society for Organizational Learning (SoL), a global network of organizations, researchers, and consultants dedicated to the 'interdependent development of people and their institutions.' More recently, he co-founded the Academy for Systemic Change, which seeks to accelerate the growth of the field of systemic change worldwide. These organizations serve as hubs for his work in advancing systems thinking and organizational learning across multiple sectors.

Stephen BachView profile

Assistant Professor

• Machine Learning
• Weak Supervision
• Probabilistic Soft Logic
• +7 more

Stephen Bach is an Assistant Professor in the Computer Science Department at Brown University, where he leads the BATS (Bach's Awesome Team of Students) research group. His research focuses on improving how humans teach computers through programmatic weak supervision and methods for learning from fewer examples like zero-shot and few-shot learning. His primary research interests include weak supervision, data programming, probabilistic soft logic (PSL), statistical relational learning (SRL), information extraction, zero-shot learning, and few-shot learning. Bach's work often focuses on exploiting high-level, symbolic or semantically meaningful domain knowledge, with applications in information extraction, image understanding, scientific discovery, and data science. Bach's recent publications show a strong focus on language models, weak supervision techniques, and multimodal learning, particularly examining the capabilities and limitations of models like CLIP. His research has increasingly emphasized practical applications in low-resource settings and cross-lingual scenarios. Best Paper Award at NeurIPS Workshop on Socially Responsible Language Modelling Research (SoLaR) 2023 Larry S. Davis Doctoral Dissertation Award Selected for oral presentation at ICLR 2024 Best of VLDB 2018 paper selection Bach advises numerous Ph.D., Master's, and undergraduate students, many of whom have gone on to positions at leading tech companies, research institutions, and graduate programs. His research group has developed several influential frameworks including Snorkel (for weak supervision), PSL (Probabilistic Soft Logic), T0 (for zero-shot task generalization), ZSL-KG (for zero-shot learning with knowledge graphs), TAGLETS (for semi-supervised learning with auxiliary data), and WISER (for programmatic weak supervision in sequence tagging).

• Computational Pathology
• Medical Image Analysis
• Deep Learning
• +4 more

Nasir M. Rajpoot is a Professor in the Department of Computer Science at the University of Warwick, UK. His research focuses on computational pathology, medical image analysis, and deep learning applications in histology. He leads interdisciplinary projects integrating artificial intelligence with healthcare, particularly in cancer diagnostics and pathology workflows. Rajpoot’s work emphasizes developing robust algorithms for histology image analysis, including nuclear segmentation, tumor classification, and domain generalization in computational pathology. His contributions include the TIAToolbox, an open-source framework for tissue image analytics, and the CoNIC Challenge to advance nuclear detection and counting in histology images. He collaborates with clinicians and biologists to translate AI models into clinical practice, addressing challenges like tumor heterogeneity and staining variability. Rajpoot’s research spans colorectal, lung, and oral cancers, with a focus on predicting clinical outcomes via histological features and genomic data integration. Notable projects include the development of Handcrafted Histological Transformer (H2T) for unsupervised representations of whole slide images and the SAFRON framework for histology image synthesis. His work addresses domain adaptation, robustness evaluation, and explainability in AI-driven pathology systems.

Yao LiangzhongView profile

Professor

• Renewable Energy Grid Integration
• Smart Grid
• HVDC Grid Control
• +4 more

Liangzhong Yao is a Professor and Director of the Smart Grid Research Institute at Wuhan University, China. He holds dual roles as Fellow of IEEE and IET, and has served in leadership positions such as Vice President of China Electric Power Research Institute (CEPRI) and Chair of IEC TC122. His expertise spans renewable energy grid integration, HVDC systems, smart grid technologies, and energy storage. Yao has led over 25 years of R&D projects with combined funding exceeding GBP 20 million and RMB 90 million, resulting in applied technologies in wind farms and HVDC grids. He has been awarded over 10 national and international accolades, including the IEC 1906 Standard Award and China Science and Technology Innovation Awards. Research focuses include AC-DC hybrid systems, distributed energy resource integration, and high-renewable energy grid operation. He has authored/co-authored 350+ publications, 60+ patents, and 4 books. Yao currently supervises 8 PhD and 10 Master's students, and serves on editorial boards of journals like CSEE Journal of Power Energy & Systems. His leadership roles in global standards bodies like IEC and CIGRE further highlight his contributions to advancing electrical engineering standards and practices.

Sheryl Staub-FrenchView profile

Professor

• Building Information Modeling (BIM)
• Virtual Design and Construction (VDC)
• Integrated Project Delivery (IPD)
• +7 more

Dr. Sheryl Staub-French is a Professor and Head (Pro Tem) in the Department of Civil Engineering at the University of British Columbia (UBC), Faculty of Applied Science. She directs the BIM TOPiCS Lab, focusing on digital delivery methods for sustainable construction using BIM. Her research spans over 100 publications in BIM, VDC, and collaboration frameworks. She previously served as Associate Dean of Equity, Diversity, and Inclusion (EDI), advancing inclusive practices in engineering education. She holds a BS from Santa Clara University and MS/PhD from Stanford University. Her research interests include BIM implementation challenges, design coordination, 4D visualization, and sustainable construction innovation. She teaches courses like CIVL 300 (Construction Engineering), CIVL 426 (Virtual Design and Construction), and advanced BIM topics. Her lab collaborates with industry/government to develop BIM guidelines and tools. Notable projects include UBC’s Brock Commons Tall Wood Building and studies on IPD adoption barriers in Canada. Her work bridges academia and industry, emphasizing digital transformation and EDI. She has pioneered BIM-based methods for facility management and energy modeling, addressing gaps in information quality and handover processes. Her contributions span policy development, tool innovation, and educational reforms to enhance construction sector efficiency and inclusivity.

Aybars TuncdoganView profile

Associate Professor

• Digital Innovation
• Information Security
• Marketing Strategy
• +3 more

Aybars Tuncdogan is a Reader in Digital Innovation and Information Security at King’s Business School, King’s College London. He holds affiliations with the King’s AI Institute, King’s Cybersecurity Centre (Informatics), and King’s Cybersecurity Group (War Studies). A Fellow of the Higher Education Academy, he also serves on the editorial review board of Industrial Marketing Management . Education : PhD in Management, Rotterdam School of Management, Erasmus University MPhil in Business Research (Distinction), Erasmus University Bachelor’s in Business Management & Computer Science (Honors), Earlham College Research Interests : His work focuses on three pillars of digital innovation: generation (crowdsourcing, AI), marketing (digital brand personality, sales ambidexterity), and protection (information security, corporate espionage). He integrates psychology (individual differences, social identity) and computer science (machine learning/AI) frameworks. Publications Trends : Recent work addresses cybersecurity challenges in retail, AI ethics in healthcare, and interdisciplinary innovation. He frequently publishes in top-tier journals like Journal of Management and Scientific American , blending academic rigor with practitioner impact. Awards & Contributions : 2015 Best Paper Award (shared) Edited books including Oxford Handbook of Individual Differences and Strategic Renewal Teaching & Pedagogy : Develops innovative teaching methods like inquiry-based learning to foster student creativity. Taught modules on digital marketing, consumer behavior, and research methods. Labs/Teams : Contributes to cybersecurity initiatives at King’s, focusing on AI-driven defense mechanisms and organizational cyber resilience strategies.

Yu SunView profile

Assistant Professor

• Biomedical Imaging
• Computational Imaging
• Inverse Problems
• +4 more

Yu Sun is an assistant professor in the Department of Electrical and Computer Engineering at Johns Hopkins University with a joint appointment at the Data Science and Artificial Intelligence (DSAI) Institute. His research integrates machine learning, computer vision, optimization, and physics to advance computational imaging frameworks for reliable AI-driven imaging systems. He earned a BEng in electronics and information from Sichuan University (2015) and a PhD in computer science from Washington University in St. Louis (2022), where his dissertation received the Turner Dissertation Award. His academic journey includes a postdoctoral fellowship at Caltech's Department of Computing and Mathematical Sciences. Dr. Sun's research spans biomedical imaging, computational imaging, inverse problems, and machine learning, focusing on interpretable AI integration for next-generation imaging. His work bridges theoretical foundations with practical applications in medical and scientific imaging domains. Recent publications reveal a dominant trend in diffusion models for scientific imaging problems, including plug-and-play priors for reconstruction (NeurIPS 2024) and benchmarks for diffusion-based scientific problem-solving (ICLR 2025 Spotlight), demonstrating cross-disciplinary impact from biomedical engineering to cell biology. Key honors include: Turner Dissertation Award for doctoral contributions Rising Star Award from the Conference on Parsimony and Learning (CPAL, 2025) He serves as a consultant associate editor for the IEEE Open Journal of Signal Processing and actively participates in the IEEE Signal Processing Society’s Computational Imaging Technical Committee. His research is supported by institutional funding through the Hopkins Computational Imaging Group. The Hopkins Computational Imaging Group, which he leads, unites AI, mathematics, and data science to develop principled algorithms for imaging systems, with emphasis on biomedical applications and novel computational frameworks.

Divya Jayakumar NairView profile

Senior Lecturer

• Transportation Engineering
• Disaster Management
• Network Design and Optimization
• +4 more

Dr. Divya Jayakumar Nair serves as Senior Lecturer in the School of Civil and Environmental Engineering at the University of New South Wales (UNSW), where she also holds the position of Associate Dean International – South Asia for UNSW Engineering. Her academic work is centered at the Research Centre for Integrated Transport Innovation (rCITI), focusing on transportation systems, network optimization, and disaster management applications. Dr. Nair's research interests span transportation engineering, disaster management, and urban mobility systems. Her work investigates complex network design problems, particularly in pre-disaster evacuation planning, transportation resilience, and food rescue logistics. She employs advanced analytical methods including traffic equilibrium modeling, network optimization techniques, and data-driven approaches to solve real-world transportation challenges with significant societal impact. Her recent publications demonstrate a strong focus on transportation resilience during disasters, with particular attention to equity considerations in pre-event planning. Dr. Nair's research shows how transportation networks can be optimized to improve emergency response while ensuring equitable access to safety for all population segments. Her work bridges theoretical network optimization with practical applications in urban environments facing climate-related challenges. Dr. Nair collaborates extensively with leading researchers in transportation including S. Travis Waller, Vinay V. Dixit, David Rey, and Taha Rashidi. Her collaborative approach spans multiple institutions and addresses pressing challenges in urban transportation systems worldwide.

Behzad FatahiView profile

Professor

• Unsaturated Soil Mechanics
• Dynamic Soil-Structure Interaction
• Ground Improvement Techniques
• +6 more

Professor Behzad Fatahi is a distinguished academic in Civil and Environmental Engineering at the University of Technology Sydney (UTS), specializing in geotechnical engineering, railway infrastructure, and sustainable construction technologies. With a career spanning over 16 years at UTS, he has served as Deputy Head of School - Teaching and Learning (2024-present), Head of Discipline (2020-2024), and School Research Coordinator (2012-2017). His research focuses on unsaturated soil mechanics , dynamic soil-structure interaction , and green infrastructure solutions . Academic Appointments : Professor (2024-present), Associate Professor (2017-2024), Senior Lecturer (2011-2017), Lecturer (2008-2011) Research Leadership : Supervised 21 PhD students to completion, developed groundbreaking techniques for landfill waste reuse and tyre-derived aggregates in railway construction His work on seismic resilience of LNG tanks and bioengineered soil stabilization has received international recognition, including the 2023 Best Research Paper Award at the Australasian Association for Engineering Education conference. Professor Fatahi's industry experience includes geotechnical engineering roles at Coffey International and SES Engineering prior to academia. Key Research Contributions : Developed green corridor models for railway lines using coupled flow-deformation equations Pioneered AI-integrated teaching frameworks for civil engineering education Advanced machine learning techniques for intelligent compaction and structural buckling analysis As a Category 1 supervisor , he mentors graduate researchers in Civil Engineering , Geomechanics , and Earthquake Engineering . His peer-reviewed work (>240 publications) demonstrates technical excellence and innovation across multiple geotechnical domains.

• Hydrology
• River Engineering
• Flood Prediction
• +7 more

Patrick Willems is a full Professor at KU Leuven's Faculty of Engineering Sciences, Department of Civil Engineering. He serves as the head of the Hydraulics Subdivision within the Hydraulics and Geotechnics unit. Professor Willems holds multiple significant roles including chairman of the ADS Bureau, member of the Faculty Council of Engineering Sciences, and participant in the Leuven One Health Institute and KU Leuven Institute for Urban Studies (LUSI). His work addresses critical global water management challenges through advanced hydrological modeling and climate change adaptation strategies. Professor Willems' research spans several critical areas in water resources engineering. His primary expertise includes urban hydrology and river engineering, statistical hydrology with focus on flood prediction and risk analysis, integrated river basin management, precipitation analysis, and climate change impacts on hydrological extremes. He employs both traditional hydrological modeling approaches and innovative machine learning techniques to develop practical solutions for flood warning systems, urban water management, and climate adaptation planning. His research integrates statistical methods, numerical modeling, and data science to address complex water management problems across multiple geographical contexts. Professor Willems leads multiple major international research projects examining hydrological extremes in transboundary river basins, natural climate adaptation measures, hydrological modeling of peatland areas, and deep learning-based prediction of hydrological extremes. His work spans various geographical contexts including Belgium, Vietnam, Bolivia, Tanzania, and the Congo Basin, demonstrating both local relevance and global applicability of his research. Within KU Leuven, Professor Willems teaches diverse courses including Environmental Problems and Techniques, Statistics and Data Science, Stochastic Hydrology, Urban and River Hydrology and Hydraulics, River Modeling, and Probability and Statistics. He also leads the Hydraulic Engineering Project course and an Artificial Intelligence Project course, reflecting his commitment to integrating traditional engineering knowledge with modern computational approaches. As head of the Hydraulics Subdivision, he oversees research activities focused on developing advanced water engineering tools and methodologies that bridge theoretical advancements with practical applications for water management authorities.

• Data Systems for AI
• Retrieval-Augmented Generation (RAG)
• Database Systems
• +4 more

Yongjoo Park is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Grainger College of Engineering. He leads research in data-intensive AI systems as a member of the Data and Information Systems (DAIS) lab, focusing on novel data systems that bridge database theory and practical AI applications. His work emphasizes open-source contributions through GitHub and direct societal impact. Research interests center on systems for data-intensive AI , particularly efficient Retrieval-Augmented Generation (RAG) systems for exploratory AI, data science versioning, and in-storage computing. Key projects include Kishu (the world's first undoable Jupyter notebook with time-travel capabilities), CARE (a causal-relational system for structured/unstructured data), and AirDB/AirIndex (serverless transactions and automatic index optimization). His group develops tools enabling scalable, optimized AI workflows from storage layers to LLM inference. Recent publications reveal a strong focus on interactive data systems (85% of recent work), with significant contributions to notebook environments (Kishu), vector databases (ISCA'25), and RAG optimization. Awards highlight technical innovation, including SIGMOD 2025 Best Demo Award and NSF CAREER funding. His open-source philosophy drives GitHub releases of all major systems. SIGMOD 2025 Best Demo Award (Kishu) NSF CAREER Award (Novel data science systems) SIGMOD'23 Best Artifact Award Honorable Mention (DeepOLA) IBM-Illinois Project Selection (VectorDB/RAG) Mentorship spans 12 current PhD/MS students and 6 graduated advisees, including Supawit Chockchowwat (now Postdoc at Google, future Assistant Professor at CMKL University). He teaches advanced courses like CS511 (Advanced Data Management) and recruits 1-2 new PhD students annually, prioritizing data systems research. His lab emphasizes diversity, individual respect, and concrete outcomes in a collaborative workspace.