Find Academic Supervisors

Helen CaiView profile

Senior Lecturer

• International Business
• Circular Economy
• Sustainable Supply Chain Management
• +11 more

Dr. Helen Cai is a Senior Lecturer in International Business and Circular Economy at Middlesex University Business School, where she serves as Programme Leader for the BA International Business Administration and BA Business Management (Top-Up). She also leads the Doctor of Business Administration (DBA) programme delivered in China through a partnership with United Business Institutions (UBI). Additionally, she holds a Full Visiting Professorship at Jiaxing University, China. Her academic leadership extends to editorial roles as Senior Editor of Cogent Business and Management and member of the editorial board of the Journal of World Business . She is Vice President of Marketing for the International Case Study Research Association (ICRA). Dr. Cai’s research focuses on international business, sustainability, green innovation, and corporate environmental governance. She employs advanced methodologies such as fuzzy-set qualitative comparative analysis (fsQCA), econometrics, and scientometric analysis. Her work addresses critical issues including green supply chains, carbon emissions, foreign direct investment, and institutional influences on innovation. The 15 most recent publications highlight a strong trend toward environmental sustainability, circular economy, and data-driven policy analysis. Her recent work spans blockchain in green supply chains, AI in rehabilitation, carbon governance, land use, and migration policy, demonstrating interdisciplinary breadth and policy relevance. Bronze award, The First National Collegiate Olympiad Mathematical Mirror Competition (2022) Honourable Mention, Interdisciplinary Contest in Modelling (2022) First Prize, Asia and Pacific Mathematical Contest in Modelling (2021) Third Prize, THE International Case Competition (2021) Dr. Cai has extensive supervisory experience, currently guiding multiple PhD candidates and having chaired over 30 DBA viva panels. She has supervised over 60 BA, 150 MSc, and 75 MBA dissertations. She has participated in 72 PhD/DBA committees in roles including external examiner, internal examiner, and panel chair. Her grants and funding are not explicitly mentioned, but her research output and editorial roles suggest sustained scholarly engagement. She leads research teams focused on circular economy and international business, and her future work is likely to expand into AI-driven sustainability analytics, cross-border green innovation, and climate governance. Her prior industry experience as a Senior Economist at China’s Central Bank enriches her applied research perspective.

• Translational Cancer Research
• Cancer Biomarkers
• Tumor Biology
• +11 more

Lars Andreas Akslen is a Professor at the Department of Clinical Medicine, University of Bergen, and serves as the Centre Director of CCBIO (Centre for Cancer Biomarkers). He is based at Haukeland University Hospital and leads a major translational cancer research group focused on biomarker discovery and validation. Position: Professor, Centre Director of CCBIO Institution: University of Bergen Department: Department of Clinical Medicine Location: Haukeland University Hospital, Bergen, Norway Email: lars.akslen@uib.no His research is centered on translational oncology, with a strong emphasis on identifying and validating novel biomarkers for improved biological classification and grading of malignant tumors. His work spans breast cancer , malignant melanoma , prostate cancer , and gynecologic cancers . By integrating human tumor sample analysis with experimental cell and animal models, his team aims to enhance the clinical utility of biomarkers in predicting aggressive tumor behavior and guiding personalized treatment strategies. The recent publications highlight a consistent focus on tumor microenvironment, immune biomarkers, imaging mass cytometry, AI in diagnosis, and age-related phenotypes in cancer. There is a strong trend towards high-dimensional spatial profiling and integration of molecular and clinical data to refine prognostic and predictive models. Lars Andreas Akslen has no listed scientific awards in the provided text. He leads the Tumor Biology Research Group (established in 1995) and the CCBIO center, indicating significant mentorship and leadership in cancer research. While specific students are not listed, his extensive collaboration network suggests active supervision of PhD and postdoctoral researchers. No specific grants are mentioned, but leadership of a national research center implies substantial funding acquisition. He is affiliated with CCBIO and the Tumor Biology Research Group, both based at the Department of Clinical Medicine, University of Bergen, and operating from Haukeland University Hospital. These teams focus on translational cancer biomarker research using advanced molecular and imaging technologies.

• Organic Farming
• Sustainable Agriculture
• Crop Production
• +13 more

Sabine Seidel is a full Professor at the Institute of Crop Production, Department of Agrarwissenschaften, University of Natural Resources and Life Sciences, Vienna (BOKU). Her research integrates plant modeling, sustainable agriculture, and digital farming to enhance climate-resilient and resource-efficient crop systems. Her research interests focus on the development and testing of innovative, diverse (organic) cultivation systems, particularly mixed cropping and intercropping. She investigates ecosystem services such as yield and greenhouse gas emissions through measurements and modeling. Her work emphasizes the interactions between genotype, environment, and management (G×E×M), especially concerning water, nitrogen, and root dynamics. She also explores root growth responses to nutrient deficiency and drought stress, and leads initiatives in digital farming, including AI tools for pollinator detection and digital twin development in agriculture. Analysis of her recent publications (2024–2025) reveals a strong trend in interdisciplinary research combining field experiments with advanced modeling. Her work spans agroecosystem modeling, intercropping systems (especially wheat and faba bean), soil-crop interactions, and the application of AI and machine learning in agriculture. She frequently contributes to multi-model studies and calibration protocols, emphasizing model accuracy and validation. Her research is highly collaborative, involving teams across Germany and Austria. Root:shoot ratio under conservation tillage Phenotypic plasticity in winter wheat Resource acquisition in intercropping Digital crop growth simulation using GANs Soil carbon sequestration and organic matter dynamics She has been actively involved in the PhenoRob Cluster of Excellence as a junior research group leader (2020–2025), focusing on optimizing plant mixtures through field experiments and modeling. Prior to this, she conducted postdoctoral research on subsoil management at the University of Bonn. Her work bridges ecology, plant science, soil science, and digital technologies. She earned her doctorate on plant modeling and irrigation from the Technical University of Dresden and studied agricultural sciences at the Technical University of Munich. She is based in Vienna and maintains an active presence in knowledge transfer, with media contributions in print and online outlets discussing sustainable farming practices.

Erik QuaeghebeurView profile

Assistant Professor

• Probability Theory
• Statistics
• Uncertainty in Artificial Intelligence
• +4 more

Erik Quaeghebeur is an Assistant Professor at Eindhoven University of Technology's School of Mathematics and Computer Science, focusing on uncertainty modeling in artificial intelligence. His work spans probabilistic circuits, imprecise probability theory, and wind energy applications. PhD in Applied Mathematics (Ghent University, 2002-2009) Master's in Applied Mathematics (Université catholique de Louvain, 2001-2002) Master's in Physics Engineering (Ghent University, 1998-2001) Research interests include probabilistic modeling under uncertainty, with applications in AI and wind energy systems. His recent work explores tensor factorizations, equivariant graph neural networks, and scalable probabilistic circuits. Scientific contributions include 60 research outputs and 2 datasets . Awards encompass the ERCIM Alain Bensoussan Fellowship (2013), BOF Postdoc (2010), and B.A.E.F. Francqui Fellowship (2009). He serves on committees for the Society for Imprecise Probability and acts as editorial board member for related conferences. Foundations of Artificial Intelligence course (since 2020) Uncertainty Representations and Reasoning course (since 2021)

• Digital Transformation
• Responsible Artificial Intelligence
• Foresight Methods
• +4 more

Matti Minkkinen is a Docent at the Turku School of Economics (University of Turku) and a Postdoctoral Researcher in Information Systems Science at the Department of Management and Entrepreneurship. His work bridges futures studies with ethics, privacy, and socio-technical systems in digital transformation. Recent roles focus on responsible AI governance and foresight methodologies. University: University of Turku School: Turku School of Economics Department: Department of Management and Entrepreneurship His research explores how digital technologies reshape organizational practices, emphasizing Futures Consciousness as a human capacity. Key themes include responsible AI , privacy protection , and causal layered analysis in scenario planning. Publications highlight ethical governance frameworks and EU policy debates. Recent articles address generative AI ethics , ML system integration , and AI auditing across journals like Communications of the Association for Information Systems and Information and Management . Topics cluster around socio-technical systems, digital ethics, and institutional adaptation to AI. Teaching and editorial roles include co-curating student research collections at Finland Futures Research Centre. No explicit scientific awards are listed, but his work contributes to foresight theory and practice.

Jeffrey C. F. HoView profile

Associate Professor

• Virtual Reality
• Interaction Design
• Human-Computer Interaction
• +6 more

Jeffrey C. F. Ho is an Associate Professor at the School of Design, The Hong Kong Polytechnic University. He serves as Deputy Specialism Leader of Interaction Design and Chairman of the School Learning & Teaching Committee. His research centers on virtual reality (VR) and interaction design, applying social science principles to influence attitudes and behaviors through immersive technologies. He leads projects in VR applications for safety training, virtual museums, and healthcare, and collaborates with the Asian Lifestyle Design Lab and the Technology and Social Behavior Lab at the University of Illinois at Urbana-Champaign. PhD in Communication, City University of Hong Kong MSc in Human-Computer Interaction with Ergonomics, University College London MPhil in Computer Science, The University of Hong Kong BEng in Software Engineering, The University of Hong Kong Ho’s research explores VR’s role in perspective-taking experiences, focusing on empathy, prosocial behavior, and spatial cognition. His work bridges VR with public health, education, and cultural preservation, such as designing VR environments for elderly care and dietary reflection. His recent publications highlight trends in generative AI ethics, beginner-friendly design software, and spatio-social impacts in VR applications. His articles span virtual reality games, VR safety training, and interactive museum design, with keywords like Virtual Reality, Human-Computer Interaction, and Cultural Preservation. Key subfields include immersive technology, social behavior analysis, and ethical design frameworks. UGC Teaching Award - Nominee (2024) Best Paper Award, EAI ArtsIT 2020 (2020) Exemplary Teaching and Learning Award - Merit (2024) QS Reimagine Education Awards 2024 - Global Education Award (2024) QS Reimagine Education Awards 2024 - Gold Award in Smart Omnichannel Campus (2024) Ho has secured grants from Hong Kong’s Research Grant Council, including HK$678,607 for immersive VR construction safety training (2024–2026) and HK$741,961 for VR safety education focusing on accident victims (2021–2023). He contributes as a reviewer for journals like Universal Access in the Information Society and Frontiers in Psychology , and leads teaching initiatives in information architecture and interactive media design.

Patrick JailletView profile

Professor

• Online Optimization
• Machine Learning
• Sequential Decision Making Under Uncertainty
• +4 more

Patrick Jaillet is the Dugald C. Jackson Professor in the Department of Electrical Engineering and Computer Science at MIT's School of Engineering. He holds joint appointments with the Laboratory for Information and Decision Systems (LIDS), the Operations Research Center (ORC), the Operations Research and Statistics Group at MIT Sloan, and the Department of Civil and Environmental Engineering. Previously, he served as Head of Civil and Environmental Engineering at MIT (2002-2009) and Chair of the Department of Management Science and Information Systems at UT Austin (1997-2002). Dr. Jaillet's research focuses on online optimization and learning, sequential decision-making under uncertainty, and security and resilience in complex networks. His work spans theoretical foundations in optimization and machine learning with applications in transportation, online market analytics, and network security. He has developed mathematical frameworks for problems involving uncertainty, dynamic resource allocation, and strategic behavior in complex systems. His recent publications reveal strong trends in bridging theoretical optimization with practical machine learning applications. Key themes include Bayesian optimization for black-box functions, online learning with limited information, mechanism design for resource allocation, and network security applications. His work increasingly integrates large language models with traditional optimization techniques, reflecting the evolving landscape of AI-driven decision-making systems. Fulbright Scholar (1990) Fellow of the Institute for Operations Research and Management Science (INFORMS) Best Applications Paper Award at ICAPS 2019 Long-standing Associate Editor for top journals including Operations Research and Transportation Science Dr. Jaillet has advised over 40 doctoral students who now hold prominent positions in academia and industry, including faculty positions at MIT, Georgia Tech, and ETH Zurich, and research scientist roles at Amazon, Microsoft Research, and Google. His research has been consistently funded by major agencies including NSF, ONR, AFOSR, and international partners like Singapore NRF, with current projects focusing on learning algorithms for autonomous security and fundamental tradeoffs in optimization. He leads a vibrant research group spanning MIT's EECS department and ORC, with current funding supporting work on neural bandits, federated optimization, and network security applications. His research group operates at the intersection of theory and practice, with strong connections to industry through collaborations with IBM, Microsoft, Google, and various transportation and technology companies. The group maintains active partnerships with international institutions, particularly through SMART in Singapore, reflecting Dr. Jaillet's global research impact.

• Political Economy of the Middle East
• Energy Economics
• Political Economy of Oil Rents
• +9 more

Mohammad Reza Farzanegan is a Professor in Economics of the Middle East at the Center for Near and Middle Eastern Studies (CNMS) & School of Business and Economics of Philipps-Universität Marburg in Germany. He serves as the coordinating professor for the international master study program of Economics of the Middle East in Marburg and holds research fellowships with ERF (Cairo) and CESifo (Munich). Education: PhD in Economics from Technische Universität Dresden (2006-09) with DAAD research grant Georg Forster Research Fellowship from Alexander von Humboldt Foundation (2010-12) MSc in Energy Economics & Marketing from University of Tehran (2000-03) BA in Theoretical Economics from Allameh Tabatabaei University, Tehran (1995-1999) Professor Farzanegan's research focuses on political economy of the Middle East, with specialization in Iran. His work spans energy economics, political economy of oil rents, climate change impacts, sanctions analysis, public finance, shadow economy, corruption economics, demographic transition, political institutions, economic development, and economics of happiness. His research methodology combines empirical institutional economics with development economics approaches. His recent publications (2025) demonstrate consistent scholarly output across multiple high-impact areas including sanctions effects on internal conflict, oil rent impacts on economic behavior, natural disaster economics, and Middle Eastern political economy. His work shows particular strength in applying advanced econometric techniques to analyze complex socio-economic phenomena in the Middle East context. Scientific Awards: ERF Research Fellow (Cairo) CESifo Research Network Fellow (Munich) Georg Forster Research Fellowship from Alexander von Humboldt Foundation Professor Farzanegan has led multiple significant international research projects including NAREM (Political Economy of Natural Resource Management, 2016-2018), NaDiMa (Socio-Economic, Cultural and Technical Aspects of Natural Disaster Management, 2020), and DEBEC (Drivers and Socio-Economic, Behavioural Effects of Climate Change in Iran, 2020-2022), all funded by DAAD/AA/BMBF. His research grants demonstrate strong institutional support for his work on Middle Eastern economic issues. He actively contributes to research networks including the NaDiMa Dialogue series which has hosted multiple workshops on disaster management, climate change, and economic policy in Iran and Germany.

Cantay CaliskanView profile

Associate Professor

• Computational Social Science
• Computer Vision
• Generative AI
• +6 more

Cantay Caliskan is an Associate Professor at the Goergen Institute for Data Science, University of Rochester. He teaches Data Mining, Statistical Machine Learning, and the Data Science Capstone courses in the undergraduate and graduate data science curriculum. Bachelor of Arts, Brandeis University Master of Arts, Koç University PhD in Political Science, Computer Science, and Statistics, Boston University (2018) His research focuses on computational social science, computer vision, and generative AI, with applications in deep learning, network analysis, and AI ethics in social contexts. His recent publications span interdisciplinary topics including: Geo-cultural bias in AI-generated urban models (SimCityNet) Comparative religious text analysis using LLMs (HalalLLM vs. KosherLLM) Political polarization metrics through social media interactions Article trends highlight AI's role in addressing social science challenges, from electoral geography to disaster response optimization. His work integrates natural language processing, dynamic network modeling, and cross-cultural analysis. He contributes to advancing accessible AI systems (ACROSS) and understanding misinformation dynamics. No scientific awards listed in available data.

• Semantics
• Pragmatics
• Syntax
• +2 more

Kyle Rawlins is a Professor in the Department of Cognitive Science at Johns Hopkins University (JHU), where he heads the Semantics Lab located in Krieger Hall 105. His research focuses on semantics, pragmatics, syntax, and their intersections, often collaborating with labs like the Van Durme Lab in Computer Science. The Semantics Lab facilitates weekly meetings for discussing research, structured as seminars or traditional lab sessions, and co-organizes projects such as the Decomp Project and MegaAttitude Project . Current lab members include PhD students Karl Mulligan and Natalia Talmina. Notable collaborators: Ilaria Frana (University of Enna), Barbara Landau (JHU), Ben Van Durme (JHU CS), and Aaron Steven White (Rochester). His research spans topics like: Questions Under Discussion (QUD) frameworks Evidentiality and bias in language Multimodal semantic parsing Decompositional semantics Pragmatic particles in Italian Recent publications analyze polar questions, neural network representations, and discourse particles. The lab maintains a mailing list for event announcements, emphasizing collaborative research in semantics and computational linguistics.

• Pediatric Oncology
• Neurogenetics
• Molecular Pathology
• +3 more

Casmir Turnquist is a Research Fellow at the Nuffield Department of Clinical Neurosciences, University of Oxford, with concurrent roles as an NIHR Academic Clinical Fellow and Specialty Registrar in Histopathology at OUH NHS Foundation Trust. His work bridges clinical practice and research in pediatric brain/spine cancers and neurodegenerative pathologies. BA, MSc, BM BCh, DPhil His research investigates fusion-driven cancers in young patients using long-read sequencing and single-cell genomics, alongside studying neurotoxicity from cancer therapies through spatial transcriptomics and developmental neuroscience perspectives. Recent work includes characterizing CLIPPERS inflammatory disorders and SLONM myopathy. Publications demonstrate expertise in CNS tumors, inflammatory pathologies, and digital pathology implementation, with methodological focus on genomic heterogeneity and precision diagnostics. NIH Director's Innovation Award Supervises DPhil students Hannah Brooks and Claire Lewis, maintaining collaborations with Oxford Brain Bank and NIH institutions while advancing translational research in neuro-oncology and neuropathology.

Yuhan JiangView profile

Assistant Professor

• Artificial Intelligence in Architecture Engineering Construction and Operations
• Robotics and Remote Sensing
• Computer Vision and Machine Learning
• +7 more

Dr. Yuhan Jiang is an Assistant Professor in the Department of Built Environment at North Carolina A&T State University's College of Science and Technology. He serves as the Founding Director of the HUD Center of Excellence for Innovation in Affordable Housing and Sustainable Communities (CIAHSC). Dr. Jiang leads a multidisciplinary research team focused on integrating robotics, artificial intelligence, and Building Information Modeling in construction operations and infrastructure management. Ph.D. in Civil Engineering from Marquette University M.M. in Construction Management from Guangzhou University Additional Construction Management degree from Guangzhou University Dr. Jiang's research primarily focuses on artificial intelligence applications in architecture, engineering, construction, and operations (AECO). His work integrates robotics and remote sensing for data collection, computer vision and machine learning for data processing, and BIM, GIS, and AR/VR for data visualization. His research enables more efficient construction operations, building inspection, and infrastructure management. Additionally, he has extensive experience in community redevelopment planning and complex systems simulation, including investigating urban village formation mechanisms. Analysis of Dr. Jiang's recent publications reveals a strong focus on applying drone technology, computer vision, and deep learning to construction and infrastructure challenges. His work spans multiple domains including façade modeling, pavement evaluation, sidewalk inspection, earthwork calculation, and 3D reconstruction. A consistent theme across his research is the development of automated systems that improve efficiency, accuracy, and safety in construction and infrastructure management through AI and robotics. N.C. A&T and CoST Junior Faculty Teaching Excellence Award 2024-25 N.C. A&T and CoST Rookie Researcher of the Year Award 2024 ASCE Journal of Architectural Engineering Best Paper Award 2022 ASCE CI & CRC Joint Conference Best Paper Award 2024 AAAS HBCU Making and Innovation Showcase 1st Place 2024 CoST SciTech Week Innovation Challenge awards (2023-2025) N.C. A&T Provost's Faculty Fellow (2023 & 2024) Dr. Jiang has successfully secured over $4.5 million in research funding as PI or Co-PI, including a $2.5 million HUD Center of Excellence grant. He has mentored students who won 1st and 3rd place in the 2023 & 2024 Sci-Tech Week Innovation Challenge competitions and 1st place at the 2024 AAAS HBCU Making and Innovation Showcase. His funded projects span AI-driven BIM education tools, smart farming with robotics, drone-based façade modeling, and digital twin applications for infrastructure management. As Founding Director of the HUD Center of Excellence for Innovation in Affordable Housing and Sustainable Communities (CIAHSC), Dr. Jiang leads a multidisciplinary team focused on innovative approaches to affordable housing and sustainable community development. His lab work integrates drone technology, computer vision, and AI to create practical solutions for real-world construction and infrastructure challenges.

Arnab NandiView profile

Professor

• Database Systems
• Human-in-the-Loop Data Analytics
• Next-Generation Query Interfaces
• +10 more

Arnab Nandi is a Professor in the Department of Computer Science & Engineering at The Ohio State University. His work bridges human interaction with data infrastructure, focusing on database systems, LLM-augmented analytics, and immersive query interfaces. Education: PhD in Computer Science & Engineering from the University of Michigan Leadership: Co-founder of OHI/O Hackathon Program and STEAM Factory interdisciplinary network Research spans human-in-the-loop data analytics , vibe querying (natural language + gestural interfaces), LLM integration into education, and climate response systems . Key projects include Omni (multimodal exploration), GestureDB , and Icarus (clinical pipelines). Recent publications analyze LLM-driven query stacks (HILDA 2025), video analytics (SIGMOD 2022), and data sunglasses for cognitive limits (HILDA 2025). Awards include NSF CAREER Google Faculty Research Award IEEE TCDE Early Career Award ACM Distinguished Member Advises students in database innovation , with alumni at Amazon, AWS, Roblox, and Meta. Teaches CSE 3241 (Database Systems), CSE 5889 (Software Startups), and CSE 5242 (Advanced Databases).

• Media Economics
• Artificial Intelligence in Communication
• Film and Audiovisual Studies
• +2 more

Dr. Mei Nan is an Associate Professor in the Department of Communication at Tongji University's School of Art and Media. With a career spanning since 2004, she previously held positions at Chang'an University before joining Tongji in 2017. Her academic credentials include a Master's from Shaanxi Normal University, postgraduate studies at Communication University of China, and ongoing doctoral research at Xi'an Jiaotong University's School of Economics and Finance. Research Expertise Her research bridges media economics, AI-driven communication paradigms, and film studies, with specific focus areas including: Media economics and corporate governance interactions Artificial intelligence's impact on communication theory Film/audiovisual language analysis Media culture evolution Marketing models in digital ecosystems Teaching Portfolio Dr. Nan teaches both undergraduate courses ( Audiovisual Language, Chinese/Foreign Film History, Media Culture, Chinese Film Appreciation ) and graduate seminars ( Intelligent Communication Theory and Practice ). Her pedagogical approach integrates contemporary media developments with theoretical foundations. Awards and Grants Tongji University Hongda Award (2021) Tongji Cup General Education Course Paper Competition Teaching Teacher Excellent Organization Award (2021) Principal Investigator: Shanghai Philosophy and Social Science Planning Project (2018BGL025) studying media impact on corporate recovery

Zhe ZhangView profile

Assistant Professor

• Business Analytics
• Fairness and Bias in Algorithms
• Sharing Economy
• +3 more

Zhe Zhang is an Assistant Professor of Innovation, Technology, and Operations at the Rady School of Management, University of California San Diego (UCSD). He holds a Ph.D. in Information Systems and Management from Carnegie Mellon University's Heinz College and dual bachelor's degrees in Economics and Statistics from Stanford University. His research focuses on the societal and spillover impacts of information technology, including fairness in algorithmic decision-making, sharing economy dynamics, and digital transformation effects. Ph.D., Carnegie Mellon University (Heinz College) B.S. in Mathematical and Computational Sciences, Stanford University B.A. in Economics (with honors), Stanford University His work spans disciplines like machine learning, applied microeconomics, and operations management. Current research includes analyzing cashierless retail technology's operational and behavioral impacts, algorithmic bias mitigation strategies, and the economic implications of Amazon Prime adoption. Key findings highlight how digital innovations reshape consumer demand, manufacturer strategies, and algorithmic fairness outcomes. Recent publications address: Bias amplification through data imputation in healthcare Strategic overfitting in data science contests Sharing economy's effect on durable goods markets He has presented at top conferences in information systems (CIST, WISE), economics (NBER), and computer science (KDD, FAccT). Awards include runner-up for the ACM SIGMIS Doctoral Dissertation Award (2019) and a POMS 2017 Supply Chain Management best paper finalist. Prior to his current role, Zhang worked as a part-time Data Creative staff member at DataKind (NYC) and was a 2016 fellow at the Data Science for Social Good Summer Fellowship (Chicago). He has also contributed to fairness methods in AI at Facebook and nonprofit research at NRDC and Union of Concerned Scientists.