Find Academic Supervisors

• Educational Technology
• Student Engagement
• Online Learning
• +3 more

Dr. Niharika Singh is a Lecturer in the UniSQ College (Pathways) at the University of Southern Queensland. She holds a BEd from the South Pacific, an MSc from the South Pacific, and a PhD from USQ. Her research spans two primary areas: educational technology and fluid dynamics. In education, she focuses on student engagement in online learning environments, interactive technologies, and widening participation programs. In fluid dynamics, her work examines solitary waves, nonlinear wave behavior, and oceanographic models. She received Seed Funding Early Research Career grant in 2023 and serves as an Associate Supervisor for doctoral research exploring effective teaching practices for remote students. Her educational research includes studies on Panopto video analytics, embedded quizzes in lecture videos, and the impact of filmic 'dark academia' on academic identity. Her fluid dynamics work analyzes modulational instability in rotating oceans and soliton dynamics in two-layer systems. Dr. Singh contributes to the academic community through affiliations with UniSQ College and collaborations on projects like Third Space Theory applications in pathways education. She has published extensively across these fields, with recent work appearing in journals like Technology, Pedagogy and Education and Wave Motion .

Wei-Chen HungView profile

Professor

• Problem Solving
• Human-Computer Interaction
• Performance Support Systems
• +7 more

Wei-Chen Hung is a Professor and Department Chair in the Department of Educational Technology, Research and Assessment at Northern Illinois University’s College of Education. He holds a Ph.D. in Instructional Systems Technology from Indiana University-Bloomington and is actively engaged in teaching, research, and leadership in educational technology. Ph.D., Instructional Systems Technology, Indiana University-Bloomington (with Minor in Information Science) His research focuses on problem solving, human-computer interaction (HCI), and performance support systems in educational contexts. He explores how technology can scaffold learning, enhance problem-solving skills, and support teachers in instructional design and classroom management. His work spans K–12, higher education, and professional training environments. The recent publications highlight a strong trend in developing and evaluating technology-enhanced learning environments, including intelligent tutoring systems, 3D virtual worlds, educational simulations, and performance support tools. These works span disciplines such as STEM education, nursing, and social sciences, reflecting an interdisciplinary approach to solving instructional challenges through technology. Wei-Chen Hung has secured significant research funding from agencies including the National Science Foundation, NASA, and the Illinois Department of Education. He has served as Principal Investigator and Co-Principal Investigator on multiple grants focused on educational simulations, research methods training, and assistive technologies. National Science Foundation: Web-based Interactive Landform Simulation Model (WILSIM), $236,041, 2013–2016 (Senior Faculty Expert) Elgin Community College: Information security awareness, $10,000, 2011–2012 (Principal Investigator) National Science Foundation: Intelligent tutoring system for research methods, $150,000, 2008–2012 (Co-Principal Investigator) NASA: MARS Valley Networks Project, $20,000, 2005–2007 (Faculty Expert) Illinois Department of Education: Assistive technology for blind and visually impaired children, $75,000, 2005–2007 (Faculty Expert) He has contributed to the development of software tools and systems such as the Cause and Consequence behavior management system and performance support systems for educators. His lab and research initiatives emphasize applied design, usability testing, and evaluation of educational technologies in real-world settings.

Keenan CraneView profile

Associate Professor

• Computer Science
• Mathematics
• Scientific Computing
• +7 more

Keenan Crane is the Michael B. Donohue Associate Professor of Computer Science and Robotics at Carnegie Mellon University , with membership in the Center for Nonlinear Analysis and mentorship in the Geometry Collective . His research bridges differential geometry and computer science to develop fundamental algorithms for geometric data processing. Education : BS from University of Illinois at Urbana-Champaign, PhD from Caltech Fellowships : Google PhD Fellow, NSF Mathematical Sciences Postdoctoral Fellow Research focuses on Discrete Differential Geometry , addressing PDE solutions, mesh processing, and geometric modeling through methods like: Walk on Spheres for PDEs Intrinsic Triangulations for robust geometry Repulsive Energy formulations for collision avoidance Recent publications span 2025–2021 , emphasizing grid-free algorithms , anisotropic mesh generation , and differentiable systems . Scientific accolades include Packard Fellowship and NSF CAREER Award . Students include Nicole Feng , Olga Gutan , and Zoë Marschner . During his 2024 sabbatical at Roblox , he does not accept new researchers. Key software contributions include Penrose (math diagram generation) and I♥Mesh (domain-specific language for mesh algorithms).

Damir IsovicView profile

Associate Professor

• Real-Time Systems
• Embedded Systems
• Scheduling Algorithms
• +3 more

Damir Isovic is an Associate Professor and Vice-Chancellor for Internationalization at Mälardalen University's Academy of Innovation, Design and Technology. Previously, he served as Dean of the School of Innovation, Design and Engineering. His roles include leadership in academic administration and participation in national boards. He holds a PhD and has extensive international teaching experience. Research focuses on real-time systems, embedded systems design, and scheduling algorithms. Notable contributions include seminal work in real-time scheduling recognized by the IEEE Technical Community on Real-Time Systems. He has organized major conferences and delivered keynotes globally. His publications emphasize hybrid scheduling approaches, real-time operating systems (RTOS), media processing in resource-constrained systems, and MPEG standards. Recent work integrates memetic algorithms with fuzzy controllers and explores multi-core scheduling fairness. His research bridges theoretical scheduling models with practical embedded system implementations. No scientific awards explicitly listed in the text. Advising activities include supervising PhD students, though specific names are not provided. Lab affiliations include the Division of Networked and Embedded Systems, where he develops frameworks like GENESIS for embedded system engineering. His work emphasizes cross-disciplinary collaboration and industry partnerships in education and technology development.

• Multi-agent Systems
• Intelligent Tutoring Systems
• Artificial Intelligence in Education
• +5 more

Ricardo Azambuja Silveira is a Professor at the Federal University of Santa Catarina, Brazil, with a distinguished research career spanning over two decades in the fields of multi-agent systems, intelligent tutoring systems, and semantic web technologies for education. His work bridges artificial intelligence with educational technology, creating innovative frameworks for adaptive learning environments and intelligent educational agents. Dr. Silveira's research interests focus on developing agent-based approaches to enhance educational experiences through technologies like BDI (Belief-Desire-Intention) architectures, ontology-based systems, and multi-context reasoning. His work particularly emphasizes the integration of intelligent agents with learning management systems to create personalized educational experiences. His recent publications demonstrate a continued evolution from foundational multi-agent frameworks to sophisticated neural-symbolic integrations and context-aware educational technologies. Throughout his career, he has published over 60 scholarly works, with consistent output from 2001 through 2024, demonstrating sustained research productivity. His publication trends show a clear trajectory from early work on JADE (Java Agent Development Framework) for distance education to current research on neural-symbolic integration in agent systems. The majority of his publications appear in prominent conferences like PAAMS, MICAI, and ICAART, reflecting his standing in the multi-agent systems community. Dr. Silveira has mentored numerous researchers who have become his frequent collaborators, including Arnoldo Uber Junior, Rodrigo Rodrigues Pires de Mello, and Thiago Ângelo Gelaim. His research has been supported through various academic grants that enabled the development of frameworks like Sigon (a multi-context system framework) and iEnsemble (for committee machine learning). He has been actively involved in the organization of academic events, particularly the Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL) conference series, where he has served as both participant and organizer. His work contributes significantly to the theoretical foundations and practical implementations of intelligent educational technologies.

Stefan WalzelView profile

Researcher

• Corporate Social Responsibility (CSR)
• Commercialization of Sport
• Sustainable Development Goals (SDG)
• +3 more

Dr. Stefan Walzel is a researcher at the Institute of Sport Economics and Sport Management (Section Sports Business Administration) at German Sport University Cologne. With a PhD in Sport Science (2010) and a diploma in Sport Economics, he focuses on Corporate Social Responsibility (CSR) in sports, commercialization impacts, and UN Sustainable Development Goals (SDGs) . His work intersects sport studies , organizational ethics , and sustainability frameworks . PhD in Sport Science (German Sport University Cologne, 2010) Diploma in Sport Economics (German Sport University Cologne, 2005) Student exchange at Victoria University of Technology (Melbourne, 2004-2005) Studies in Business Administration (Distance Learning University Hagen, Humboldt University Berlin, 1997-2002) His research explores CSR implementation in sports, governance practices, and sustainability challenges in major sporting events. Projects include CSR-Score Card and co-hosting event sustainability analysis , with findings published in journals and anthologies. Recent works address ethical sponsorship strategies and SDG alignment. Notable scientific awards include the EASM Distinguished Service Award (2022) . He serves on editorial boards and academic councils, with over 74 publications and 8 projects. Collaborations span researchers like Sebastian Uhrich, Kirstin Hallmann, and Christoph Breuer. He actively contributes to international sports policy discussions and industry knowledge transfer.

• New Product Development
• Knowledge Management
• Collaborative Work Environments
• +5 more

Angelo Corallo is an Associate Professor at the Department of Experimental Medicine, University of Salento, specializing in technologies and methodologies for collaborative processes in industrial systems. His research spans Digital Business Ecosystems , Cybersecurity , and Collaborative Product Design , focusing on the interplay between technology and organizational dynamics. He leads interdisciplinary research divisions in Open Networked Business Management , Learning and Innovation , and Collaborative Product Design . Research Interests : Corallo's work integrates Information and Communication Technologies (ICT) with Business Management, particularly in Digital Twins for healthcare and manufacturing Knowledge Modeling and Ontology Engineering Industry 4.0 and Smart Manufacturing Agri-Food Sustainability through digitalization Scientific Contributions : His recent articles explore trends in Cybersecurity for Industrial IoT Metaverse Applications in business models Traceability Systems in food supply chains Collagen-Based Biomaterials from aquaponics

Magdalena FuentesView profile

Assistant Professor

• Machine Listening
• Human-Centered Machine Learning
• Multimodal Representation Learning
• +3 more

Magdalena Fuentes is an Assistant Professor of Music Technology and Integrated Design & Media at New York University (NYU), affiliated with the Music and Audio Research Lab (MARL) and the Integrated Design & Media (IDM) programs. She holds a Ph.D. from Université Paris Saclay (France) and a B.Eng. in Electrical Engineering from Universidad de la República (Uruguay). Her research focuses on Machine Listening, Human-Centered Machine Learning, and Multimodal Representation Learning, with applications to Music Information Retrieval and Environmental Sound Analysis. Previously, she served as a Postdoctoral Faculty Fellow at NYU’s MARL and Center for Urban Science and Progress (CUSP). Her work bridges technical innovation with cultural and societal contexts, particularly in underrepresented music traditions like Brazilian percussion and Candomblé rituals. She has developed open-source tools such as Soundata to ensure reproducible audio dataset usage. Her research outputs span audio-visual synchronization (e.g., SONIQUE), environmental sound monitoring (e.g., SONYC projects), and rhythm analysis frameworks (e.g., Carat toolbox). These contributions highlight her dual focus on advancing machine learning techniques while maintaining human-centric and culturally sensitive applications.

• Human-Computer Interaction
• Social Computing
• Artificial Intelligence
• +5 more

Bongwon Suh is a Professor in the Department of Computer Science at the Korea Advanced Institute of Science and Technology (KAIST), College of Computing. With a prolific publication record spanning over two decades, Suh has established himself as a leading researcher in Human-Computer Interaction, Social Computing, and Artificial Intelligence applications. His research interests focus on Human-Computer Interaction, Social Computing, Artificial Intelligence, Large Language Models, Information Visualization, Recommender Systems, Multi-Agent Systems, and Accessibility Technologies. Suh's work often explores the intersection of social dynamics and technological systems, examining how AI and interactive systems can enhance human experiences in diverse contexts including education, entertainment, communication, and accessibility. Recent publications (2023-2025) demonstrate a strong focus on Large Language Model applications, with significant contributions in social simulation for education, conversational AI systems, multi-agent coordination, and accessibility technologies. His work frequently appears in top-tier venues including CHI, CSCW, UIST, and SIGIR, reflecting the high impact of his research. Suh has collaborated extensively with researchers across KAIST and internationally, with frequent co-authors including Changhoon Oh, Kyusik Kim, Hyungwoo Song, and Jeongwoo Ryu. His research program consistently bridges theoretical insights with practical applications, particularly in developing systems that enhance human social experiences through technology.

• Industrial Systems
• Entrepreneurship
• Agility Applications
• +3 more

Emory W. Zimmers is a Professor and Director of the Enterprise Systems Center (ESC) at Lehigh University's Department of Industrial and Systems Engineering. He holds multiple degrees from Lehigh, including a Ph.D., M.S., and two B.S. degrees in Industrial and Mechanical Engineering. His research focuses on industrial systems design, agility in manufacturing, entrepreneurship, leadership development, and innovative educational technologies. Education: Ph.D., Industrial Engineering, Lehigh University M.S., Industrial Engineering, Lehigh University B.S., Mechanical Engineering, Lehigh University B.S., Industrial Engineering, Lehigh University Research Interests: Dr. Zimmers leads interdisciplinary projects blending academia, industry, and government. His work emphasizes system agility, logistics optimization, and transformative education methods. He has authored/co-authored 76 papers, 288 technical reports, and the textbook CAD/CAM: Computer-Aided Design and Manufacturing (with Dr. Mikell P. Groover). Awards: Fellow, Institute of Industrial and Systems Engineers (IISE) Fellow, Society of Manufacturing Engineers (SME) Recipient of Lehigh's Alfred Noble Robinson Faculty Award Recipient of the Christian & Mary Lindback Award for Distinguished Teaching Advising & Grants: Principal investigator on over 1,000 research projects with 400+ industry partners. Courses taught include leadership development, computer-integrated manufacturing, and the senior capstone project. Labs/Teams: Director of the Enterprise Systems Center, a hub for collaborative innovation in industrial systems and entrepreneurship.

• Machine Learning
• Information Fusion
• Data Clustering
• +3 more

Julien Ah-Pine is a lecturer at Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS) under Université Clermont Auvergne , with affiliations at Institut national polytechnique Clermont Auvergne and École des Mines de Saint-Étienne . He also holds a Researcher position at CNRS. Research Interests His work spans machine learning , information fusion , aggregation functions , and multi-criteria decision support , with a focus on complex data types like graphs , functional data , and multi-view datasets . Recent publications emphasize anomaly detection in spectral data streams , online learning , and interpretable AI for industrial applications. Selected Publications 2025 work on OnlineBootKNN introduces a novel framework for real-time spectral anomaly detection, while 2024 research explores multiple kernel methods in functional data classification. Earlier studies cover graph-based clustering , relational data mining , and linguistic network models for NLP tasks. Laboratory & Collaborations Works within LIMOS laboratory at Université Clermont Auvergne, collaborating with institutions like Mines Saint-Étienne and CNRS. Key partnerships include Nicolas Rojas Varela and Engelbert Mephu Nguifo on data stream analysis projects.

Lei ChenView profile

Professor

• Data-Driven Machine Learning
• Crowdsourcing-Based Data Processing
• Uncertain and Probabilistic Databases
• +3 more

Lei Chen is a Chair Professor and Director of HKUST Big Data Institute at the Hong Kong University of Science and Technology , where he has served since 2005. His research spans data-driven machine learning , crowdsourcing systems , and uncertain database processing , with notable contributions in privacy-preserving spatial queries and graph neural networks . Ph.D. in Computer Science, University of Waterloo (2004) MS in Computer Science, Asian Institute of Technology (1997) BS in Computer Science, Tianjin University (1994) His work focuses on: Spatial Crowdsourcing - Efficient task assignment and privacy frameworks Graph Processing - Novel indexing for heterogeneous networks Explainable AI - Human-centric model interpretation techniques Uncertain Data - Probabilistic query processing with crowdsourcing Recent publications cluster around secure data federation , distributed graph training , and privacy-preserving mobility systems , reflecting his leadership in ACM and IEEE communities. Students include 15 active Ph.D. candidates and 20+ graduated researchers now at institutions like BeiHang University and Huawei Noah's Ark Lab . Awards: ACM Fellow (2024), VLDB Best Paper (2022), SIGMOD Test-of-Time Award (2015).

Corrado LoglisciView profile

Assistant Professor

• Temporal Data Mining
• Temporal Learning
• Textual Data Mining
• +13 more

Corrado Loglisci is an Assistant Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. His research focuses on Temporal Data Mining , Machine Learning , and Quantum Computing , with applications in bioinformatics, medical informatics, and cybersecurity. He earned his Ph.D. in Computer Science with a thesis on temporal projection in longitudinal data. Research Highlights : Temporal Learning, Textual Data Mining, Quantum-Classical Hybrid Systems Collaborations : IRSTEA Research Institute (France), Aristotle University of Thessaloniki (Greece) His publications address dynamic network analysis , emotion detection in social media , and quantum-enhanced classification . He contributes to program committees and journal editorial work, including a special issue on Mining Complex Patterns in the Journal of Intelligent Information Systems . Notable contributions include the jKarma framework for change detection and studies on concept drift robustness in intrusion detection systems. His work spans European/National research projects, leveraging machine learning for tasks like mobile crowd sensing trustworthiness prediction (2020) and investor behavior analysis (2023-2025).

• Avian Migration
• Evolutionary Ecology
• Climate Change Adaptation
• +3 more

Prof. Christiaan Both is a Professor of Animal Ecology at the University of Groningen's Faculty of Science and Engineering, affiliated with the Groningen Institute for Evolutionary Life Sciences. His research focuses on avian migration, climate change impacts, and ecological adaptation, particularly in migratory birds. He holds leadership roles in scientific advisory boards such as SOVON and the Netherlands Ornithologists Union. Both studied Biology at Wageningen, Groningen, and Oxford, completing a PhD on avian reproductive ecology in 1998. He held postdoctoral positions globally before joining Groningen in 2004. Key research themes include phenological mismatch in migratory birds, climate-driven habitat shifts, and dispersal strategies in response to environmental change. His work has been featured in Science , Nature , and Current Biology , and he has received grants from NWO, NATO, and the Prins Bernhard Fund. Notable contributions include documenting climate-related shifts in bird migration timing and population declines in long-distance migrants. Both advises on conservation policies and has engaged the public through media outlets like TIME Magazine and National Geographic. His current projects explore genetic and behavioral mechanisms enabling bird populations to adapt to global environmental changes.

Venkatesh SaligramaView profile

Professor

• Machine Learning
• Video Analysis
• Statistical Signal Processing
• +3 more

Venkatesh Saligrama is a Professor in the Department of Electrical and Computer Engineering at Boston University, with affiliations in Systems Engineering, the Center for Information and Systems Engineering, and the College of Arts & Sciences’ Computer Science division. He holds a PhD from MIT (1997) and leads the Data Science & Machine Learning Lab. His research focuses on Machine Learning, Video Analysis, Statistical Signal Processing, and Network Science, with notable contributions to vision-language models, bandit algorithms, and synthetic data strategies. He has received prestigious awards like the NSF CAREER Award (2005) and Presidential Early Career Award (2003). His teaching includes courses on signals, stochastic processes, and digital communication systems. Saligrama’s work bridges theoretical foundations and applied systems, emphasizing efficient learning under constraints. His recent publications explore zero-shot detection, data-efficient pretraining, and safe optimization techniques. Beyond academia, his research impacts domains like autonomous systems, healthcare prediction, and cybersecurity. He actively contributes to editorial roles, conferences, and interdisciplinary initiatives, fostering collaborations across engineering and computer science.