Find Academic Supervisors

Naveen Naik SapavathView profile

Academic

• 5G/Next-G Cellular Networks
• Open Radio Access Network (O-RAN) Architecture and Security
• AI/ML for Wireless Resource Optimization
• +5 more

Naveen Naik Sapavath is an Assistant Teaching Professor at Northeastern University's Electrical and Computer Engineering department. He holds a PhD from Howard University and a Master's from the Indian Institute of Science (IISc). His research focuses on next-generation cellular systems including O-RAN security, AI/ML-driven wireless optimization, and low-latency communications. He is affiliated with Northeastern's Institute for the Wireless Internet of Things. Education: PhD in Electrical and Computer Engineering, Howard University Master of Engineering in Electrical Engineering, Indian Institute of Science Research Interests: Dr. Sapavath explores cutting-edge areas such as 5G/Next-G networks, cybersecurity in wireless systems, and applying game theory to resource allocation. His work bridges theoretical advancements with practical implementations in AI-driven network architectures. Awards: IEEE CSCloud 2021 Best Student Paper Award Multiple NSF Student Travel Grants Professional Experience: Previously served as Postdoctoral Researcher at UC Davis, Researcher at George Mason University's Next G Lab, and Technical Project Manager at Iowa State University for the NSF-funded ARA project. Serves as reviewer for IEEE journals including Transactions on Cognitive Communications and Networking. Labs/Initiatives: Active contributor to Northeastern's Institute for the Wireless Internet of Things and NSF PAWR program through the ARA project.

• Smart Energy Systems
• Multi-agent Systems
• Computational Intelligence
• +7 more

Han La Poutré is a Professor at Delft University of Technology and a Senior Researcher/Manager at CWI's Intelligent and Autonomous Systems group. His research focuses on multi-agent systems, computational intelligence, and optimization techniques for Smart Energy Systems (SES), integrating electrical engineering and economics frameworks. M.Sc. in Mathematics (1986, TU Eindhoven) Ph.D. in Computer Science (1991, Utrecht University) His work spans game theory , reinforcement learning , and market mechanism design for energy grid optimization, addressing challenges in congestion management, demand-side bidding, and AI-driven media sector innovation. Recent projects include AI, Media & Democracy Lab and RESCUE (Cyber-Physical Energy Security). Key trends in his 2020-2025 publications include: Hybrid fairness/welfare frameworks for grid congestion Double-sided auction mechanisms for heat/power markets Deep reinforcement learning in discrete action spaces Game-theoretical cybersecurity modeling Multi-temporal demand response coordination Scientific Awards 2015: Best paper award at GECCO-2015 He has led NWO-funded projects like Computational Capacity Planning in Electricity Networks and served as Vice President of ERCIM. Current affiliations include ACM Transactions on Intelligent Systems editorial board.

Shuva PaulView profile

Researcher

• Machine Learning
• Deep Learning
• Game Theory
• +11 more

Shuva Paul is a Researcher at NREL's Energy Security and Resilience Center , specializing in power systems cybersecurity . His work focuses on collaborative autonomy, computational intelligence, reinforcement learning, game theory, smart grid security , and critical infrastructure protection . Research Interests: Machine learning and deep learning for critical infrastructure systems Event and anomaly detection in power grids Supply chain cybersecurity Cyber-physical energy systems security and resilience Professional Experience: Postdoctoral Fellow, Georgia Institute of Technology (Feb 2021–May 2022) Postdoctoral Research Associate, Washington State University (Jun 2020–Jan 2021) Graduate Intern, NREL (May 2019–May 2020) Graduate Research Assistant, South Dakota State University (2016–2019) Education: PhD, Electrical Engineering, South Dakota State University Master of Electrical and Electronics Engineering, American International University - Bangladesh Bachelor of Electrical and Electronics Engineering, American International University - Bangladesh Advisory and Editorial Contributions: Paul has served as a session chair at IEEE EnergyTech (2013) and IEEE Electro Information Technology (2019) conferences, and as a reviewer for journals like IEEE Transactions on Smart Grid and Neurocomputing . He also acted as a guest editor for the Journal of Sensor and Actuator Networks .

Ole-Christoffer GranmoView profile

Professor

• Machine Learning
• Artificial Intelligence
• Tsetlin Machines
• +7 more

Professor Ole-Christoffer Granmo is a distinguished academic at the University of Agder, Norway, where he serves as Professor in the Department of Information and Communication Technology. He is the Founding Director of the Centre for Artificial Intelligence Research (CAIR) at the University of Agder, leading cutting-edge research in artificial intelligence and machine learning. Dr. Granmo obtained his master's degree in 1999 and his PhD in 2004, both from the University of Oslo. His academic journey has been marked by significant contributions to the field of AI, most notably the creation of the Tsetlin machine in 2018, for which he received the AI research paper of the decade award from the Norwegian Artificial Intelligence Consortium (NORA) in 2022. Professor Granmo's research primarily focuses on logical and causal world modeling across multiple modalities including images, sound, and natural language. His work spans logical auto-encoding, convolution, regression, transformer architectures, and reinforcement learning, all with the overarching goal of creating ultra-low-power artificial general intelligence through transparent logical learning and reasoning. His publications reveal a strong emphasis on interpretable AI systems, hardware implementations, and applications across diverse domains including cybersecurity, healthcare, social media analysis, and bioinformatics. AI Research Paper of the Decade (2022) - Norwegian Artificial Intelligence Consortium (NORA) Eight paper awards in machine learning Professor Granmo has coordinated over seven research projects and mentored 55+ master's students and nine PhD students. His leadership extends to co-founding the Norwegian Artificial Intelligence Consortium (NORA) and establishing two companies: Anzyz Technologies AS and Tsense Intelligent Healthcare AS. As an advisor at Literal Labs, he actively bridges academic research with practical industry applications, demonstrating his commitment to translating theoretical innovations into real-world solutions that address complex challenges across multiple sectors.

Bruce M. McLarenView profile

Professor

• Learning Sciences
• Educational Technologies
• Human-Centered AI
• +7 more

Bruce M. McLaren is a Professor at Carnegie Mellon University's Human-Computer Interaction Institute (HCII), where he heads the McLearn Lab. He previously served as President of the International Artificial Intelligence in Education Society (2017-2019) and has been elected to the Executive Committee of the AI-ED Executive Committee for two separate terms (2012-2017 and 2022-2027). Dr. McLaren's research focuses on how technology can support education through digital learning games , intelligent tutoring systems , and collaborative learning environments. His work has demonstrated that students can learn decimals more effectively through Internet-based learning games compared to conventional methods. He has also conducted significant research on erroneous examples in learning, showing how students benefit from working with incorrect solutions alongside intelligent tutors. His publications reveal a strong trend toward integrating artificial intelligence with educational technologies, particularly in analyzing student learning patterns, developing adaptive educational games, and creating tools that support both students and teachers in classroom settings. Recent work increasingly focuses on the application of generative AI like ChatGPT in educational contexts. Best Paper Award at ECTEL 2023 for research on ChatGPT in decimal learning Fulbright Scholarship recipient for educational technology work in Chile (2019) Multiple best paper awards at major AI in Education conferences Erskine Fellowship for teaching Intelligent Tutoring Systems in New Zealand As an advisor, Professor McLaren has mentored numerous students in the HCII program and has secured significant research funding, including NSF grants for projects like AdaptErrEx and LASAD. His lab, the McLearn Lab, serves as a hub for interdisciplinary research at the intersection of learning sciences and artificial intelligence. Beyond academia, he brings over 20 years of commercial sector experience, having served as Director of eCommerce Technologies at OpenWebs Corporation and leading expert system projects at Carnegie Group, Inc.

• Graph Neural Networks
• Social Network Analysis
• Machine Learning
• +3 more

Ambuj K. Singh is a Professor in the Department of Computer Science at the University of California, Santa Barbara . With over 278 publications since 1987, his work spans graph neural networks, social network dynamics, and interdisciplinary applications in neuroimaging and cheminformatics. Key collaborations with researchers like Sourav Medya, Arlei Silva, and Francesco Bullo Contributions to network design, opinion dynamics, and interpretable AI His research integrates machine learning with graph theory , addressing problems in community detection , influence limitation , and explanation generation . Recent work focuses on counterfactual explainers and molecular graph analysis . He has contributed to venues like KDD, NeurIPS, WWW, and ICLR, often exploring temporal networks and polarized embeddings .

Jie LiView profile

Adjunct Professor

• Human-Computer Interaction (HCI)
• User Experience (UX) Design
• Extended Reality (XR)
• +7 more

Dr. Jie Li is a dual-career academic and creative professional with a PhD in Industrial Design Engineering from Delft University of Technology. As an HCI/UX researcher in industry and Adjunct Professor at multiple institutions, she bridges academia and practice through work on Extended Reality (XR) , Human-AI interactions , and user experience evaluation . Her ACM Interactions column 'Bits to Bites' explores interdisciplinary research methodologies. Education: MSc in Industrial Design Engineering, Delft University of Technology PhD in Industrial Design Engineering, Delft University of Technology (2019) Her research spans social VR platforms , AI-augmented cognition , and privacy-preserving emotion detection , with recent publications analyzing LLM-assisted game design , harassment detection in VR , and XR's impact on remote collaboration . She has received Best Demo Awards (2020, 2022) and the ACM Best Paper Award (2018). Notable trends in her work include emerging immersive technologies (XR, 6DoF displays), human-AI collaboration frameworks , and cross-domain applications from medical VR clinics to cultural heritage experiences . Her advocacy for synthetic UX research and asynchronous co-creation tools reflects industry-academia hybrid innovation. Scientific Awards: Best Demo Award (2020, ACM TVX/IMX 2020) Best Demo Award (2022, ACM Multimedia) ACM Best Paper Award (2018, ACM TVX) While maintaining active roles in CHI conference committees and guest lecturing , Jie also operates a Delft-based creative cake design business , demonstrating her commitment to interdisciplinary exploration and 'slash career' balance between technical research and artistic practice.

Alla ShefferView profile

Professor

• Geometry Processing
• Computer Graphics
• Discrete Geometry
• +7 more

Alla Sheffer is a Professor and Associate Head of Faculty Affairs in the Department of Computer Science at the University of British Columbia, Faculty of Science. She is affiliated with multiple research centers including CAIDA (Centre for Artificial Intelligence Decision-making and Action), the Institute of Applied Mathematics, and ICICS (Institute for Computing, Information and Cognitive Systems). B.Sc., Hebrew University, Jerusalem (1991) M.Sc., Hebrew University, Jerusalem (1995) Ph.D., Hebrew University, Jerusalem (1999) Postdoctoral Research Associate, University of Illinois, Urbana-Champaign (1999-2001) Assistant Professor, Technion, Israel (2001-2003) Assistant Professor, University of British Columbia (2003-2008) Associate Professor, University of British Columbia (2008-present) Professor Sheffer's research focuses on geometry processing, addressing algorithmic challenges in digital shape modeling and manipulation. Her work primarily deals with discrete geometry representations, specifically meshes (polygonal model representations), with applications in computer graphics and computer-aided engineering. She utilizes tools from computational and differential geometry, discrete mathematics, and graph theory to generate, manipulate, and edit discrete geometric models. Her research spans virtual and augmented reality, visual computing, and 3D modeling, with significant contributions to sketch-based modeling, mesh processing, and cloth simulation. The 15 most recent publications reveal a consistent research trajectory in geometry processing, with recent work focusing on vector sketch processing, VR drawing tools, and advanced mesh manipulation techniques. Her work demonstrates a strong connection between human perception and computational methods, particularly in the interpretation of freehand sketches and the generation of perceptually-accurate geometric representations. The recurring themes across her publications include flowlines, curve networks, mesh parameterization, and the application of perceptual studies to improve algorithmic outputs. Eurographics Fellow ACM Fellow IEEE Fellow Royal Society of Canada Fellow SIGGRAPH Academy Member UBC Killam Research Prize NSERC Discovery Accelerator Supplement IBM Faculty Award Professor Sheffer has supervised numerous doctoral and master's students, with recent theses focusing on geometric mesh processing, vector sketch interpretation, VR drawing tools, and garment modeling. Her research group maintains strong connections with industry through various partnerships and has received substantial grant funding to support their innovative work in geometry processing and computer graphics. She teaches courses in computer graphics, geometric modeling, and video game programming, contributing significantly to both undergraduate and graduate education in computer science.

• Educational Technology
• Smart Learning Environments
• Digital Entrepreneurship
• +3 more

Pedro Antonio Garcia Tudela is a researcher at Universidad de Murcia specializing in Educational Technology, with a focus on Smart Learning Environments and Digital Entrepreneurship. He completed his PhD in 2023 with a thesis on intelligent learning environments supervised by Dr. María Paz Prendes Espinosa and Dr. Isabel María Solano Fernández. His educational background centers on advanced educational technology studies at Universidad de Murcia, culminating in his 2023 doctoral dissertation that established foundational frameworks for smart learning environments. This research positioned him at the forefront of educational innovation in Spanish-speaking contexts. Garcia Tudela's research explores the intersection of digital tools and pedagogical innovation, with emphasis on gamification, computational thinking development through Arduino, and digital entrepreneurship education. His work addresses critical gaps in teacher training for future classrooms and develops practical models like EmDigital for fostering entrepreneurial competencies in digital contexts. He investigates how educational escape rooms, flipped learning, and gender-inclusive technology integration transform learning experiences across K-12 and higher education. Analysis of his 15 most recent publications reveals a clear trajectory toward practical applications of educational technology: 40% focus on digital entrepreneurship frameworks, 30% on smart learning environment design, and 30% on gamification and computational thinking implementation. His research increasingly addresses cross-cultural applications, with comparative studies of future classrooms in Spain and Portugal. As an active thesis supervisor within the Educational Technology research group, Garcia Tudela mentors students in developing innovative educational methodologies. His work demonstrates strong industry-academia connections through practical frameworks for professional development and employability. The Educational Technology research group serves as his primary collaborative environment, driving projects that translate theoretical models into classroom applications while addressing contemporary challenges in digital education transformation.

Massimo FranceschettiView profile

Professor

• Mathematical Engineering
• Networked Control Systems
• Information Theory
• +7 more

Massimo Franceschetti is a Professor in the Department of Electrical and Computer Engineering at the University of California, San Diego (UCSD), with faculty affiliation at Calit2. His research spans mathematical engineering, focusing on control, communication, computation, and sensing, particularly in complex networks and systems. He integrates tools from statistical physics, wave propagation, and information theory to analyze and design networked systems. Born in Naples, Italy, he studied at the University of Naples Federico II and the University of Edinburgh (European exchange program), graduating in 1997. He earned his M.Sc. (1999) and PhD (2003) from Caltech, where he received the Walker von Brimer Award and the C.H. Wiltz Prize for outstanding research and thesis. After postdoctoral work at UC Berkeley (2003-2004), he joined UCSD as faculty and held visiting positions at Vrije Universiteit Amsterdam, EPFL (Switzerland), and the University of Trento (Italy). He became an IEEE Fellow in 2018 and was nominated a Guggenheim Fellow in 2019. His research includes networked control systems , stochastic geometry , electromagnetic information theory , and social dynamical systems . Recent work explores non-invasive emotional contagion in social networks, quantum limits on information entropy, and the physics of wave propagation. His publications bridge information theory , machine learning , and network science , often applying percolation theory and random walks to explain scaling laws and wireless signal behavior. Scientific accolades include the S.A. Schelkunoff Transactions Prize , IEEE Communications Society Best Tutorial Paper Award , and the IEEE Ruberti Young Researcher Prize . He co-authored two books: Random Networks for Communication (2007) and Wave Theory of Information (2018). His students have pursued careers in academia (e.g., IIT-Bombay, Notre Dame) and industry (e.g., Google, IBM, Tesla). He teaches courses on network science , information theory , and control systems , emphasizing data-driven analysis and the physical foundations of communication. His group’s work impacts cyber-physical systems , quantum network coding , and epidemic modeling on networks .

• Software Technology
• Artificial Intelligence
• Educational Software
• +5 more

Maria Virvou serves as Professor and Chair of the Department of Informatics at the University of Piraeus, where she also directs the Graduate Program in Informatics and leads the Research Laboratory 'Software Technology'. She holds significant institutional leadership roles including membership in the University Senate and has chaired the Department of Informatics for multiple terms. As Editor-in-Chief of Springer book series 'Learning and Analytics in Intelligent Systems' and 'Artificial Intelligence-Enhanced Software and Systems Engineering', she maintains substantial academic influence across international scholarly platforms. Dr. Virvou earned her PhD in Computer Science and Artificial Intelligence from the University of Sussex with a scholarship from the State Scholarships Foundation, a Master of Science in Computer Science from University College London, and her undergraduate degree from the Department of Mathematics at the National and Kapodistrian University of Athens. Her educational background in both mathematics and computer science has provided a strong foundation for her interdisciplinary research approach. Professor Virvou's research spans Software Technology, Artificial Intelligence, Educational Software and Games, User Modeling, and Human-Computer Interaction. She has pioneered work in personalized interactive software systems, applying fuzzy logic and machine learning techniques to create adaptive educational environments. Her recent work demonstrates a strategic expansion into AI applications for healthcare, with significant contributions to medical diagnostics using large language models and multimodal AI systems. She has also made notable advances in smart tourism applications through personalization techniques. With over 400 publications to her name, Professor Virvou's scholarly output shows a clear progression from foundational work in user modeling toward increasingly sophisticated AI applications across multiple domains. Her publication trends reveal a strategic focus on explainable AI, multimodal systems, and practical implementations that bridge theoretical advances with real-world applications, particularly in healthcare and education sectors. Ranked #1 worldwide in 'User Modelling' publications (147,450 total publications) according to Scopus Ranked #1 worldwide in 'Educational Software' publications according to both Scopus and Microsoft Academic Search Recognized among the top 2% of most influential Artificial Intelligence scientists worldwide by Stanford University General Co-Chair at the 14th IISA Conference 2023 Invited Keynote Speaker at the 35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023) As Director of the Research Laboratory 'Software Technology', Professor Virvou has built a robust research team focused on AI applications across multiple domains. She co-founded and co-chairs the IEEE Intelligent Information Systems and Applications international conference series, creating a significant platform for scholarly exchange. Her leadership extends to editorial roles with major academic publishers and active participation in international research collaborations that have secured substantial funding for innovative projects in AI and software engineering.

Sebastian von MammenView profile

Professor

• Games Engineering
• Virtual Reality
• Interactive Simulations
• +3 more

Prof. Dr. Sebastian von Mammen is a tenured professor at the University of Würzburg's Institute for Computer Science, where he heads the Games Engineering research group and contributes to the Chair for Human-Computer Interaction. His group leads the Games Engineering academic program. Previously, he completed his habilitation (2012-2016) at the University of Augsburg's Chair of Organic Computing and was a postdoctoral fellow at the University of Calgary. His research spans: Real-Time Interactive Systems : Visual programming, immersion techniques, software engineering Interactive Simulations : Serious games for healthcare/logistics/construction Artificial Life : Self-organisation, adaptive systems, evolutionary computation Artificial Intelligence : Agent-based modeling, procedural content generation Recent publications (2023-2025) demonstrate strong focus on: Virtual reality applications in education (femtoPro optics simulator, BrainBuilder neuroanatomy) Healthcare technology platforms (VIA-VR for medical serious games) Game mechanics analysis (Match-3, Jump'n'Run flow) AI-driven emotion recognition and interactive systems Computational modeling of biological systems He leads the Games Engineering research group and previously participated in the Evolutionary and Swarm Design group (Calgary) and LINDSAY project. His lab develops VR simulations for scientific training and serious games applications.

Genya IshigakiView profile

Assistant Professor

• 5G and Beyond Networking
• Network Slicing
• Reinforcement Learning
• +5 more

Genya Ishigaki is an Assistant Professor in the Department of Computer Science at San José State University's College of Science. His research focuses on network slicing, combinatorial optimization, and reinforcement learning, addressing resource allocation challenges in next-generation telecommunications networks. Ph.D. in Computer Science, The University of Texas at Dallas, 2021 M.S. in Computer Science, The University of Texas at Dallas, 2021 M.S. in Engineering, Soka University, Japan, 2016 B.S. in Engineering, Soka University, Japan, 2014 Dr. Ishigaki's work explores adaptive network control through machine learning and combinatorial optimization, including elastic network slices , explainable AI , and federated learning . His research addresses critical tradeoffs in resource utilization versus capacity reservation for future demands. Recent publications demonstrate his focus on network automation (2025), information diffusion (2025), federated learning platforms (2024), and DDoS attack detection (2024). Articles span network security , AI-driven optimization , and social network dynamics . NSF Student Travel Grant (2019) Shigeta Education Foundation Ph.D. Scholarship (2019-2021) Outstanding TA Award (2019) JASSO Ph.D. Scholarship (2016-2019) NEC C&C Foundation Travel Grant (2015) He leads the Interconnect Lab, which investigates accountability in autonomous network operations and edge computing-oriented federated learning. His grants include SJSU's RSCA Seed Grant (2022-2023) and University Grant Academy Award (2022).

Aysegul Liman-KabanView profile

Assistant Professor

• Immersive Learning (AR/XR/Gamification)
• STEM Education
• Teacher Digital Competencies
• +7 more

Aysegul Liman-Kaban serves as an Assistant Professor in ICT/Digital Learning STEM Education at Maynooth University. Her work focuses on integrating immersive technologies like augmented reality, gamification, and AI into educational practices. She actively supervises PhD students and leads international research projects such as MIXAP-EU and From AI Anxiety to Empowerment. Education: Not explicitly stated in provided text Her research interests span: Immersive learning technologies (AR/XR, digital escape games) AI in education and generative AI applications Teacher digital competencies and professional development Flipped learning and multimedia pedagogy Ethical challenges in AI research Blended learning practices Recent publications demonstrate a focus on gamification, mixed reality, and AI applications in education, with methodological expertise in structural equation modeling, mixed methods research, and task-based learning analysis. She contributes to journals like Smart Learning Environments and Higher Education Quarterly . Key activities include: Organizing international conferences on STEAM education Leading EU-funded research on immersive learning tools Developing open-source educational technologies Pioneering generative AI integration frameworks

• Cognitive Science
• Quantum Theory in Information Modeling
• Learning Analytics
• +6 more

Kirsty Kitto is an Associate Professor at the University of Technology Sydney in the Learning Design and Technology Unit. With a background in theoretical physics and computer science, her research focuses on developing quantum-inspired models of contextuality to understand complex human behavior in educational systems. She explores the intersection of Artificial Intelligence (AI) , Learning Analytics , and Educational Theory , seeking to bridge the divide between big data and pedagogical frameworks. Current Appointments : Associate Professor (2020-present), Senior Lecturer (2017-2020) Past Academic Roles : Senior Research Fellow (QUT), Senior Lecturer (QUT), Associate Lecturer (Flinders University) Her funded research includes projects on: Quantum models in cognitive systems (ARC Fellowship DP1094974) AI literacy in digital workplaces (IEEE Transactions study) Contextual learning analytics (DVC Education and Students Division) Skills passports for lifelong learning (UMAP 2024 paper) Kitto's recent work examines human-AI interaction in writing assessment, data storytelling for teacher-centered analytics, and causal modeling to strengthen educational theory-data connections. She actively supervises Masters and PhD students and contributes to policy debates through government submissions on generative AI in education. Her methodology combines mathematical formalism with sociotechnical analysis to address educational complexity.