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Swapna GottipatiView profile

Associate Professor

• Artificial Intelligence
• Data Science
• Machine Learning
• +7 more

Swapna Gottipati is a Full-time Associate Professor of Information Systems (Education) and Associate Dean (Undergraduate Education) at the School of Computing and Information Systems , Singapore Management University . Holding a PhD from SMU (2014) , she specializes in text analytics, education technology, and digital business. Current focus areas: Artificial Intelligence, Data Science, Technology-Enhanced Learning Interdisciplinary applications: Health Informatics, Social Media Analytics Research Interests span text analytics, opinion mining, curriculum analytics, and digital transformation. She applies machine learning and data mining to educational systems, business processes, and health domains. Scientific Contributions: 2016 Best Paper Award (AIS SIG-ED) 2016 MOE TRF Grant 2017-2020 Conference Best Paper Nominations 2013 Best Paper Finalist (CIKM) Academic Leadership includes: Director of Undergraduate Education Co-developer of SMU-X pedagogy Founder of MyCompetencies mobile platform Organizer of curriculum analytics workshops Grant Projects include the Learning Analytics on Qualitative Student Feedback system (MOE TRF 2016) and ICDL-funded digital literacy studies. She has delivered 12+ invited talks on digital transformation in education and industry.

Giuseppe DesoldaView profile

Associate Professor

• Human-Computer Interaction
• Usable Security
• End-User Development
• +4 more

Giuseppe Desolda is an Associate Professor at the Computer Science Department of the University of Bari Aldo Moro , where he has been since July 2, 2022. He leads research at the Interaction, Visualization, Usability & UX (IVU) Lab , focusing on Novel Interaction Techniques , Internet of Things development, and Usable Security . His work includes coordinating the PRIN PNRR DAMOCLES project (2022-2025) on human-centric cybersecurity and leading Work Package 1 of PNRR SERICS. PhD in Computer Science from University of Bari Co-author of over 110 publications Associate Editor for IEEE Access Journal Research interests span Human-Computer Interaction (HCI), End-User Development (EUD) for IoT, and Usable Security systems. His recent work explores AI-driven usability evaluation, voice-based 3D modeling, and GDPR-compliant software frameworks. Article trends show focus on phishing mitigation , smart environment customization , and privacy-by-design methodologies. Publications appear in TOCHI , FGCS , IJHCS , and BIT . Scientific achievements include: Selected for Heidelberg Laureate Forum (2019) LARE spin-off grant (EUR 50,000, 2013) He supervises PhD students Andrea Esposito and Francesco Greco, and has advised multiple funded research projects (PRIN DAMOCLES, DevProDev, PNRR SERICS). Teaching roles include courses on Human-Centered AI, IoT Security, and Web Programming across undergraduate and graduate programs.

• Software Engineering
• Artificial Intelligence
• Social Computing
• +4 more

Professor Keith Phalp is the interim Pro-Vice Chancellor for Education and Quality at Bournemouth University. With over 30 years in higher education, he has held roles ranging from lecturer to Executive Dean. His research focuses on software engineering, model-driven development, AI applications, and social computing, particularly digital addiction and online gambling. He leads research and knowledge exchange at the university, with over 200 refereed publications. His work addresses challenges in software project phases, business-software model relationships, and ethical tech design. Recent articles highlight his contributions to safer gambling transparency, social media misinformation intervention design, and fairness in cloud computing. He collaborates extensively on interdisciplinary projects, such as combating digital addiction through peer support groups and enhancing educational tools with AI. Professor Phalp’s leadership spans strategic academic roles, balancing administrative duties with advancing research in socially impactful areas like responsible technology and user behavior analysis.

Daniel TauritzView profile

Professor

• Artificial Intelligence for National Security
• Cyber Security
• Critical Infrastructure Protection
• +5 more

Daniel Tauritz is a Professor in the Department of Computer Science and Software Engineering at Auburn University and serves as Director for National Laboratory Relationships. He holds a Ph.D. and M.S. in Computer Science from Leiden University, along with propaedeutic studies in Computer Science and Mathematics. His research focuses on AI-driven cybersecurity, automated algorithm design using hyper-heuristics, computational game theory, and evolutionary computation. Tauritz leads initiatives such as the Auburn Cyber Research Center and collaborates with institutions like Los Alamos National Laboratory on critical infrastructure protection and satellite network security. His work bridges academia and national security through projects like the Cyber Fire Puzzles competition and the Satellite Tycoon economic simulation game. His educational background includes advanced studies at Leiden University, with a strong foundation in computer science and mathematics. Research contributions span evolutionary algorithms for molecular evolution, coevolutionary defense strategies, and generative hyper-heuristics. Tauritz has secured grants including an NSF award for AI-cybersecurity education and contributed to Auburn’s partnerships with national laboratories. He is actively involved in fostering student engagement through ethical hacking clubs and experiential learning programs. Notable achievements include moderating panels on AI in cybersecurity and AI workforce development, as well as developing frameworks like Galaxy for network emulation and DCAFE for automated cyber experiments. His publications emphasize applying evolutionary computation to real-world challenges, including satellite constellation economics and adversarial network defense strategies.

Bin HuView profile

Assistant Professor

• Resilient Cyber-Physical Systems (CPS)
• AI-Human Collaboration Safety & Security
• Big Data & Machine Learning-Based Control
• +5 more

Dr. Bin Hu is an Assistant Professor in the Department of Engineering Technology at the University of Houston (2022–present) and previously held the same position at Old Dominion University (2019–2022). He earned a Ph.D. in Electrical Engineering from the University of Notre Dame (2016), an M.S. in Control Science from Zhejiang University (2010), and a B.S. in Electrical Engineering from Hefei University of Technology (2007). His research focuses on resilient Cyber-Physical Systems (CPS), AI-human collaboration safety, machine learning-driven control, and vehicular networks. Key projects include NASA-funded work on adaptive human-autonomy responsibility allocation (2023–2026) and NSF-supported AI-human collaboration in autonomous vehicles (2020–2023). He has secured over $1.2 million in grants, including a $700k NASA grant (pending) and an ONR Rapid Solutions grant ($42k). Dr. Hu’s work bridges control theory, machine learning, and human factors. Recent contributions include safer leader-follower robotic systems, fault-tolerant UAV control, and studies on driver trust in AI-driven vehicles. His research has been recognized through awards like the 2024–2025 APeX Excellence Speaker Series. Teaching experience includes courses on C++ programming and electrical engineering fundamentals at both the University of Houston and Old Dominion University. He advises multiple undergraduate and graduate students in projects ranging from LiDAR systems to cyber-physical security. Key Labs/Teams : NAIL Lab (Networked Autonomous Intelligence & Learning), part of the University of Houston’s Cybersecurity and Robotics initiatives. Grants : NASA TTT Grant ($700k), NSF CHS Grant ($500k), ONR RSLP Project ($42k).

Carson LeungView profile

Professor

• Big Data Science
• Data Mining
• Machine Learning
• +5 more

Dr. Carson Kai-Sang Leung is a Full Professor in Computer Science at the University of Manitoba's Faculty of Science. He founded and directs the Database & Data Mining Lab. His research focuses on big data science, data mining, machine learning, health informatics, and visual analytics. He holds SMIEEE and SMACM fellowships, reflecting his contributions to the field. Education: B.Sc., M.Sc., and Ph.D. from the University of British Columbia (UBC). Research interests include human-centered exploratory data mining, image databases, and scalable algorithms. He emphasizes user-driven constraints in mining processes and has developed techniques like the segment support map and OSSM for optimized frequency counting. His work on subimage queries in large image databases addresses real-world challenges in visual data retrieval. Publications span data mining, healthcare analytics, and transportation systems. His lab collaborates on projects like visual analytics for motor vehicle accidents and environmental data science for smart cities. He is affiliated with institutions such as the Institute of Industrial Mathematical Sciences (IIMS) and TRLabs. Key awards: Senior Member of IEEE (SMIEEE) and Senior Member of ACM (SMACM).

• Artificial Intelligence
• Geospatial Data Science
• Knowledge Graphs
• +5 more

Professor Manolis Koubarakis is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on geospatial data science, knowledge graphs, entity resolution, and AI applications in Earth observation. He leads projects like ExtremeEarth and Plato, advancing semantic data cube systems and geospatial question answering engines. His work bridges AI and geospatial technologies, with contributions to frameworks like pyJedAI and Strabo 2 for managing big geospatial data. Research Interests include: Geospatial Question Answering Systems Entity Resolution and Entity Linking Ontology-Based Data Access (OBDA) Knowledge Graph Construction and Applications Earth Observation Data Analytics AI for Geoinformatics Notable Projects: ExtremeEarth: Combines Copernicus satellite data with machine learning for environmental analytics. Plato: Semantic data cube system enabling advanced querying of multidimensional datasets. GeoQA2: A geospatial question answering engine evaluated on large benchmarks. JedAI Family: Tools for scalable entity resolution in structured/semi-structured data. His publications span 20+ years, with recent emphasis on: AI-driven Earth observation systems Geospatial RDF benchmarking 3D geospatial interlinking Large language models for legal and health content delivery

Bill ChuView profile

Professor

• Cybersecurity
• Cyber Threat Intelligence
• AI in Cybersecurity
• +2 more

Bill Chu is a Professor and Managing Director of CyberDNA at the University of North Carolina at Charlotte's College of Computing and Informatics. His research focuses on cybersecurity automation, cyber threat intelligence, application security, and AI-driven cybersecurity solutions. He has contributed to numerous publications on threat detection, vulnerability analysis, and secure software development practices. Chu's work emphasizes practical applications of cybersecurity, including static analysis tools, interactive code annotation for vulnerability detection, and educational tools for secure programming. His research spans collaborations with institutions and industry to bridge gaps in cybersecurity education and practice. Notable contributions include developing frameworks for extracting actionable threat intelligence from social media, automated unit testing for XSS vulnerabilities, and leveraging large language models for vulnerability detection. Chu actively participates in workshops and conferences on cybersecurity and software engineering, contributing to advancements in both theory and application.

Djamel E. KhelladiView profile

Researcher

• Software Engineering
• Model-Driven Engineering
• Software Evolution
• +6 more

Djamel E. Khelladi is a CNRS researcher affiliated with the IRISA research lab and the DIVERSE team at University of Rennes 1 , France. Previously, he held postdoctoral and PhD positions at Johannes Kepler University (JKU) Linz, Austria, and Université Pierre et Marie Curie (UPMC), France. Research interests include: Model-Driven Engineering Software Evolution & Co-evolution AI and Generative AI Applications Polyglot Programming Digital Twins Recent article trends focus on integrating Large Language Models (LLMs) for code-metamodel co-evolution, polyglot programming challenges, incremental build optimization in configurable systems, and empirical studies on software evolution. His work often bridges theoretical modeling with practical implementation in industrial contexts. Academic service roles include: Proceedings Co-Chair @MODELS 2025 Co-Organizer of Models and Evolution (ME) workshops (2023-2025) Co-Editor for special issue on Model Driven Engineering for Digital Twins (SoSym 2024/25) PC member in top venues: ICSE , ASE , MODELS , ECMFA , MSR , FSE

Christopher CollinsView profile

Professor

• Information Visualization
• Human-Computer Interaction
• Pen+Touch Interface Design
• +7 more

Dr. Christopher Collins is a Professor of Computer Science at Ontario Tech University, leading the Visualization for Information Analysis Lab (vialab). He holds a PhD from the University of Toronto (2010) and focuses on interdisciplinary research in information visualization, human-computer interaction, and natural language processing. His work addresses challenges in information overload, text analytics, and novel interfaces such as touch, pen, VR/AR. Collins' research has been featured in top-tier venues like ACM CHI and IEEE Transactions on Visualization and Computer Graphics, earning honorable mentions and over $3M in funding as sole PI. He serves on the IEEE VIS Executive Committee and Board of Governors at Ontario Tech University. Education: PhD in Computer Science, University of Toronto (2010) MSc in Computer Science, University of Toronto (2004) BSc (Hons) in Computer Science, Memorial University (2001) Research Interests: Collins' work spans information visualization , pen+touch interfaces , visual analytics , and text-driven systems . He explores how interactive technologies can democratize complex data analysis, particularly in education, healthcare, and creative domains. Recent projects include gaze-driven learning tools, context-aware camera interfaces, and bias-mitigating product review analysis. Awards: ACM CHI Honorable Mention Award IEEE VIS Honorable Mention Award Grants & Impact: Secured $3M+ in research funding. Media coverage includes New York Times and CBS Sunday Morning for innovations in visualization and text analytics. Teaches courses in human-computer interaction, computer graphics, and information visualization. Labs & Collaborations: vialab develops tools like Lexichrome , ConToVi , and NeuroSight . Active in IEEE Visualization and ACM Interactive Media communities. Collaborates with academia and industry globally.

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +5 more

Dr. Masoud Makrehchi is an Associate Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, part of the Faculty of Engineering and Applied Science. His research focuses on Natural Language Processing, Artificial Intelligence, Machine Learning, and Social Computing, with a strong emphasis on applications in network science and moral AI. He holds a PhD from the University of Waterloo (2007), along with earlier degrees from Shiraz University and Iran University of Science and Technology. Prior to academia, he worked as a Senior Research Scientist at Thomson Reuters (2008–2012) and completed a postdoctoral fellowship at the University of Waterloo (2007–2008). His research expertise includes text mining, social network analysis, and network science, addressing challenges such as signed social network analysis, document classification, and crime trend prediction using social media data. He has received several awards, including the NSERC Postgraduate Scholarship and the SBP Challenge Award (2012). His work spans over 50 peer-reviewed publications in journals like Expert Systems with Applications, Social Network Analysis and Mining, and Web Intelligence, with contributions to conferences such as GECCO and IEEE/ACM. Dr. Makrehchi’s publications highlight innovations in feature selection, text segmentation, and AI-driven frameworks for requirements elicitation. His recent work explores coherence graphs for text segmentation, generative AI in education, and bias detection in medical datasets. He has also contributed to patent applications related to sentiment analysis and text extraction systems.

• Human-Computer Interaction (HCI)
• Learning Sciences
• Artificial Intelligence
• +5 more

Hariharan Subramonyam is an Assistant Professor (Research) at Stanford University's Graduate School of Education and Computer Science (by courtesy) . He is also a Faculty Fellow at the Institute for Human-Centered AI (HAI) and a core member of the Stanford HCI Group . His research focuses on augmenting human learning, creativity, and sensemaking with AI, informed by cognitive psychology and collaborative design practices. Research Interests: Human-Computer Interaction (HCI) Learning Sciences Generative AI Educational Technology Assistive Technology Cognitive Psychology Recent Trends: Designing AI tools for education and creative coding Co-developing AI experiences with multidisciplinary teams Ethical and responsible AI frameworks Accessible interfaces for visually impaired users Scientific Awards: Best Paper Award, CHI 2025 Best Paper Honorable Mention, CHI 2025 Best Paper Award, ASSETS 2024 Best Paper Award, UIST 2023 Best Paper Award, IUI 2021 Best Paper Award, CHI 2020 Advising & Grants: Co-advising PhD student Neha Rajagopalan Mentoring 23+ student researchers Principal Investigator on HAI Hoffman Yee Grant (2024) Labs & Teams: Stanford Human-Computer Interaction Group Stanford Institute for Human-Centered AI Collaborative projects with University of Michigan, Georgia Tech, and National University of Singapore

• Electronic Design Automation (EDA)
• Computer Architecture
• Embedded Systems
• +5 more

Prof. Wolfgang Ecker is a Professor at the Technical University of Munich (TUM), affiliated with the Chair of Design Automation within the TUM School of Computation, Information and Technology . His research focuses on Electronic Design Automation (EDA), RISC-V processor architectures, and hardware-software co-design. He leads projects advancing EDA tools for embedded systems, neural network acceleration, and formal verification methodologies. Ecker's work bridges machine learning techniques with traditional EDA challenges, addressing topics like energy-efficient AI inference and automated documentation generation. His contributions span compiler optimization, FPGA implementations, and fault analysis in digital systems. Recent research highlights include contributions to the TRISTAN project for RISC-V ecosystem development, model-driven architecture frameworks, and AI-driven timing analysis. He actively collaborates on open-source EDA tools and explores Rust-based embedded systems development. Ecker’s lab emphasizes practical applications in edge computing and automotive microcontroller safety, with a strong emphasis on interdisciplinary collaboration across TUM’s CIT School. His publications (15 most recent listed) reflect a focus on EDA tool innovation, processor design, and leveraging machine learning for hardware optimization. While no specific awards are mentioned, his involvement in ERC-funded projects and leadership in international collaborations underscores his academic impact.

Jonathan SprinkleView profile

Professor

• Cyber-Physical Systems
• Autonomous Systems
• Traffic Control
• +3 more

Jonathan Sprinkle is Chair and Professor of Computer Science at Vanderbilt University's School of Engineering, with additional roles as Professor in Civil and Environmental Engineering and Electrical and Computer Engineering. Previously, he was Litton Industries John M. Leonis Distinguished Associate Professor at the University of Arizona and Interim Director of the Transportation Research Institute. His research focuses on model-based cyber-physical systems, autonomous systems, and traffic control, emphasizing industry impact. He holds a Ph.D., M.S., and B.S. in Electrical Engineering from Vanderbilt University and Tennessee Technological University. Key awards include the NSF CAREER Award (2013), UA Distinguished Scholar (2020), and NSF I-Corps Best Team (2012). His work spans traffic wave dissipation, autonomous vehicle safety, and large-scale field experiments like the CIRCLES consortium's 100-AV test. He leads initiatives in data-driven control systems and smart infrastructure through collaborations with NSF and industry. Research highlights include developing control barrier functions for automated vehicles, integrating LLMs for traffic analysis, and deploying ROS-based frameworks for vehicle communication. His contributions aim to bridge theoretical models with real-world applications, addressing challenges in energy efficiency, safety, and scalability.

• Educational Technology
• Programming Tutoring Systems
• Game-Based Learning
• +1 more

Johan Jeuring is Professor of Software Technology for Learning and Teaching at Utrecht University's Department of Information and Computing Sciences. His research focuses on intelligent tutoring systems, computational thinking education, and game-based learning environments. Research Interests: Prof. Jeuring's work explores computational thinking pedagogy, automated feedback systems, and educational game design. His research bridges artificial intelligence with educational psychology to develop effective learning tools. Publications: Recent publications focus on augmented reality learning environments, programming education methodologies, automated assessment systems, and AI applications in education. His work combines empirical studies of learning behaviors with technological innovations in educational tools.