Gias Uddin is an Associate Professor at York University's Lassonde School of Engineering and an Adjunct Professor at the University of Calgary . His research bridges Software Engineering (SE) and Artificial Intelligence (AI) , focusing on AI Trustworthiness Assessment (SE4AI) and AI-Driven Productivity Tools (AI4SE) . PhD in Software Engineering & AI, McGill University (2018) MSc in Software Engineering, Queen’s University (2008) BSc in Computer Science & Engineering, Bangladesh University of Engineering and Technology (2004) His research explores: Metamorphic Relations for LLM Hallucination Detection AI-Enhanced Software Documentation Foundational Models for Runtime System Modernization Developer-Centric AI Tooling Recent article trends show expertise in LLM Trustworthiness , Low-Code Platforms , and IoT Developer Communities . Awards include Distinguished Paper at FSE 2025 , multiple IBM Champion recognitions, and York Research Award . He leads the Data Intensive Software Analytics (DISA) Lab and mentors PhD students in SE-AI Intersections .
Yingfei Xiong is an active Associate Professor at Peking University, China, specializing in software engineering and programming languages. With a consistent research trajectory from 2013 through 2026, Xiong has established themselves as a prominent figure in the software engineering research community, regularly contributing to top-tier conferences including SPLASH, ICSE, ASE, and PLDI. Dr. Xiong's research primarily focuses on program synthesis, automated program repair, and software analysis techniques. Their work bridges theoretical programming language concepts with practical software engineering applications, particularly in developing novel approaches for code generation, bug fixing, and program optimization. The research demonstrates strong interdisciplinary connections between traditional software engineering, programming languages theory, and emerging AI techniques. Analysis of Xiong's publication trends reveals a clear evolution in research focus, beginning with foundational work in API transformations and program adaptation around 2013-2016, shifting toward program repair techniques from 2017-2020, and most recently incorporating machine learning and neural approaches into program synthesis and repair (2021-2026). The work consistently addresses practical challenges in software development while maintaining theoretical rigor, with increasing integration of AI techniques in recent years. Dr. Xiong has served in various leadership roles across the software engineering conference ecosystem, including program committee membership and session chair positions at major conferences. Their extensive service demonstrates recognition by peers as a subject matter expert in software engineering and programming languages research. While specific grant information isn't detailed in the provided text, the sustained publication record suggests successful research funding.
Martin Rajman is a Senior Scientist at École Polytechnique Fédérale de Lausanne (EPFL) with multiple affiliations across the institution. He holds positions in the School of Computer and Communication Sciences (SIN - Teaching, SCI IC MR Group, SSC - Teaching) as well as in the Vice Presidency for Strategic Development (VPS Artificial Intelligence) and the Vice Presidency for Academic Affairs (SNAI Administration). He serves as the Executive Director of Nano-tera.ch, a large Swiss Research Program funding collaborative multi-disciplinary projects in Health and the Environment. Rajman's research spans the intersection of artificial intelligence, natural language processing, and information retrieval. His work demonstrates a consistent focus on developing practical applications of computational linguistics and machine learning techniques. Early in his career, he contributed significantly to syntactic parsing, stochastic language models, and vector space representations for text. More recently, his research has expanded into deep learning applications for 3D reconstruction, empathetic conversational agents, and distributed analytics systems. His publications reveal a trajectory from foundational NLP research toward increasingly applied and interdisciplinary work connecting AI with healthcare, environmental monitoring, and human-computer interaction. Analysis of his recent publications (2015-2024) shows a clear evolution toward more applied AI research with strong interdisciplinary connections. While maintaining his core expertise in natural language processing and information retrieval, his work has expanded into computer vision, healthcare applications, and sustainable computing. The publications demonstrate increasing collaboration across disciplines, with applications in medical imaging, mental health support systems, environmental monitoring, and human-centered AI. His leadership role in the Nano-tera.ch program reflects this interdisciplinary approach, connecting computing research with real-world challenges in health and environmental contexts. Rajman has mentored several PhD students including Ailomaa Marita, Eckard Emmanuel, Melichar Miroslav, and Veselý Martin. His research has been supported through the Nano-tera.ch program, which has funded more than 100 research projects with over 95 million CHF in public funding. He has also managed more than 20 European projects during his tenure as Director of the EPFL Global Computing Center. As Executive Director of Nano-tera.ch, Rajman leads a significant research initiative connecting EPFL with national and international partners. His work bridges academic research with industry applications, notably through collaborations with eBay on product ranking technology and with Elsevier on article recommendation systems. His leadership extends to managing large-scale research programs while maintaining an active research agenda and mentoring the next generation of computer scientists.
Christian Wolff is a University Professor and Chair of Media Informatics at the Institute for Information and Media, Language and Culture at the University of Regensburg. Since April 2022, he has served as the founding Dean of the Faculty of Computer Science and Data Science, while maintaining secondary membership in the Faculty of Languages, Literature and Cultural Studies (SLK). His academic career spans over three decades with significant contributions to multiple disciplines at the intersection of computer science and humanities. Wolff's research interests center around multimedia and multimodal information systems, electronic publishing, and text technology, particularly text mining. His work bridges computer science with digital humanities, legal informatics, and social media analysis. Recent publications demonstrate a strong focus on large language models, sentiment analysis applications across various domains, legal technology innovations, and virtual reality research for cognitive studies. His interdisciplinary approach has produced significant contributions in both technical and humanities domains. His recent publication trends reveal a strategic shift toward applied AI research, particularly in legal technology (LegalTech), social media analysis, and sentiment analysis using large language models. The publications show increasing collaboration across disciplines, connecting computer science with law, political science, literature, and psychology. His work on the digital basis document for legal proceedings represents a major practical application of his research in the German justice system. East Bavarian Cultural Prize Doctoral Award of the University of Regensburg Wolff has led numerous interdisciplinary research projects connecting computer science with humanities and legal studies. His leadership extends to institutional roles including Dean of Research, Vice Dean, and Dean of Faculty positions. He has been instrumental in establishing the new Faculty of Computer Science and Data Science at the University of Regensburg, demonstrating significant impact on institutional development and research infrastructure. Wolff directs research initiatives focused on text technology, digital humanities, and legal informatics. His work with the INDIGO - Internet and Digitization Eastern Bavaria initiative and the TRIO project demonstrates commitment to regional technology transfer and innovation. The interdisciplinary nature of his research groups connects computer scientists with legal scholars, linguists, and social scientists to address complex digital transformation challenges.
Dr. Chenhao Ma is an Assistant Professor at the School of Data Science , The Chinese University of Hong Kong, Shenzhen , where he works on large-scale data management and data mining. Previously, he was a Postdoctoral Fellow at the University of Hong Kong (2021–2022) and earned his PhD in Computer Science from the University of Hong Kong (2021) and B.Eng. from Shandong University (2017). Current research focuses on graph computing (dense subgraph discovery, motif analysis, graph learning), AI+DB (Text-to-SQL, vector search), and traffic data mining (trajectory analysis, outlier detection). He has published over 40 papers in top venues including SIGMOD, PVLDB, KDD and received the ACM SIGMOD Research Highlight Award 2021 and Best of SIGMOD 2020 (4/458). Scientific Awards : ACM SIGMOD Research Highlight Award 2021 Best of SIGMOD 2020 (4/458) Presidential Young Fellow at CUHK-Shenzhen (2023) Hong Kong and China Gas Scholarship (2019-2020) Reaching Out Award (2019) HKU Postgraduate Scholarship (2017-2021) ACM-ICPC Gold Medal (2015) National Scholarship (2014, 2015) Advising and Research Team : He leads a team including Postdoc Dr. Yuanyuan Zeng, PhD students Lujie Ban, Yuwei Xu, and MPhil students Yi Yang, Yuyang Liang. Former mentees like Yichen Xu (PhD at Berkeley) and Jiayang Pang (Master at UC San Diego) have achieved academic placements. Professional Service : He has served as PC member/reviewer for VLDB, KDD, ICDE, WWW, NeurIPS, TKDE , and guest editor for Applied Sciences and Frontiers in Big Data . He chairs sessions at ICDE and VLDB.
Cen “April” Yue is an Assistant Professor of Mass Communication, Advertising, and Public Relations at Boston University’s College of Communication. Her research focuses on internal public relations, leadership communication, organizational change, and corporate social responsibility/irresponsibility. She holds a Ph.D. in Communication from the University of Florida, an MA from Purdue University, and a BA in English from Shandong Normal University. Yue’s work has been published in top journals like Communication Research and Public Relations Review. She is co-authoring a book, *Strategic CEO Communication* (Routledge, 2025), and has received over 10 top research awards. She serves as Chief Research Editor at the Institute for Public Relations’ Organizational Communication Research Center and holds advisory roles at the Internal Communication Research Hub (University of Florida) and the Global Strategic Communication Consortium. She also contributes to editorial boards of Public Relations Review and Communication Reports. Her research explores AI’s role in communication, ethical responses to corporate misconduct, and leadership’s impact on employee engagement. Notable projects include a computational review of 2,675 public relations articles (2012–2022) and studies on supervisory communication and employee well-being. Yue previously taught at the University of Connecticut and has designed courses in public relations principles, campaigns, and research methods. She actively engages in professional organizations and advocates for inclusive, ethical communication practices in organizations.
Jan Cudzik is an Assistant professor at the Gdańsk University of Technology's Department of Urban Architecture and Waterscapes, Faculty of Architecture. He leads the Digital Technology Laboratory and focuses on integrating computational methods with architectural design and conservation. His research spans parametric design, generative systems, artificial intelligence, and sustainable construction practices. Education details are not explicitly provided in the texts, but his academic roles indicate advanced training in architecture and engineering. Research interests include: AI-driven design processes Generative design using swarm intelligence 3D printing in construction Energy-efficient building lifecycle assessment Traditional-conservation/digital-fabrication hybrids Key publication trends emphasize: Public space sustainability (lighting, greenery) Machine learning applications in architecture Historical structure preservation He contributes to projects like ENACT 15mC, focusing on urban community development. His work bridges digital innovation with ecological and cultural heritage concerns. Labs/Teams: Director of the Digital Technology Laboratory, active in architectural education reform using AI tools.
Angelica Lim is an Assistant Professor of Professional Practice and Rajan Family Scholar in the School of Computing Science at Simon Fraser University. Her research focuses on Human Robot Interaction, Affective Computing, and Multimodal Perception with applications in healthcare and developmental robotics. She holds a PhD in Informatics from Kyoto University (2014), an M.Sc. from Kyoto University (2012), and a B.Sc. in Computing Science from SFU (2008). Her work bridges robotics and human-centered AI through projects like the ROSIE Lab, exploring emotion-aware systems, socially assistive robots, and VR programs for aging populations. Key contributions include benchmarking emotional speech recognition (BERSting), developing embodied emotion models for robots, and co-designing healthcare technologies with patient partners. Recent publications emphasize ethical AI, multimodal perception systems, and human-robot collaboration in dynamic environments. Teaching includes courses on software engineering, artificial intelligence, and introductory computer science. Her research has been applied in dementia care through VR programs, robotic companionship for older adults, and emotion-aware human-robot communication systems. Current initiatives focus on inclusive HRI design and sim2real methodologies for underrepresented data in affective computing.
Dr. João Henriques is a Research Fellow of the Royal Academy of Engineering (RAEng) at the Visual Geometry Group (VGG), University of Oxford. His research focuses on advancing computer vision, deep learning, and robotics, particularly in areas like 3D scene understanding, reinforcement learning, and multi-agent systems. He is renowned for developing the KCF and SiameseFC visual trackers, which won the VOT Challenge and are deployed in consumer hardware. His work spans 3D geometry, self-supervised learning, causal inference, and neuro-symbolic systems. Key contributions include methods for egocentric video analysis, unsupervised reconstruction, and robot navigation. He leads the VGG's research on neural feature fields, hierarchical scene understanding, and real-time 3D perception. Recent publications emphasize 3D-aware segmentation, universal place recognition, and neuro-symbolic world modeling for robotics. His research often bridges theoretical guarantees with practical applications, such as medical imaging and autonomous systems. Dr. Henriques collaborates with industry and academia on AI ethics, friendly AI, and interpretable learning. His lab hosts DPhil students advancing creative AI applications, such as generative models for gameplay design and LLM evaluations in real-world editorial workflows.
Stephan Nüesch is a Professor and Director of the International Institute of Management in Technology at the University of Fribourg, affiliated with the Faculty of Management, Economics and Social Sciences. His research focuses on innovation management, artificial intelligence, sharing economy dynamics, organizational behavior, and technology leadership. He holds a prominent role in bridging academic research with practical business applications, particularly in digital transformation and healthcare systems. His work explores topics such as CEO-TMT shared cognition, human-AI collaboration, and value creation in emerging economic models. He teaches courses in management and technology strategy and actively contributes to interdisciplinary research initiatives. His recent articles address nonlinear relationships in economic systems, toolkit-driven innovation, and the impact of crises on organizational identity. Nüesch is a leading voice in leveraging technology for strategic advantage, with a strong emphasis on empirical analysis and policy implications.
Dr. Tim Oates is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County . His research spans machine learning, artificial intelligence, and brain-machine interfaces, with a focus on weakly supervised methods, human-in-the-loop reinforcement learning, and grounded policy development for robotics. Ph.D., Computer Science, University of Massachusetts, Amherst, 2000 M.S., Computer Science, University of Massachusetts, Amherst, 1997 B.S., Computer Science and Electrical Engineering, 1989 Current research threads include: Developing non-invasive brain injury severity assessment via medical time series Modeling human brain development through computational frameworks Designing algorithms for autonomous robotic learning Recent publications highlight AI security mechanisms (backdoor detection via tensor decomposition, matrix factorization) Medical applications (3D artery reconstruction, skin lesion diagnosis, EEG denoising) Neuro-symbolic integration (holographic representations, language-guided reinforcement learning) Mathematical reasoning (schema-based problem solving, subitizing algorithms) Contact: oates@cs.umbc.edu | Office: 336 Information Technology and Engineering (ITE) Building
Elif Bilgic is an Assistant Professor and Education Scientist at McMaster University's Department of Pediatrics. Her research program focuses on performance assessment across medical specialties, with an emphasis on optimizing clinical and simulation-based evaluations through technological innovation, interdisciplinary collaboration, and competency-based frameworks. McMaster University, Department of Pediatrics (2025-present) McGill University, Department of Surgery (2018-2025) Research Interests span performance assessment in surgical and pediatric education, virtual reality simulations, and artificial intelligence applications in health sciences training. She investigates: Valid assessment tools for laparoscopic suturing and endoscopic procedures Extended reality (XR) adoption in Canadian medical simulation centers Emotional impacts of competency assessment mandates on trainees and faculty Interdisciplinary AI integration in surgical education Educational analytics for skill acquisition tracking Teaching includes modules like The Fundamentals of Skill Acquisition (HSEDUC 704) and Program Evaluation in Health Sciences Education (HSEDUC 710). Her 2025 publications highlight advancements in simulation platforms for pediatric acute care, AI implications in surgical training, and emotional analysis of assessment systems.
Craig Knoblock serves as Keston Executive Director of the Information Sciences Institute (ISI) at the University of Southern California (USC), Vice Dean of the USC Viterbi School of Engineering, and Research Professor of Computer Science and Spatial Sciences. He also directs the Data Science Program and the Center on Knowledge Graphs at USC. His educational background includes a Ph.D. and M.S. in Computer Science from Carnegie Mellon University (1991, 1988) and a B.S. with honors in Computer Science from Syracuse University (1984). Knoblock's research focuses on data semantics , specializing in source modeling, schema and ontology alignment, entity and record linkage, data cleaning, Web data extraction, and knowledge graph construction. His work bridges computer science, geospatial analysis, and artificial intelligence to solve complex data integration challenges. Recent projects emphasize historical map digitization, geospatial knowledge graphs, and smart city applications. His 300+ publications demonstrate consistent contributions to knowledge graphs and geospatial data integration, with a growing emphasis on historical map analysis and urban applications. The research trajectory shows increasing interdisciplinary collaboration across computer vision, geoinformatics, and domain-specific applications. IEEE Fellow (2020) ACM Fellow (2017) AAAI Fellow (2004) Robert S. Engelmore Memorial Lecture Award (2014) Donald E. Walker Distinguished Service Award (IJCAI, 2018) Use-Inspired Research Award (USC Viterbi, 2018) As Executive Director of ISI, Knoblock oversees one of USC's premier research centers with significant federal funding. His leadership extends to directing the Center on Knowledge Graphs and the Data Science Program. While specific grant details aren't provided, his extensive publication record and leadership roles indicate substantial research funding across data integration, knowledge representation, and geospatial applications. His work bridges theoretical computer science with practical applications in historical preservation, urban planning, and resource management through collaborative projects with government agencies and industry partners. Knoblock leads the Center on Knowledge Graphs at USC, focusing on developing techniques for building and utilizing knowledge graphs across diverse domains. His team combines expertise in artificial intelligence, geospatial analysis, and data integration to tackle challenges in historical map digitization, urban applications, and resource discovery. The research group maintains strong connections with both academic and government partners through the Information Sciences Institute's extensive network.
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.
Mert Kiray is a researcher at the Department of Informatics, Technical University of Munich (TUM), affiliated with the Chair of Computer Aided Medical Procedures under Prof. Nassir Navab. He is based at Campus Garching and actively contributes to research in computer vision, medical imaging, and surgical robotics. His research focuses on Computer Vision , Deep Learning , and Medical Image Analysis , with applications in Augmented Reality , Generative Models , and Robotics . Current projects include surgical data science, 3D reconstruction, and vision-language integration. Recent publications highlight his work on Multimodal Human Action Recognition (2025) and Text-to-3D Gaussian Animation (2025), reflecting expertise in combining 3D Computer Vision with Medical Applications .
