Chua Tat Seng is a Professor at the School of Computing, National University of Singapore (NUS), holding the KITHCT Chair Professorship since 2009. He serves as co-Director of the NExT++ Center, a joint research center between NUS and Tsinghua University focused on Extreme Search. His academic career spans over three decades at NUS, where he has held various leadership positions including Acting Dean of the School of Computing (1998-2000) and Acting Head of the Department of Information Systems & Computer Science (1996-1998). Professor Chua's research spans unstructured data analytics , multimedia information retrieval , recommendation and conversation systems , and emerging applications in e-commerce and fintech . He established the Lab for Media Search (LMS) at the School of Computing and has been instrumental in advancing multimodal learning and search technologies. His work bridges theoretical foundations with practical applications, particularly in developing trustable AI systems for real-world deployment. His recent publications demonstrate a strong focus on large language models for recommendation systems , multimodal learning , and generative AI applications . The research trends show increasing emphasis on LLM-based recommendation, multimodal understanding, and addressing fundamental challenges in AI reliability, fairness, and efficiency. His work spans theoretical advancements in representation learning to practical applications in e-commerce, finance, and healthcare domains. ACM SIGMM Technical Achievement Award 2015 Multiple Best Paper Awards across ACM Multimedia, IEEE Transactions, and MMM conferences (2007-2020) Professor Chua has supervised 37 PhD students since 2004, establishing himself as a dedicated mentor in the academic community. His research has been supported by substantial grants including NExT++ ($12 million), Base Metals Price Forecasting ($200,000), and Multilingual Multimodal Knowledge Graph ($500,000). He maintains active collaborations with Tsinghua University, University of Southampton, and industry partners like Four Elements Capital and Singapore Press Holdings. As co-Director of the NExT++ Center, he leads a major research initiative focused on Web Intelligence and User Empowerment. His visiting professorships at Tsinghua University (2017-present) and Zhejiang University (2021-present) reflect his international impact in the field of multimedia and AI research.
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Andrew Colesمشاهده پروفایل
دانشگاهی
Dr Andrew Coles is a Reader in Artificial Intelligence at the Department of Informatics, King's College London, within the Faculty of Natural, Mathematical & Engineering Sciences. His research focuses on temporal and numeric planning, explainable planning, and human-robot collaboration. He leads and co-investigates multiple research projects funded by EPSRC, the Royal Academy of Engineering, and the European Commission. His research interests include Artificial Intelligence, Temporal and Numeric Planning, Planning with Rich Domain Models, Explainable Planning, Human-Robot Interaction, Autonomous Systems, Heuristic Search, and Decision-Making. He has published extensively in top-tier AI and robotics conferences such as ICAPS, IROS, HRI, AAAI, and IJCAI. His recent publications demonstrate a strong trend toward explainable AI in human-robot collaboration, with a focus on multimodal sensing (e.g., eye tracking), user needs for explanation, and adaptive planning. His work integrates planning algorithms with human-centered evaluation and real-world applications in robotics. Scientific Awards: International award for PhD thesis on assistive robots (2020) Advising and Grants: Dr Coles has supervised multiple students, including Lara Wachowiak, Guillem Canal, and Petra Tisnikar. He has led or co-investigated several major research projects, including: COHERENT (EPSRC): Collaborative Hierarchical Robotic Explanations Plan and Goal Reasoning for Explainable Autonomous Robots (Royal Academy of Engineering) ADE (European Commission): Autonomous Decision Making in Very Long Traverses ERGO (European Commission): European Robotic Goal-Oriented autonomous controller Labs and Teams: He is affiliated with the Reasoning and Planning research group and the Trusted Autonomous Systems Hub at King's College London, focusing on developing trustable autonomous systems through robust planning and human-centered AI.
Professor Xiaodong Liu is a faculty member at Edinburgh Napier University, affiliated with the School of Computing, Engineering and the Built Environment . His research spans Internet of Things , Edge Computing , Artificial Intelligence , and Cybersecurity , with a focus on decentralized systems and data-driven decision-making. Research Themes : IoT orchestration, federated learning, smart city infrastructure, building maintenance optimization, and automotive cybersecurity. Current Projects : Leading Swarmchestrate (EU-funded), Long-range Perceptive Autonomous Vehicles (Royal Society), and Met-Bot for Disaster Surveillance (Royal Society). His recent publications emphasize privacy-preserving edge learning , semantic IoT data validation , and deep learning for weather prediction . As a supervisor, he has guided PhD students in areas like federated learning, smart building systems, and IoT security. Collaborations include partnerships with institutions in Scotland, China, and Italy, alongside funding from European Commission , Royal Society , and Scottish Funding Council . He contributes to international conferences and journals, with notable work in IEEE Transactions , ACM TAAS , and MDPI publications.
Gaang Leeمشاهده پروفایل
استادیار
Gaang Lee is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Alberta's Faculty of Engineering, where he joined in 2022 after earning his Ph.D. from the University of Michigan. His research pioneers 'sympathetic' built environments that enhance safety, health, productivity, and comfort for workers and users through integration of wearable biosensors, AI, extended reality, and robotics with psychophysiological theories. Education: Ph.D in Civil and Environmental Engineering, University of Michigan, Ann Arbor (2022) - Emphasis: Construction Engineering and Management; Graduate Certificate in Computational Discovery and Engineering Graduate Certificate in Computational Discovery and Engineering, University of Michigan, Ann Arbor (2022) M.S. in Architectural Engineering, Yonsei University, South Korea (2012) - Emphasis: Construction Engineering and Management B.S. in Architectural Engineering, Yonsei University, South Korea (2010) Dr. Lee combats technological exclusion for marginalized groups (construction workers, older adults) by developing empathetic technologies for workplaces, buildings, and urban spaces. His work applies human sensing, AI, and digital twins to create environments that adapt to diverse human needs, with key projects spanning psychophysiological safety monitoring, human-robot collaboration, and inclusive urban design. He integrates psychophysiological and socio-cognitive theories to address real-world gaps in construction engineering and computer science. His recent publications (2023-2025) reveal strong trends in AI-driven safety hazard identification, biosensor-based stress/fatigue monitoring, and virtual reality for construction team dynamics. A critical emerging focus is equity-centered technology design, with increasing publications addressing inclusive built environments and technological access for vulnerable populations through graph-based algorithms, domain adaptation, and interpretable AI models. Scientific Awards: No awards mentioned in the provided text. Dr. Lee actively recruits students for his 'Empathetics' research group starting in 2026, prioritizing candidates with empathy, research motivation, and commitment to diversity and inclusion. While specific grants are not detailed, his research program receives institutional support from the University of Alberta and likely external funding given its interdisciplinary scope and industry relevance. He leads the 'Empathetics' research group (part of Attentive Hub) which emphasizes diversity as fundamental to innovation. Current projects include psychophysiological monitoring for occupational safety, trustable human-robot collaboration systems, and extended reality frameworks for empathetic built environments. The group collaborates with IHT LAB (https://www.iht-lab.com/) and focuses on deploying technologies that make daily surroundings safe, healthy, and truly inclusive for all individuals.
David Ebert is a Gallogly Chair Professor of Electrical and Computer Engineering at the University of Oklahoma (OU), where he serves as Director of the Data Institute for Societal Challenges. He is also an Adjunct Professor at Purdue University and leads the Department of Homeland Security’s Visual Analytics Center of Excellence (VACCINE). Education: Ph.D., M.S., B.S. in Computer Science from The Ohio State University Research Interests : His work spans visual analytics , human-computer teaming , trustable AI , and data science with applications in energy/climate resiliency, defense/security, health, and digital humanities. Recent projects include predictive visual analytics for public safety and social media spambot detection. Scientific Awards : IEEE Fellow IEEE Computer Society vgTC Technical Achievement Award National Science Foundation's InTRO grant University Faculty Scholar DHS S&T Award of Excellence Leadership Roles : Associate Vice President of Research and Partnerships at OU, with directorships in multiple research centers focused on visual analytics and information assurance.
Sergio Segura is a Full Professor of Software Engineering at the University of Seville (Spain), where he leads the research line on Software Engineering within the SCORE Unit of Excellence. He is a member of the Applied Software Engineering research group and affiliated with the SCORE Lab at the I3US Institute. His research focuses on applied and tool-oriented software engineering, with particular emphasis on improving software quality and developers' productivity through automation. He actively collaborates with industry through research contracts and technical training initiatives. Segura's research interests include software testing, AI-driven software engineering, trustworthy AI, and software engineering education. His recent work shows a strong trend toward testing RESTful APIs, safety and fairness testing of large language models, and mutation testing in practice. His publications demonstrate a consistent focus on practical, tool-oriented solutions to real-world software engineering challenges. Docentia Teaching Accreditation - Excellence Mention (2025) Best Application Paper Award at AITest 2022 His student Alberto Martín won the SCIE/BBVA National Young Researcher Award 2023 Segura has supervised numerous PhD students, many of whom have achieved significant recognition including First and Second Place Winners in ACM SRC Grand Finals. He leads the TRUST4AI project focused on trustable AI-driven internet search and maintains close collaboration with industry partners such as Schneider Electric through industrial PhD programs.
Dr. Aitor Arrieta is a permanent full-time Lecturer and Researcher at Mondragon University in Spain. His research focuses on software engineering and testing methodologies for complex systems including Cyber-Physical Systems, AI-based systems, and Generative AI models. He maintains strong industry collaborations with companies like Orona and Developair to address real-world engineering challenges. Research interests span: AI system validation and safety testing Metamorphic testing techniques Autonomous vehicle verification Large Language Model bias/fairness analysis Search-based software engineering His recent publications demonstrate a focus on developing automated testing tools for AI systems, particularly in safety-critical domains. Awarded Best Paper at the 15th International Symposium on Search-Based Software Engineering. Active in European research projects: InnoGuard: Generative AI for autonomous cyber-physical systems TRUST4AI: Trustable AI-driven internet search
Amanda Colesمشاهده پروفایل
مدرس ارشد
Dr. Amanda Coles is a Senior Lecturer in Computer Science at the Department of Informatics , King's College London , within the Faculty of Natural, Mathematical & Engineering Sciences . She is a leading researcher in Artificial Intelligence Planning , focusing on temporal, continuous, and preference-based planning, with applications in robotics, space, healthcare, and autonomous systems. University: King's College London School: Faculty of Natural, Mathematical & Engineering Sciences Department: Department of Informatics Academic Rank: Senior Lecturer Email: amanda.coles@kcl.ac.uk ORCID: https://orcid.org/0000-0002-1838-8301 Her research centers on advanced AI planning techniques, including planning under uncertainty, numeric and temporal reasoning, and explainability in planning systems. She investigates how AI can support decision-making in complex domains such as space robotics (e.g., ERGO, ADE projects), multimorbid patient management, and power systems. Her work often integrates constraint programming, heuristic search, and optimization to improve planner efficiency and expressiveness. Her recent publications (2019–2024) reflect a strong focus on explainable AI in planning, with user studies informing the design of interpretable planning systems. She also continues to advance core planning technologies, such as handling nonlinear change, disjunctive scheduling, and metastate abstractions. Her work bridges theoretical AI with practical deployment in real-world autonomous systems. EPSRC Post-Doctoral Research Fellowship (2010–2013) Invited speaker at IJCAI Early Career Spotlight (2016) Dr. Coles has led multiple externally funded research projects, including from EPSRC and the European Commission (e.g., ERGO, ADE, POLARIS), focusing on scalable planning, continuous change, and autonomy in robotics. She has edited major conference proceedings (e.g., ICAPS 2016) and co-developed influential planning systems like COLIN and PDDL+. She actively supervises research students and collaborates across disciplines, contributing to the development of trustable autonomous systems at King's College London. She is a key member of the Planning, Reasoning and Planning research group and the Trusted Autonomous Systems Hub , where her work supports the development of reliable, explainable, and efficient autonomous decision-making systems for future applications.
- Artificial Intelligence
- AI Planning
- Automated Planning
- +۱۴ مورد دیگر
Robert G. Reynolds is a Professor of Computer Science at Wayne State University's College of Engineering, where he leads pioneering research in Cultural Algorithms and evolutionary computation. With over 197 publications spanning from 1982 to 2024, he has established himself as a leading authority in computational intelligence and socially-inspired optimization techniques. His work bridges computer science, social modeling, and practical applications across diverse domains including education, healthcare, and archaeology. Reynolds' research interests center around Cultural Algorithms, which he developed as a framework for modeling how cultures solve problems through social learning and knowledge transmission. His work extends to evolutionary computation, swarm intelligence, and agent-based modeling, with applications ranging from virtual reality educational systems to medical imaging analysis. He has published the influential book 'Culture on the Edge of Chaos - Cultural Algorithms and the Foundations of Social Intelligence' (2018) that formalized his theoretical contributions. His recent publications (2022-2024) demonstrate continued innovation in applying Cultural Algorithms to diverse challenges including STEM education through virtual reality environments, medical image analysis, economic modeling, and climate change impact assessment. These works consistently show his approach of integrating social dynamics into computational problem-solving frameworks. Among his notable scientific contributions is the development of the Cultural Algorithms framework as a comprehensive approach to optimization and problem-solving that incorporates social dimensions often missing in traditional evolutionary algorithms. His work has influenced numerous researchers in the field of computational intelligence. Professor Reynolds has mentored numerous students who have become frequent collaborators, including Mostafa Z. Ali, Thomas Palazzolo, Sarah Saad, and Chencheng Zhang. His research has been supported by various grants that have enabled the development of projects like the Deep Dive Virtual Reality system for exploring ancient submerged civilizations and educational applications of AI. His laboratory work focuses on developing the Cultural Algorithms Toolkit (CAT) and applying it to real-world problems through virtual environments that simulate social and cultural dynamics. Current projects include extending Cultural Algorithms for trustable AI systems and developing more sophisticated models of cultural knowledge transmission.
Ehsan Toreini is a Lecturer in Software Security at the University of Surrey's Surrey Centre for Cyber Security (SCCS), and a visiting academic in the Department of Computer Science at Durham University. He holds a PhD from Newcastle University, specializing in secure systems and protocols. His research focuses on physical security, trustworthy machine learning, web security, and privacy-preserving technologies, with over 35 peer-reviewed publications and two US patents. Dr. Toreini's work has led to impactful contributions, including mitigations deployed in major browsers (Mozilla Firefox, Apple iOS), standardization at W3C, and recognition such as the Kaspersky Lab Cyber Security Award (2016). He has secured grants like the EPSRC-funded AGENCY project and PETRAS-funded Cyfer initiative. His research team includes current and past PhD students like James Clarke and Patrick Wake, with notable alumni now in industry roles. Key research areas include sensor-based privacy leakages, anti-counterfeiting via digital fingerprinting, and secure e-voting systems. His work bridges theoretical advancements with real-world applications, emphasizing industrial impact and ethical considerations in AI and FinTech. Grants: EPSRC AGENCY (2022-Now), PETRAS Cyfer (2021-2023), StandICT Grant (2019) Awards: Kaspersky Lab Winner (2016), Blavatnik Nominee (2022) Impact: CVE fixes, W3C standards updates, patents (#US10680825, #US10841098)
David S. Ebert is a Gallogly Chair Professor of Computer Science and Electrical and Computer Engineering at the University of Oklahoma, serving as Director of the Data Institute for Societal Challenges and Associate Vice President for Research and Partnerships. He holds adjunct professorships at Purdue University and leads the Department of Homeland Security's Visual Analytics Center (VACCINE). Ebert's research focuses on visual analytics, human-AI collaboration, and trustable AI systems with applications in climate resilience, public health, and security. He earned a Ph.D., M.S., and B.S. in Computer Science from The Ohio State University. His work has led to patents in public safety systems and predictive analytics, alongside impactful tools like SMART 2.0 for social media misinformation tracking and MetricsVis for law enforcement performance evaluation. Ebert has received prestigious awards including the IEEE Visualization Technical Achievement Award and multiple Department of Homeland Security recognitions. His contributions span interdisciplinary projects addressing societal challenges such as pandemic preparedness, methane emission monitoring, and sustainable agriculture through data-driven decision systems. Key leadership roles include directing the DHS Visual Analytics Center, the Purdue Visual Analytics Center, and the Center for Education and Research in Information Assurance and Security. His research emphasizes bridging technical innovations with real-world applications in emergency response, healthcare, and environmental sustainability.
Karthik Krishnanمشاهده پروفایل
استادیار مدعو
Karthik Krishnan is an Adjunct Assistant Professor at the Leonard N. Stern School of Business, New York University, where he has been teaching since 2012. He specializes in the business of publishing and media industry transformation, focusing on disruptive forces such as digitization and consumer-generated content. As Global CEO of Britannica Group, he leads a global mission to elevate trustable information and transform learning experiences through technology. MBA, NYU Stern School of Business Bachelor of Engineering, Coimbatore Institute of Technology Certificate in Design Thinking, Stanford University His research and professional interests center on educational technology, AI in learning, digital publishing, and the future of information . He is passionate about lifelong learning and societal impact, advocating for human-centered design in technology. His work bridges academia and industry, focusing on how digital transformation can improve access, equity, and quality in education. The published articles reflect a strong thematic focus on the intersection of technology, education, and leadership. They emphasize ethical AI, future skills, education reform, talent identification, and early learning investment , indicating a forward-looking, policy-aware, and socially responsible research trajectory. Scientific and Professional Recognition: Stern Scholar, NYU Beta Gamma Sigma Honor Society NACD Governance Fellow Top 100 Global Influencer in Education Technology Best in KLAS Award Frost & Sullivan Technology Innovation Award Student of the Year, Coimbatore Institute of Technology Best Outgoing Student Karthik has advised UNICEF and the Global Coalition for Education on youth skills and education policy. He serves on the board of Urban Upbound and as a non-executive director for Britannica Knowledge Systems and Melingo. His leadership extends to transformative initiatives in Harlem, India’s agriculture, and NYU’s media and technology specialization. Though no formal grants are listed, his strategic partnerships with YouTube, Samsung, Northwestern University, and Nickelodeon reflect significant institutional and industry-level support. He is actively involved in global thought leadership through the World Economic Forum Expert Network and contributes to public discourse via interviews with CEO Today, CIO, Chicago Tribune, and Tech for Good. His work emphasizes excellence, integrity, and the transformative power of education.
Cristian Borcea is a Professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT). His research focuses on federated learning, privacy-preserving systems, mobile computing, and distributed systems. He has led multiple NSF-funded projects, including collaborative studies on privacy interventions in publishing ecosystems and cybersecurity education initiatives. His work spans IoT-driven network control, edge computing, and secure mobile applications. Key Research Areas: Federated Learning, Edge Computing, Privacy-Preserving AI, Mobile Sensing, IoT Notable Projects: CyberCorps Scholarship Program, SaTC Core Project on Online Privacy, NSF-funded Mobile Distributed Computing Recent contributions include ZoneFL (zone-based federated learning at the edge), SGCode (secure prompt-optimizing systems), and FedMTL (privacy-preserving multi-task learning frameworks). He actively collaborates with institutions globally, including Japan's National Institute of Informatics, where he delivered a talk on privacy-preserving machine learning systems. He has advised over 100 research outputs, including peer-reviewed articles in top venues like ACM Web Conference and IEEE Transactions. His grants total over $5M in funding, emphasizing interdisciplinary approaches to distributed systems security and privacy.
Xiaowei Guمشاهده پروفایل
مدرس ارشد
Dr. Xiaowei Gu is a Senior Lecturer at the University of Surrey, affiliated with the School of Computer Science and Electronic Engineering and the Computer Science Research Centre. He holds a PhD in Computer Science from Lancaster University (2018). Previously, he served as a Lecturer at the University of Kent, Aberystwyth University, and as a Senior Research Associate at Lancaster University. His research focuses on transparent machine learning models that balance interpretability and performance, particularly in semi-supervised and streaming data contexts. Key applications include disaster response via satellite imagery analysis and environmental monitoring. Notable projects include developing a human-trustable machine learning framework for rapid disaster response using satellite data. Teaching responsibilities include courses like Programming Fundamentals (COM1027) and AI & AI Programming (EEEM005). He actively supervises exceptional PhD candidates with strong research backgrounds in machine learning and data analytics. No scientific awards are explicitly listed, but his work emphasizes impactful, application-driven research. Publications span explainable AI, fuzzy systems, and deep learning applications in environmental and cybersecurity domains. His work often bridges theoretical advancements with real-world challenges, such as wildlife tracking and ocean temperature modeling.
Dejiu Chenمشاهده پروفایل
دانشیار
Dejiu Chen is an Associate Professor in the Unit of Mechatronics at KTH Royal Institute of Technology's Digital Futures Faculty. His research focuses on trustworthy human-compatible Cyber-Physical Systems (CPS), with applications in automotive and medical domains. He holds a Docent title and leads projects addressing system reliability, self-management, and safety assurance. Research interests include embedded control systems, anomaly detection, formal modeling, and AI integration for CPS. Key projects include TRUSST-E (trustable embedded systems), SALIENCE4CAV (autonomous vehicle safety), and SocketSense (IoMT wearable sensors). Publications span over 100 peer-reviewed articles, emphasizing topics like graph neural networks, digital twins, and fault management. He collaborates with industry partners through initiatives like the Mechatronics Twin Framework and condition monitoring methodologies. Teaches courses such as Embedded Systems Design and Smart CPS for Sustainability. Active in grants and industrial partnerships, with a focus on advancing CPS resilience and industrial relevance.