Tim Ruben Davidson is a Researcher at the Digital Life Lab (DLAB) within the School of Computer and Communication Sciences at EPFL. His current role is Doctoral Assistant, pursuing a doctoral program in Computer and Communication Sciences. His research focuses on advanced machine learning topics including deep generative models, agentic systems, synthetic data applications, and representation learning. His work bridges theoretical advancements in AI with practical implications, particularly in understanding AI agency, synthetic data generation, and latent space structures. Key research trends in his articles include exploring AI self-awareness, evaluating AI-driven peer review systems, and optimizing generative models through geometric and topological approaches. He has contributed to foundational studies on hyperspherical VAEs and reparameterization techniques on Lie groups, advancing mathematical foundations of neural networks. His work is published in top-tier venues and reflects interdisciplinary engagement between computer science, mathematics, and ethical AI considerations.
Dr. Vladimir Vlassov is a full Professor in Computer Systems at the Division of Software and Computer Systems (SCS) , Department of Computer Science (CS) , School of Electrical Engineering and Computer Science (EECS) , KTH Royal Institute of Technology , Stockholm, Sweden. He leads the AVA project in ALEC2, an AI-powered system for mental health care. He is a member of the Distributed Computing research group (DC@KTH) . Education & Roles: Holds a PhD and is a member of ACM and IEEE. Previously visited MIT (1998) and UMass Amherst (2004). Teaches courses on Data Mining , Distributed Systems , and Concurrent Programming . Research Interests: Focus on scalable AI, Cloud computing, distributed systems, and NLP for mental health. Projects include ExtremeEarth (Copernicus data analytics) and EMJD-DC (distributed computing PhD program). Grants & Projects: Principal Investigator in ALEC2 (adaptive mental health care) and ExtremeEarth (EU H2020). Led EU projects like ENCORE (manycore systems) and PaPP (embedded systems). Labs & Teams: Directs the Distributed Computing group, contributing to Hopsworks (machine learning feature store) and Maggy (hyperparameter optimization).
Patrick Lam is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, with a cross-appointment to the Cheriton School of Computer Science. His research focuses on applications of programming languages and static analysis to software engineering challenges, emphasizing verifiable software specifications and program understanding. Dr. Lam has held significant grants from NSERC and is recognized for his impactful work, including the First Decade High Impact Paper award for his Soot framework. Education: Doctorate in Computer Science, Massachusetts Institute of Technology, 2007 Master's in Computer Science, McGill University, 2000 Bachelor's in Joint Honours Mathematics and Computer Science, McGill University, 1999 Research Interests: His primary areas include static program analysis, verifiable software specifications, and compiler design, with a focus on linking high-level software designs to low-level implementations. He explores techniques like lightweight specifications and domain-specific languages to enhance software reliability and efficiency. Recent work also addresses empirical studies of programming practices and security through modularization. Publications: Dr. Lam's recent publications span advancements in static analysis tools (e.g., WasmWalker for WebAssembly), formal verification of code generated by AI tools like GitHub Copilot, and empirical studies on C++ immutability usage. His work bridges theoretical programming language research with practical software engineering applications, emphasizing tools for developer productivity and code reliability. Awards and Recognition: First Decade High Impact Paper recognition for "Soot – A Java Optimization Framework" (2010) Teaching and Grants: He has taught courses such as CS 447, ECE 453, and ECE 459 on software testing and performance programming. Active in grant-funded research, he secured NSERC Engage Grant (2013) and an ongoing NSERC Discovery Grant (2013–2018). Lam has also advised graduate students and contributed to the Software Engineering Program at Waterloo as its Director (2016–2019). Labs and Teams: His research group explores topics in program analysis and software engineering, with collaborations on projects like abstract debugging tools (GobPie) and static analysis frameworks (Soot). He maintains an open-source repository on GitHub, contributing to educational materials and research tools.
Yannis Konstas is an Associate Professor (Reader in the UK system) at Heriot-Watt University’s School of Mathematical & Computer Sciences, Department of Computer Science. He co-leads the Safe and Secure AI for Robotics (SAIR) theme at the National Robotarium. His research focuses on Responsible, Safe, and Explainable AI applications using NLP, including Gender-Based Violence (GBV) detection via LLMs, Social Behavior Modeling, and Vision-Language-Action (VLA) models for robotics. He holds a PhD from the University of Edinburgh (2013), supervised by Mirella Lapata, and has held postdoctoral roles at the University of Washington and the University of Edinburgh. Research interests include Natural Language Generation (NLG), representations, modeling, and evaluation across domains like math problems and dialogue systems. His work spans Psycholinguistics, semantics, and Information Retrieval. He actively explores new fields, such as LLM interpretability and instruction-driven robotic manipulation. He accepts PhD students and collaborates on interdisciplinary projects, including regulatory compliance digitalization and embodied AI for egocentric video understanding. Education: PhD in Computer Science (2013), University of Edinburgh; Postdoctoral Researcher at University of Washington (2015–2017) and University of Edinburgh.
Assoc Prof Cesar Albarran-Torres is a Mexican-Australian scholar and film critic at Swinburne University of Technology. As an Associate Professor in Media , he explores intersections of postcolonial identities , digital media , and Latin American political cultures . His work spans academic publications public engagement supervision of HDR students . His research focuses on digital gambling , media history , and transnational film studies , examining topics like social media and narco-politics AI-generated art indigenous representation in Hollywood . A key project, Understanding Children’s Mobile Gamble-Play Cultures , funded by the ARC, investigates how mobile media normalizes gambling among youth. Recent publications analyze media’s role in framing Mexican drug cartels , streaming’s impact on cultural representation , and digital platforms’ influence on political discourse . He also contributes to journals like Senses of Cinema and Refractory , and serves on the Glen Eira Multicultural Advisory Committee. His academic background includes a PhD in Digital Cultures , a Master in Digital Communication and Culture , and a Bachelor in Communication Sciences , with additional filmmaking training from the New York Film Academy.
Yifan Sun is an Assistant Professor in the Department of Computer Science at William & Mary, leading the Scalable Architecture Lab. He holds a Ph.D. in Electrical and Computer Engineering from Northeastern University (2020). His research focuses on GPU architecture, simulation tools, and multi-GPU system design. Recent work includes TrioSim (a lightweight DNN workload simulator) and NetCrafter (optimizing multi-GPU network traffic). He has published extensively at top venues like ISCA, MICRO, and IEEE Vis. Educations: Ph.D. in Electrical and Computer Engineering, Northeastern University (2020); M.S. and B.S. not explicitly stated but implied through academic progression. Research Interests: Developing explainable architecture tools, improving simulation frameworks (Akita/MGPUSim), and addressing challenges in wafer-scale GPU design. His work bridges hardware-software co-design with visualization techniques to enhance human understanding of complex architectures. Grants: Awarded NSF CCRI and CRII grants for simulation-as-a-service and explainable architecture projects. Collaborations include UVA, NUS, and Northeastern University. Labs/Teams: Scalable Architecture Lab (SARCHLAB), focusing on GPU systems, simulation, and visualization. Active in organizing workshops and GitHub repositories (e.g., https://github.com/sarchlab).
Marco Maggini is a Full Professor in the Department of Information Engineering and Mathematics at the University of Siena, a position he has held since joining the university in 1996. His academic career spans over 25 years with foundational expertise in computer engineering and artificial intelligence, focusing on theoretical and applied machine learning research. His educational background includes: Laurea degree (cum laude) in Electronics Engineering from the University of Florence (1991) Ph.D. in Computer Engineering and Control Systems from the University of Florence (1995) Prof. Maggini's research encompasses machine learning, neural networks, kernel machines, and the integration of symbolic and sub-symbolic knowledge systems. He extends these foundations into practical applications including web mining, search engine technology, pattern recognition, natural language processing, and computer vision. This interdisciplinary approach bridges theoretical computer science with real-world implementation challenges across multiple domains. Analysis of his 15 most recent publications (2023-2025) reveals a dominant focus on multilingual NLP applications, particularly educational puzzle generation for low-resource languages (Italian, Arabic, Persian, Turkish) using LLMs. His work demonstrates consistent innovation in named entity recognition, commonsense reasoning evaluation, and cross-lingual adaptation techniques. Secondary research threads include medical imaging segmentation, molecular property prediction, and AI security vulnerabilities, reflecting his broad technical mastery across computer vision, bioinformatics, and adversarial machine learning. No specific scientific awards were mentioned in the provided documentation, though his editorial roles indicate peer recognition within the academic community. While student mentoring details are absent from the source material, his position as Full Professor and leadership of SAILab imply active graduate supervision. His extensive publication record (120+ papers) and editorial service suggest significant research grant involvement, though specific funding sources remain undocumented. He directs the Siena Artificial Intelligence Laboratory (SAILab), which serves as an interdisciplinary hub for advancing machine learning theory and applications. The lab's current projects emphasize educational technology, multilingual NLP systems, and the integration of symbolic reasoning with neural architectures, maintaining strong industry and international academic collaborations.
Dr. Raja Sooriamurthi is a Teaching Professor and Program Director of the Decision Analytics and Systems minor at the Information Systems Program of Carnegie Mellon University's Heinz College. His teaching and research focus on artificial intelligence, cognitive science, and educational pedagogy. Teaching Interests: Data science, database systems, big data, puzzle-based learning, system development lifecycle Research Interests: Case-based reasoning, knowledge management, distributed reasoning, machine learning, software development pedagogy Dr. Sooriamurthi leads curriculum innovation in information systems education, particularly through the IS2020 competency model . His work bridges AI applications with educational technologies, emphasizing authentic learning and generative AI tools for skill development. Key publication themes include: SQL instruction using AI-driven assessment Information systems curriculum design Puzzle-based learning for critical thinking Service-learning in leadership development Integration of NoSQL databases in education
Carmel O’Shannessy is a Senior Lecturer at the Australian National University’s School of Literature, Languages and Linguistics and an affiliate of the ARC Centre of Excellence for the Dynamics of Language (CoEDL) . Her work focuses on language contact, mixed languages, and child language acquisition, particularly in Indigenous Australian communities. Education: PhD in Linguistics (University of Sydney, Australia; Max Planck Institute for Psycholinguistics, The Netherlands, 2007) She has documented the development of Light Warlpiri , a new mixed language, since its emergence. Her research explores how children and adults contribute to contact-induced language change, with fieldwork in Central Australia since 1996. Key projects include her ARC Future Fellowship grant for tracking Indigenous children’s language development. Recent publications span topics like typology of Australian contact languages, child-directed speech modifications in Warlpiri, and sociolinguistic dynamics of youth language varieties. Her work appears in journals such as Journal of Pidgin and Creole Languages and Languages , as well as edited volumes like The Oxford Guide to Australian Languages . Scientific Awards: ARC Future Fellowship She has mentored students including Francois-Xavier Faucounau , Annie Kwai , and Zobule . Her interdisciplinary approach combines linguistic analysis, digital tools (e.g., the Little Kids Learning Languages app), and community collaboration. Labs/Teams: ARC Centre of Excellence for the Dynamics of Language (CoEDL)
Professor Kewen Wang is a faculty member in the School of Information and Communication Technology at Griffith University , where he has been actively working in computational logic, knowledge representation, and their applications in artificial intelligence for over 30 years. His research has led to the development of novel logics, computer languages, and systems for knowledge representation and reasoning. Broad research areas: Computational Logic, Knowledge Representation, Artificial Intelligence, Programming, Knowledge Graphs, Explainable AI, Ontology Reasoning, Rule Learning Key contributions: RLvLR (scalable rule learner for KGs), TyRuLe (typed rule learning), Drewer (Datalog+- query engine), ALBERT+CCR (CommonsenseQA model), auction design algorithms His research has been widely cited in top venues like Artificial Intelligence , JAIR , ACM Transactions on Computational Logic , and conferences AAAI (Area Chair 2022-2025), IJCAI , KR . He has secured six ARC Grants (five Discovery, one Linkage) and smaller grants from NICTA, CSIRO, and Griffith University. Editorial roles: Area Chair for AAAI (2022-2025), Associate Editor for Journal of Web Semantics , TGDK Supervision: Has supervised over 15 PhD students including Hong Wu, Peng Xiao, and Pouya Omran Teaching: Courses in Intelligent Systems, Data Structures, Discrete Mathematics, and Robotics
Hwajung Hong is an Associate Professor in the School of Interactive Computing at Georgia Institute of Technology's College of Computing. With a prolific publication record spanning from 2009 to 2025, Dr. Hong has established herself as a leading researcher at the intersection of Human-Computer Interaction, accessibility, and mental health applications. Her work frequently appears in top-tier venues including CHI, CSCW, and DIS, with growing emphasis on AI/LLM applications in recent years. Dr. Hong's research focuses on designing technology for vulnerable populations, particularly individuals with autism spectrum disorder, mental health challenges, and neurodiverse communities. Her early work centered on social computing applications for autism support, evolving toward more comprehensive systems addressing mental wellness, stress management, and relationship dynamics. Recent publications demonstrate a strategic pivot toward leveraging large language models for healthcare interventions, communication support, and bias mitigation. Analysis of her 15 most recent publications reveals a strong trajectory toward AI-mediated interventions across multiple domains - from mental health support for Korean investigative officers to communication tools for minimally verbal autistic children. Her work consistently emphasizes user-centered design, cultural sensitivity, and practical implementation in real-world contexts rather than purely theoretical approaches. Dr. Hong has mentored numerous graduate students who have become productive researchers in their own right, with Kwangyoung Lee, Dasom Choi, and Hyunseung Lim appearing as frequent collaborators on recent publications. Her research program demonstrates remarkable continuity in addressing human-centered challenges while adapting methodologies to incorporate emerging technologies.
Brady D. Lund is an active researcher in Library and Information Science with significant contributions to bibliometrics, information behavior, and the ethical implications of artificial intelligence in scholarly communication. His research spans multiple domains including data science ethics, information literacy, and public library services, with particular attention to how digital technologies impact information practices across diverse populations. Lund's research interests focus on the intersection of information science and emerging technologies, particularly examining how AI systems affect scholarly publishing practices, research ethics, and information behavior. His work on ChatGPT's impact on academic writing and AI authorship policies has been particularly influential in library and information science circles. He also investigates information literacy among vulnerable populations, including rural older adults during the pandemic, highlighting the critical role of libraries in community information ecosystems. Analysis of Lund's recent publications reveals a clear trajectory toward examining the ethical dimensions of AI in information contexts, with increasing focus on transparency frameworks, data privacy, and the practical implementation of AI systems in professional settings. His collaborative work spans multiple disciplines, connecting information science with healthcare, cybersecurity, and public policy. Lund demonstrates strong collaborative patterns, frequently working with Ting Wang and Nishith Reddy Mannuru across multiple publications. His research shows methodological diversity, employing both quantitative bibliometric approaches and qualitative investigations of information behavior. While specific grant funding isn't detailed in the publication records, his work addresses significant societal challenges related to information access, digital equity, and ethical technology implementation.
Lai Ma is Associate Professor at the School of Information and Communication Studies, University College Dublin (UCD), where she also serves as Director of Research (2022–2025) and previously directed the MLIS and GradDipLIS programmes. She holds a PhD in Information Science from Indiana University Bloomington and a BSc(Econ) from The Chinese University of Hong Kong. Her work bridges philosophy, information science, and science policy. PhD, Information Science, Indiana University Bloomington MLIS, Indiana University Bloomington BSc(Econ), The Chinese University of Hong Kong Her research centers on the epistemology of information and knowledge production, with a focus on open research, scholarly communication, research evaluation, and research infrastructure. Influenced by critical social theory, philosophy of language, and STS, she investigates issues of epistemic injustice, bibliodiversity, and the political economy of academic publishing. A major theme is the critique of metrics and platformisation in research. Her recent publications reveal a strong trend toward analyzing the structural inequalities in global knowledge production, especially through the lens of open access models, citation practices, and research assessment. She critically examines how commercial interests and dominant platforms shape what counts as knowledge, often marginalizing voices from the global periphery. Best Paper Meta Reviewer Award Teaching Excellence Award Best Paper Reviewer Award Lai Ma leads the ERC Consolidator Grant project Sustainable and Collaborative Research Information for Bibliodiverse Ecosystems (SCRiBe) (2025–2030) and has secured other grants on open research culture. She actively mentors PhD students and has coordinated key modules such as Digital Libraries , Scholarly Communication , and Research and Practice in LIS . She serves on editorial boards and review panels for major journals and funding bodies, and has held leadership roles in ASIS&T and the Library Association of Ireland. She is affiliated with the UCD Geary Institute for Public Policy and contributes to policy discussions on research evaluation, ethics, and open science. Her work emphasizes the need for community-governed, equitable, and sustainable research infrastructures.
Halvor Eifring is a Professor of Chinese Studies at the Department of Cultural Studies and Oriental Languages, Faculty of Humanities, University of Oslo. With expertise spanning Chinese language, literature, philosophy, and meditation studies, he has established himself as a leading scholar in interdisciplinary Chinese studies and comparative meditation traditions. Dr. Eifring received his Master's degree in linguistics in 1987 and his Ph.D. in 1993, both from the University of Oslo, where he has been a professor of Chinese since 1995. His academic journey includes research visits to prestigious institutions including Princeton University (1992), National Taiwan University (1995), Peking University (2000), Harvard University (2001), Center for Chinese Studies in Taiwan (2007, 2009), and Meiji University in Japan (2018). Eifring's research interests span multiple interconnected domains. His primary focus includes Chinese language (both modern and pre-modern), Chinese literature (especially pre-modern fiction), and Chinese philosophy (particularly early Confucianism and Daoism). He has made significant contributions to the study of meditative traditions, examining how language, culture, and thought intersect in Chinese contexts. His current work explores 'mind wandering' across various contemplative traditions, while his longstanding research investigates psychological structures in the 18th-century Chinese novel 'Dream of Red Mansions.' Analysis of Eifring's recent publications reveals a clear interdisciplinary trajectory, bridging Chinese studies with cognitive science, neuroscience, and comparative religious studies. His work increasingly focuses on the intersection of meditation practices, consciousness studies, and cultural contexts, with particular attention to how traditional Chinese philosophical concepts inform contemporary understandings of mind and cognition. The publications demonstrate a methodological approach that combines philological rigor with cross-cultural comparative analysis. Eifring has held significant academic leadership positions, serving as director of the Department of East European and Oriental Studies (1997-1999) and research leader at the Department of Cultural Studies and Oriental Languages (2005-2006). He teaches Chinese language, literature, and culture at both bachelor's and master's levels, occasionally extending to East Asian and general linguistics. Beyond academia, he serves as an editor for the cultural magazine 'Dyade' and is a meditation teacher at 'Acem,' reflecting his commitment to bridging scholarly research with practical application. His current research projects include 'Two Thousand Years of Mind Wandering' and he is affiliated with the research group 'Literature, Cognition and Emotions' at the University of Oslo, demonstrating his ongoing engagement with interdisciplinary approaches to understanding human cognition through cultural and historical lenses.
Dr. Can Liu is an Assistant Professor at the School of Creative Media, City University of Hong Kong, where she leads the ERFI Lab (Laboratory of Empirical Research for Future Interfaces). Her research focuses on designing future interfaces for ubiquitous technologies through empirical understanding of human cognition and behavior, with emphasis on multimodal interaction combining physical and digital elements. Education: PhD in Human-Computer Interaction, Université Paris-Sud (France), INRIA labs ex)situ and ILDA MSc in Media Informatics, RWTH Aachen University (Germany) Dr. Liu's research spans three primary domains: AI-assisted Input (using LLMs/NLP to enhance text manipulation and speech interfaces), Spatial Computing (multimodal interfaces for AR/VR and large displays), and Hybrid/Remote Collaboration (supporting intuitive remote interaction through understanding collocated collaboration). Her work integrates empirical user studies with real-world system deployments in public spaces. Recent publications demonstrate strong trends toward LLM-integrated interfaces, wearable computing applications, and novel interaction techniques for foldable devices. Her team consistently publishes at top venues including CHI, UIST, and CSCW, with increasing focus on practical AI integration for everyday tasks. Awards and Recognition: Best Paper Award at ACM CHI 2014 (top 1%) Honourable Mention at ACM CHI 2012 (top 5%) Dr. Liu actively mentors PhD students and researchers while securing substantial research funding including Google Faculty Research Awards, National Natural Science Foundation grants, and RGC Early Career Schemes. She serves on numerous program committees including ACM CHI (Associate Chair 2024, 2022, 2021, 2020, 2019, 2017) and co-organizes research initiatives like the HCIX Summer Research Program. Her laboratory ecosystem includes the ERFI Lab, affiliation with the Augmented Materiality Lab and Kowloon Interaction Center, and active participation in the Greater Bay HCI community, supporting both fundamental research and industry collaboration with partners including Google, Huawei, and Lenovo.
