Dr. Brady D. Lund is an Assistant Professor at the University of North Texas, focusing on interdisciplinary research at the intersection of information science, artificial intelligence, and ethics. His work addresses AI adoption in libraries, data privacy, academic integrity, and international development. He holds a Ph.D., M.S., and B.S. from Emporia State University and Wichita State University. Education: Ph.D., Emporia State University M.S., Emporia State University B.S., Wichita State University Research Interests: Dr. Lund explores how AI impacts information seeking behaviors, data privacy literacy, and library services. His work emphasizes ethical AI deployment in academic and clinical settings, with a focus on marginalized communities. Key areas include AI-driven library systems, blockchain applications for academic integrity, and the societal implications of generative AI. Research Trends: Recent publications analyze AI's role in health information, cybersecurity threat intelligence, and library leadership in minority-serving institutions. He critiques AI authorship policies, evaluates large language models, and advocates for equitable AI access in developing countries. Labs & Teams: Leads the Computational Humanities and Information Literacy Lab and the CyberCrews initiative, focusing on AI ethics, digital literacy, and interdisciplinary collaboration.
Tianyi Zhang is a Tenure-Track Assistant Professor in the Department of Computer Science at Purdue University, part of the College of Science. He leads the Human-Centered Software Systems Lab, focusing on AI-driven systems that synergize human expertise with machine intelligence to enhance programming productivity and software reliability. Prior to Purdue, he was a Postdoctoral Fellow at Harvard University under Dr. Elena Glassman and earned his Ph.D. from UCLA (2019) and B.Sc. from Huazhong University of Science and Technology (2013). Education: Ph.D. in Computer Science, University of California, Los Angeles (2019) Bachelor's in Computer Science, Huazhong University of Science and Technology (2013) Research Interests: His work spans Software Engineering, Human-Computer Interaction, and AI. Key areas include program synthesis, interactive debugging tools, autonomous driving system testing, and mitigating biases in AI models. He develops systems like Interpretable Program Synthesis and SQLucid to bridge human and machine intelligence. Recent Trends in Publications: Recent work emphasizes human-in-the-loop AI, including mixed-initiative systems for data wrangling (Dango), interactive program repair, and bias analysis in text representations (STILE). He also explores challenges in autonomous driving testing and LLM-based code generation errors. Awards & Grants: NSF Career Award (2024) Amazon Research Award Showalter Trust Research Award for pre-diabetes research $1.5M NSF grant for software supply chain security Best Paper Honorable Mentions at CHI and VAHC Advising & Teams: Supervises 12+ PhD/Master's students and 30+ research interns. Notable advisees include Bonan Kou (API misuse studies) and Yuan Tian (text-to-SQL systems). Collaborates with Harvard Medical School on healthcare data analysis. Labs & Initiatives: Directs Purdue's Human-Centered Software Systems Lab. Co-founded the Societal Impact Fellows program. Active in open-source projects like Examplore for API usage visualization and JShrink for Java debloating.
Ning Nan is an Associate Professor at the University of British Columbia's Sauder School of Business, specifically within the Department of Accounting and Information Systems. With a BA from Peking University, an MA from the University of Minnesota, and a PhD from the University of Michigan, Dr. Nan focuses on digital business strategy, evolvable IT infrastructure, and complex adaptive systems. His research explores blockchain applications, agent-based modeling, and the intersection of AI with societal challenges like sustainability. Education: PhD in Information Systems, University of Michigan MA in Information Systems, University of Minnesota BA in Computer Science, Peking University Research Interests: Dr. Nan investigates how technology shapes organizational and societal systems, with a focus on AI ethics, sustainability through personalized recommendations, and blockchain's role in decentralized supply chains. He employs agent-based modeling to simulate complex phenomena like innovation diffusion and online community dynamics. Recent work addresses explainable AI in smart cities and carbon-reduction gamification strategies. Teaching: In 2024-2025, he teaches Data Management for Business Analytics , emphasizing practical applications of data-driven decision-making. Key Research Themes: His articles highlight trends in AI sustainability (e.g., carbon footprint impacts of recommendation systems), digital business strategy (blockchain governance, app update strategies), and foundational IS theory (hyperturbulence and IS strategy).
Anil Madhavapeddy serves as Professor of Planetary Computing at the University of Cambridge's Department of Computer Science and Technology and directs the Cambridge Centre for Carbon Credits (4C). A Fellow of Pembroke College, he integrates systems research with environmental conservation through the Computer Laboratory's Environment and Energy Group. His career spans industry leadership (NetApp, Citrix, Intel), academic appointments (Cambridge, Imperial, UCLA), and entrepreneurial ventures (XenSource, Unikernel Systems, Docker). Madhavapeddy earned his PhD at Cambridge's Computer Laboratory in 2006. His research bridges computational systems and planetary-scale environmental challenges, with deep expertise in open-source development (OCaml, Xen, Docker, OpenBSD) and technology strategy advising for organizations including Zededa, Tezos Foundation, and Tarides. His work centers on environmental computing and climate informatics, leveraging distributed systems and functional programming to develop sensing infrastructure for conservation. Recent projects focus on carbon credit systems, AI-driven biodiversity monitoring, and sustainable computing architectures that minimize ecological footprints while maximizing analytical capability. Analysis of his 2025 publications reveals a concentrated effort on AI-integrated conservation tools, privacy-preserving carbon accounting, and energy-efficient computing. Key themes include spatial networking for ecological data, LLM-enhanced evidence retrieval in conservation science, and novel metrics for extinction risk assessment—demonstrating computational innovation applied to urgent planetary boundaries. No scientific awards were documented in the source material. Madhavapeddy advises multiple technology firms on strategic development while leading the Cambridge Centre for Carbon Credits, though specific grant funding details remain unreported. He actively contributes to the Environment and Energy Group at Cambridge's Computer Laboratory and directs the interdisciplinary Cambridge Centre for Carbon Credits (4C). His open-source leadership spans critical infrastructure projects including OCaml, Xen, and Docker, fostering collaborative development communities that underpin modern cloud and container technologies.
Zohreh Pourzolfaghar is an Assistant Professor in Management Information Systems (MIS) at the School of Business, Maynooth University (MU). She serves as Director of the IT-Enable Innovation Programme and cluster lead for the Digital Construction cluster at the Innovation Value Institute (IVI). She is also a member of Lero, the SFI Research Centre for Software. Education: PhD in Project Management (University Putra Malaysia, 2011); MSc in Management Systems and Productivity; BSc in Software Engineering. Research Interests : Focuses on digital transformation for SMEs, information management in construction, and smart city architectures. Leads EU-funded projects like EnTrust (agri-data governance), DIGI+ (sustainable digital transformation), and DigiFABs (food & beverage SMEs). Co-PI for projects such as GDI-IE (genomic data infrastructure) and PERFORM (digital retail innovation). Grants & Awards : Secured funding from SFI, Enterprise Ireland, and EU. Notable awards include the BIM Hero Award (2022) and Research Engaged Award (2022). Teaching : Courses include Digital Business, Digital Technology Governance, and Enterprise Architecture. Advises PhD students in MIS and digital transformation. Industry Collaboration : Works with firms like ArcDox and Corballis Technologies on BIM standards and data governance. Active in national and EU policy networks, including NSAI committees.
Renée J. Miller is Professor and Canada Excellence Research Chair in Data Intelligence at the University of Waterloo. A Fellow of the Royal Society of Canada and ACM, her research transforms how organizations manage and derive value from heterogeneous data sources. Professor Miller pioneered foundational work in schema mapping and data exchange recognized by the ICDT Test-of-Time Award. Her current research develops frameworks for semantic data discovery in data lakes, including the SANTOS system for relationship-based table search and Gen-T for table reclamation. She leads international collaborations advancing data management practices through tools like iBench for metadata generation and DIALITE for open data integration. Her CERC position establishes Canada's leadership in next-generation data intelligence systems.
Elena Simperl is a Professor of Computer Science and Deputy Head of Department for Enterprise and Engagement at King's College London's Department of Informatics. She co-directs the King's Institute for Artificial Intelligence and serves as Director of Research for the Open Data Institute. As a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study, she leads the Trustworthy Knowledge Graphs focus group and contributes to advancing human-centric AI research across European institutions. Professor Simperl obtained her doctoral degree in Computer Science from the Free University of Berlin and her diploma from the Technical University of Munich. Prior to joining King's, she held academic positions in Germany, Austria, and at the University of Southampton, and was a Turing Fellow. Her career trajectory demonstrates consistent leadership in bridging academic research with practical applications in data ecosystems. Her research sits at the critical intersection of AI and social computing, focusing on human-centric approaches to building sociotechnical systems that integrate data, algorithms, and human capabilities. She investigates how to make knowledge engineering more accessible, how to leverage collective intelligence for data quality improvement, and how to design participatory AI systems that address societal challenges like misinformation. Her work spans knowledge graphs, semantic technologies, crowdsourcing, and open data, with particular emphasis on the social dimensions of data-intensive systems and the governance frameworks needed for trustworthy AI deployment. Analysis of her recent publications reveals a strong evolution toward integrating large language models with traditional knowledge engineering practices while maintaining human oversight. There's a clear trajectory from foundational work on knowledge representation toward increasingly applied research addressing real-world challenges in media ecosystems, citizen science, and data governance, with growing attention to policy implications of AI technologies. Fellow of the British Computer Society Fellow of the Royal Society of Arts Hans Fischer Senior Fellow at TUM-IAS (2023) Ranked among top 100 most influential scholars in knowledge engineering of the last decade Included in Women in AI 2000 ranking Professor Simperl has led 14 major European and national research projects totaling millions in funding, including MediaFutures (a Horizon 2020 program tackling online misinformation), QROWD, ODINE, Data Pitch, and ACTION. She currently co-chairs the Croissant working group in ML Commons developing data standards for AI, and serves as president of the Semantic Web Science Association. Her research has directly influenced the development of data ecosystems supporting startups and citizen science initiatives across Europe, demonstrating exceptional ability to translate theoretical advances into practical impact. As Director of Research at the Open Data Institute, she oversees initiatives connecting data entrepreneurs with artists and civic organizations. Her leadership in the MediaFutures project established a data-driven innovation hub that supported 51 startups/SMEs and 43 artists through three open calls, creating a sustainable model for arts-technology collaborations addressing media challenges. Her work with the ODINE project helped create a European ecosystem for data-driven startups, demonstrating her commitment to building practical applications of open data principles.
Pontus Johnson is a Professor at the KTH Royal Institute of Technology in Stockholm, Sweden. He leads the Center for Cyber Defense and Information Security (collaborating with Swedish Armed Forces, FRA, MSB, FOI, FHS) and serves as vice director of Cybercampus Sweden since 2024. His research focuses on cybersecurity , enterprise architecture analysis , and probabilistic threat modeling , particularly through his development of the Meta Attack Language (MAL) for simulating cyber attacks on networked systems. Education: MSc in Computer Science, Lund Institute of Technology (1997) PhD in Computer Science, KTH (2002) Docent title, KTH (2007) Leadership Roles: Director, Center for Cyber Defense and Information Security (2013–present) Vice Director, Cybercampus Sweden (2024–present) Board Member, Swedish Research Council (2025–present) Deputy Chair, Swedish Royal Academy of Engineering Sciences (IVA) Board (2024–present) His work spans cybersecurity research , attack simulation methodologies , and enterprise architecture frameworks . He has developed tools like securiCAD (acquired by Google) and pwnPr3d for probabilistic threat modeling. His 15 most recent publications highlight advancements in graph-based attack simulations , automated security assessments , and AI applications in cyber defense . Scientific recognition includes: Listed among Tech Awards Sweden's 50 Most Influential People in Swedish Tech (2022, 2023) Discovery of vulnerability in the Universal Turing Machine (2021) He supervises 16 PhD students and alumni (2005–2024), including Simon Gökstorp , Jakob Nyberg , and Sotirios Katsikeas . His academic service includes over 50 program committee roles and leadership positions in international conferences. He contributes to both academic and public domains through media appearances (SVT, Aftonbladet), courses in ethical hacking , and industry collaboration via his role at Google (20% of his time). His research group Software Systems Architecture and Security (SSAS) focuses on predictive security frameworks and system-of-systems analysis.
Gioele Zardini is the Rudge (1948) and Nancy Allen Assistant Professor at MIT's Department of Civil and Environmental Engineering (CEE), with affiliations to the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS). He holds a PhD from ETH Zurich and previously worked as a postdoctoral scholar at Stanford University. His research focuses on co-design of complex systems, autonomous systems, and game-theoretic modeling of transportation networks. Education: BSc and MSc in Mechanical Engineering and Robotics from ETH Zurich (2017–2019), PhD in 2023. He has held visiting roles at nuTonomy Singapore, Stanford, and MIT. Research interests include co-design methodologies, autonomous vehicle systems, compositionality in engineering, and strategic interactions in mobility networks. Recent work emphasizes scalable fleet coordination, safety-critical robotics, and user-centric transportation solutions. Notable awards include the 2024 ETH Doctoral Dissertation Award (Silver Medal), Best Paper at ITSC 2021, and federal grants for enhancing urban transit equity. He leads the Zardini Lab, fostering interdisciplinary collaboration in systems engineering and autonomy. Grants and advising: Received federal grants for transit accessibility projects. His work on Autonomy Talks has produced over 180 recorded lectures, promoting knowledge exchange in autonomous systems. Labs/Teams: Principal Investigator at LIDS, affiliate at IDSS, and founder of the Zardini Lab, focusing on systems co-design, mobility innovation, and game-theoretic frameworks.
Dr. Min Chi is a Professor in the Department of Computer Science at North Carolina State University, where she joined in 2013 as a Chancellor's Faculty Excellence Program cluster hire in the Digital Transformation of Education. Her academic journey includes a Ph.D. and M.S. in Intelligent Systems from the University of Pittsburgh and a B.E. in Information Science and Technology from Xi'an Jiaotong University, China. She completed postdoctoral fellowships at Carnegie Mellon University's Machine Learning Department and Stanford University's Human Sciences and Technologies Advanced Research Institute. Dr. Chi's research focuses on the development and empirical evaluation of cutting-edge Artificial Intelligence, Deep Learning, and Reinforcement Learning frameworks tailored for addressing human-centric challenges. Her work spans multiple domains including advanced learning technologies, AI and intelligent agents, data sciences and analytics, and human-computer interaction. She has made significant contributions to intelligent tutoring systems, healthcare applications, nuclear power systems, and humanitarian efforts such as food distribution and disaster relief. Her publication record demonstrates a strong focus on applying AI techniques to real-world educational challenges, with recent work examining metacognitive knowledge transfer, reinforcement learning for pedagogical policy induction, and deep learning approaches for proactive help in educational settings. Her research also extends to healthcare applications, food distribution systems, and other socially impactful domains. 10 Best Paper, Best Student Paper, and Outstanding Paper Awards Prestigious Alcoa Foundation Engineering Research Achievement Award NSF CAREER Award Dr. Chi leads multiple significant research projects funded by the National Science Foundation, National Institutes of Health, and the Department of Energy, with a total funding exceeding $7 million. Her work bridges theoretical advances in AI with practical applications that address critical societal challenges in education, healthcare, and humanitarian operations.
Steve Hailes is a Professor of Wireless Systems at the Department of Computer Science, University College London. He has served as Head of Department since 2019 and Deputy Head from 2005. His research spans wireless networks, computational trust, AI, and sensor systems for health, ecological, and environmental applications. Education: PhD and undergraduate degree from Cambridge University Appointment: Joined UCL in 1991 (postdoc), Lecturer in 1992 Research interests include: Trust and security in networked systems (co-founder of computational trust) Security of industrial control systems AI/ML applications in security and causal discovery Multi-agent reinforcement learning and moral behavior modeling Gas sensor fabrication and deployment for diverse applications Recent publications focus on feature selection for cybersecurity , moral alignment in LLM agents , trust-based consensus algorithms , and causal discovery using reinforcement learning . Collaborations include co-authors like Westphal, Musolesi, and Tennant. Applications span healthcare (dementia, JIA), ecology (endangered species in Botswana), and environmental monitoring (CO distribution, meth lab detection).
Huazheng Wang is an Assistant Professor in the School of Electrical Engineering and Computer Science at Oregon State University. His research focuses on reinforcement learning, information retrieval, and trustworthy AI. He received his Ph.D. from the University of Virginia (2021) and B.E. from the University of Science and Technology of China (2015). He holds awards including the 2025 EECS Fabulous Teacher Recognition and SIGIR 2019 Best Paper Award. His work addresses challenges in robust reinforcement learning, adversarial attacks on bandit systems, and applications in scientific discovery. Education: Ph.D., Computer Science, University of Virginia (2021) B.E., Computer Science and Technology, University of Science and Technology of China (2015) Research interests emphasize developing efficient algorithms for reinforcement learning, multi-armed bandits, and their applications in recommendation systems, protein optimization, and security. Notable contributions include provably efficient risk-aware reinforcement learning frameworks and adversarial attack analysis on bandit systems. Recent work includes NSF-funded research on neural bandits (IIS-2403401) and publications in top venues like ICML, NeurIPS, and AAAI. His lab explores embodied LLM agents for team cooperation and federated collaborative online monitoring frameworks.
Rozenn Dahyot is a Professor of Computer Science at Maynooth University within the Faculty of Science & Engineering. She previously held roles as Assistant and Associate Professor in Statistics at Trinity College Dublin (2008-2021) and Lecturer in Computer Science (2005-2008). Her research interests bridge Digital Signal Processing, Computer Vision, Machine Learning, and Statistical Analysis. She organized the European Signal Processing Conference (EUSIPCO2021) in Dublin and served as President of the Irish Pattern Recognition and Classification Society (IPRCS) from 2014-2020. Her work spans topics like semantic scene understanding, CNN compression, and medical image segmentation. Key contributions include advancements in graph-based image analysis, reinforcement learning optimization, and AI-driven systems for disaster management. Dahyot is a member of IEEE, ACM, and EURASIP, contributing to both academic and industrial collaborations.
Paolo Tonella is a Full Professor and Director of the Software Institute at the Faculty of Informatics, Università della Svizzera italiana (USI) in Lugano, Switzerland. He also holds an Honorary Professorship at University College London (UK) and previously led the Software Engineering group at Fondazione Bruno Kessler (Italy). His research focuses on software testing, analysis, and AI-driven systems. He has authored over 200 peer-reviewed papers and 100 journal articles, with an H-index of 72. He teaches courses in Data and Software Engineering and Informatics, including Information Modeling, Probability & Statistics, and Knowledge Search. Key contributions include foundational work on web application testing (ICSE MIP award), evolutionary testing techniques (eToc/EvoSuite tools), and reverse engineering of object-oriented systems. He led the ERC-funded PRECRIME project on anticipatory testing. His recent work addresses AI dependability, autonomous systems testing, and deep learning fault analysis. Scientific awards include the ICSE MIP Award (2001) and ERC Advanced Grant (2018). He has served on editorial boards for major journals like IEEE Transactions on Software Engineering and ACM TOSEM. Current roles include leadership in the Software Institute and organizing the SIESTA summer school.
Assoc. Prof. Dr. Sema Alaçam Doğan has been affiliated with Istanbul Technical University since 2014, serving as an Associate Professor in the Department of Architecture . She has held administrative roles including Deputy Head of Department and Erasmus Coordinator. Education : PhD in Informatics in Architectural Design (2008-2014), MS in Informatics in Architectural Design (2005-2008), and BS in Architecture (1999-2005) from Istanbul Technical University. Her research explores Computational Design , Artificial Intelligence in Architecture , and Sustainable Material Innovation . She investigates digital tools for heritage preservation, daylight optimization in BIM, and cognitive development in architecture students. Recent publications analyze AI-assisted design literacy , machine learning for Sinan mosques , and environmental comfort in Harran houses . Her work integrates algorithmic frameworks with sustainable practices. Scientific awards include multiple ITU Publication and Performance Awards (2021-2024), FABFEST Prizes , and the 2024 Artemis Educator Award from NASA. Active projects like "Physical Computation in Architectural Drawing" and "Robotic Fabrication with Recycled Wind Turbine Blades" demonstrate her leadership in computational and sustainable research.
