Michele Melchiori is an associate professor at the Università degli Studi di Brescia (Italy) since 1998, specializing in systems for information processing. He holds a PhD in Information Engineering from the University of Brescia and a Master's in Computer Science from the University of Milan. His research focuses on information systems design, semantic-based services, blockchain integration, and smart city technologies. Notable contributions include frameworks for smart contract design, blockchain applications in agri-food supply chains, and IoT-driven solutions for construction quality assurance. His work bridges theoretical advancements with practical implementations, spanning projects funded by collaborative initiatives. Key areas include personalized data exploration using semantic web technologies, trust management in decentralized systems, and healthcare applications like food recommendation systems. He has authored over 80 publications, emphasizing interdisciplinary approaches to data management challenges. Melchiori frequently contributes to academic events such as the Italian Symposium on Advanced Database Systems. His research bridges technical innovations (e.g., blockchain) with societal needs (e.g., smart city infrastructure and post-pandemic healthcare models).
Nick Camp is an Assistant Professor of Organizational Studies at the University of Michigan, with a courtesy appointment in Psychology. He holds a B.A. in Psychology from Columbia University (2009) and a Ph.D. in Psychology from Stanford University (2018). His research focuses on the social psychology of racial inequality, particularly examining police-citizen interactions and their implications for institutional trust. By analyzing body-worn camera footage, surveys, and experimental methods, he explores how routine encounters shape racial disparities in policing. Camp argues for targeted training to improve officer communication and reduce inequities in law enforcement practices. His work bridges organizational behavior, sociology, and cognitive science, with a focus on translating findings into actionable policy recommendations. Current projects include leveraging AI-driven natural language processing to monitor policing at scale, and studying how physical environments impact workplace well-being through mixed-methods approaches. Camp’s research has been featured in prominent outlets, emphasizing the urgency of addressing systemic biases in public institutions. Education: B.A. in Psychology, Columbia University, 2009 Ph.D. in Social Psychology, Stanford University, 2018 Lab Team: Includes Lab Manager Ara Jo (arajo@umich.edu). Camp’s work integrates interdisciplinary perspectives to address pressing societal challenges, with grants focusing on policing reform and organizational equity initiatives.
Dr. Kwabena Bennin is an Assistant Professor in the Information Technology Group at Wageningen University & Research. His expertise spans software engineering, machine learning, and software quality assurance. He holds a PhD in Computer Science from City University of Hong Kong and a BA (Hons) in Computer Science and Statistics from the University of Ghana. His research focuses on applying AI to software engineering tasks, including defect prediction, automated testing, and software analytics. He has conducted extensive studies on machine learning applications in agriculture, such as plant disease detection using deep learning. Bennin also explores recommender systems for sustainable online food choices and has experience in distributed software development methodologies. He has over 40 international publications and has worked as a Postdoctoral researcher at Blekinge Institute of Technology and a Data Science Consultant at Ericsson. His current projects include developing socio-technical decision support systems for healthy and sustainable food choices in online shopping platforms. Key Skills: Software Architecture, Empirical Software Engineering, Precision Agriculture Analytics Education: PhD in Computer Science, City University of Hong Kong BA (Hons) in Computer Science and Statistics, University of Ghana His work integrates technical innovation with real-world applications, addressing challenges in both software systems and agricultural technology domains.
Paolo Burelli is a Lecturer and Head of the brAIn Lab at the IT University of Copenhagen. He also serves as a Senior Data Scientist at Tactile Entertainment A/S since 2016. His research focuses on Game AI, Player Experience, Machine Learning, and Neuroscientific approaches to gaming. Key affiliations include the Creative AI Lab and The Maritime Hub. Research interests span adaptive game systems, player modeling, and the intersection of neuroscience with game design. Notable projects include the Pioneer Centre for Artificial Intelligence (2021–2034), ALGO (2019–2022), and CREATE (2023–2025). Projects emphasize creative AI applications in education, difficulty modeling in games, and maritime safety through alarm-handling practices. Publications highlight work on LLM emotion generation, EEG-based neural decoding, and player frustration tolerance. Collaborations include institutions like Springer and the Danish National Research Foundation. His datasets, such as the Uncanny Valley Face Questionnaire, contribute to facial perception studies. Labs under his leadership include the brAIn Lab, exploring AI ethics, game analytics, and human-centered computing. Projects emphasize practical applications of AI in education and industry.
Shwai He is a PhD student and Affiliate Assistant Professor at the University of Maryland, advised by Ang Li. Their research focuses on advancing AI systems through innovative approaches in large language models (LLMs), fairness in machine learning, and efficient neural network architectures. Key areas include multi-agent systems, causal modeling for bias mitigation, and optimization techniques for mixture-of-experts models. Research interests span artificial intelligence, machine learning, and natural language processing with emphasis on practical applications like healthcare diagnostics and social pairing systems. Notable work includes developing GNWT-based multi-agent digital twins for social platforms and improving LLM transparency through token analysis. Publications highlight contributions to counterfactual fairness, dynamic-depth transformers, and parameter-efficient methods. Current efforts explore computational efficiency in vision-language models and bio-inspired antibody prediction systems. No scientific awards have been mentioned. Advising and grants: Currently a PhD student under Ang Li's supervision. Research involves collaborations across computer science and bioinformatics domains.
Önder Babur is an Assistant Professor in the Department of Information Technology at Eindhoven University of Technology. His research focuses on software engineering, machine learning applications, precision agriculture, and digital twin technologies. He has contributed to projects involving business process modeling, drone analytics, and energy market methodologies. Babur collaborates with institutions like Wageningen University & Research and has supervised PhD candidates in generative AI approaches and digital twin systems. His research interests span model analytics, clone detection, API usage analysis, and low-code platforms. Notable projects include an empirical study of business process models on GitHub and foundational work in digital twins for energy markets. Babur has co-developed datasets for drone imagery analysis and systematic reviews of food recommender systems. His work bridges theoretical software engineering advancements with practical applications in agriculture and energy systems. Advising PhD candidates include Gürkan Soykan (digital twins in energy markets) and Jeroen Doornbos (generative AI in drone analytics). Projects emphasize collaborative frameworks like SAMOS for model management and Apache Spark-based distributed analytics. Babur’s contributions span 45+ peer-reviewed publications and two active PhD supervisions.
Carlos Badenes-Olmedo is a Post-Doctoral Researcher at the Polytechnic University of Madrid’s Faculty of Informatics, part of the Ontology Engineering Group (OEG). He holds a Master’s in Artificial Intelligence (2015) and a Computer Science Engineering degree (2006) from the same institution. Previously, he worked in industry for 8+ years as a software architect specializing in real-time data and M2M communications. He collaborates with the TEDECO group on data mining using Call Detail Records (CDRs). Research Focus: Ontology Engineering, Machine Learning, Information Retrieval, Exploratory Search, Recommender Systems, Multilingual Document Similarity, Public Procurement Analysis, and Clinical Data Mining (e.g., polypharmacy studies). His work includes developing cross-lingual search engines, knowledge graphs for public procurement (e.g., EU Contract Hub), and health-related ontologies (e.g., Drugs4Covid). Key Projects: Led development of the Corpus Viewer platform for analyzing research documents, created the FarolApp for light pollution monitoring using Linked Data, and contributed to the librAIry framework for distributed text mining. Active in public procurement transparency initiatives and biomedical knowledge graph construction. Skills: Natural Language Processing, Topic Modeling, REST APIs, Docker, Linked Data, and open-source tool development (e.g., TBFY Harvester). Collaborates internationally on EU-funded projects and publishes extensively in top venues like K-CAP, ISWC, and IEEE conferences. Teaching: Delivers tutorials on hybrid NLP techniques, cross-lingual document exploration, and semantic search. Involves in educational experiments like LEGO® Serious Play in software engineering education.
Taolue Chen is a Senior Lecturer in the School of Computing and Mathematical Sciences at Birkbeck, University of London. He holds a PhD from Vrije Universiteit Amsterdam and MSc/BSc degrees from Nanjing University, China. His research focuses on neuro-symbolic software engineering, combining AI (Machine Learning/NLP) with formal methods in software engineering, program analysis, and verification. He has published extensively in top conferences like POPL, OOPSLA, and NeurIPS, and has received multiple awards including the ACM SIGSOFT Distinguished Paper Award (2024). Education: PhD: Centrum Wiskunde & Informatica (CWI) and Vrije Universiteit Amsterdam (2010s) MSc: Computer Science, Nanjing University (China) BSc: Computer Science, Nanjing University (China) Research Interests: Taolue's work bridges AI and traditional software engineering, with a focus on neuro-symbolic systems, code generation, adversarial robustness, and formal verification of cryptographic programs. He explores synergies between statistical (deep learning) and logical (constraint solving) methods to address challenges in software verification and cybersecurity. Articles Overview: His recent work emphasizes code generation improvements, adversarial defense mechanisms, and formal verification of secure cryptographic implementations. Key themes include enhancing model robustness, optimizing documentation in code generation, and applying large language models to symbolic reasoning tasks. Awards: Best Paper Award at SETTA’20 (2020) 1st Prize in CCF Software Prototype Competition (2022) QF Strings Competition Win (2023) ACM SIGSOFT Distinguished Paper Award (2024) Advising & Grants: Advises PhD student JEFERSON DORNELLES SCHNEIDER. His work is supported by grants focusing on neuro-symbolic systems, cybersecurity, and formal methods for software engineering. Labs/Teams: Leads research groups in neuro-symbolic software engineering and cryptographic verification at Birkbeck, collaborating with institutions like University of Oxford and University of Twente.
Dr Colin Perkins is a Senior Lecturer (Associate Professor) in Computing Science at the University of Glasgow, serving as Chair of the Internet Research Task Force (IRTF). He leads research in network transport protocols, focusing on real-time multimedia and protocol standardization. His work includes contributions to QUIC, post-Sockets APIs, and improving Internet protocol specifications. Education: BEng (Electronic Engineering, 1992) and PhD (1996) from the University of York's Department of Electronics. Research Interests: Transport protocols for real-time multimedia Network protocol design and implementation Standardization processes in IETF QUIC protocol implications Post-Sockets API development Professional Roles: Co-chair of the RTP Media Congestion Avoidance Techniques (RMCAT) IETF working group Past co-chair of Audio/Video Transport and Multiparty Multimedia Session Control groups Member of Glasgow Systems Section (GLASS) and Networked Systems Research Group Awards: Fellow of the Higher Education Academy Senior Member of IEEE Grants & Labs: Active in Scottish Networking Event (SCONE) initiatives and collaborative projects on network measurement, protocol analysis, and distributed systems.
Peter Menell is the Koret Professor of Law at the University of California, Berkeley School of Law, and Co-Director of the Berkeley Center for Law & Technology (BCLT). He co-founded BCLT in 1995 and BJI (Berkeley Judicial Institute) in 2018 to bridge academia and the judiciary. His work focuses on intellectual property law, judiciary reform, and technology policy. Menell holds a J.D. from Harvard Law School and a Ph.D. in Economics from Stanford University. Research interests include intellectual property in digital technology and entertainment, environmental law, law and economics, and judicial reforms. He has authored over 100 articles, 15 books, and co-founded Clause 8 Publishing to make legal education accessible. His contributions include advising U.S. agencies on trade secrets and shaping the Defend Trade Secrets Act (2016). Menell has organized over 60 IP education programs for the Federal Judicial Center, including annual ‘Intellectual Property in the Digital Age’ seminars. He co-authored the 1,200-page Patent Case Management Judicial Guide, a key resource for federal judges. Recent projects include leading WIPO’s International Patent Case Management initiative and advising the U.S. PTO as an Edison Distinguished Scholar. Honors include the Donald C. Brace Memorial Lecture (2013) and Melville B. Nimmer Memorial Lecture (2019). His advocacy spans patent eligibility, design patent law, and API copyright issues, with a focus on consensus-building in contentious areas like Section 101 reforms. Menell’s work bridges legal scholarship and policy impact, addressing challenges like federal judiciary capacity crises and innovation incentives in life sciences. He collaborates with interdisciplinary teams and governments globally, emphasizing equitable policy solutions.
Jana Lasser is Professor for Data Analysis at the University of Graz and leads the Complex Social & Computational Systems research group at the interdisciplinary IDea_Lab. She is also Associate Faculty at the Complexity Science Hub Vienna (CSH), reflecting her deep engagement with complex systems research across institutions. Her educational background includes a PhD in Physics from Georg-August-University of Göttingen, based on research at the Max Planck Institute for Dynamics and Self-Organization. She held postdoctoral and visiting positions at the Medical University of Vienna, Graz University of Technology (as a Marie Curie Fellow), and RWTH Aachen (as interim professor) before joining the University of Graz in 2024. Her research centers on emergent phenomena in complex social systems, using machine learning, data science, NLP, and computational modeling. Key interests include misinformation, counterspeech, social media algorithms, mental health in academia, and pattern formation in geophysical systems. She is a leading voice in open science, data literacy, and reforming academic culture. Her recent publications (2023–2025) reveal a strong interdisciplinary trend, bridging computational social science, public health, political communication, and geophysics. Many papers focus on misinformation, political discourse, and algorithmic governance, often using large-scale social media data. Others explore mental health, academic labor, and foundational geophysical processes, demonstrating her wide-ranging analytical expertise. ERC Starting Grant 101160928 (DeSiRe) FWF standalone project P 37280-N netidee SCIENCE prize Open Knowledge Fellow of the Wikimedia Foundation (2019/2020) Marie Curie Fellow Jana Lasser actively mentors and advises through her leadership of major research projects and initiatives. She leads the Survey Special Interest Group in the COST Action on Researcher Mental Health and co-founded the Network Against Abuse of Power in Science. Her research has been supported by prestigious grants including an ERC Starting Grant and FWF funding. She has developed and taught numerous open-access courses in computational social science, Python, and data literacy, emphasizing reproducibility and educational outreach. She leads the Complex Social & Computational Systems research group at IDea_Lab and is a key figure in the Complexity Science Hub Vienna. Her work on the Schwurbelarchiv and agent-based models for healthcare resilience demonstrates her leadership in building and utilizing large-scale data infrastructures for societal benefit.
Grzegorz Kołaczek is a faculty member at the Faculty of Information and Communication Technology at Wrocław University of Science and Technology, affiliated with the Department of Computer Science and Systems Engineering . His research focuses on cybersecurity , intrusion detection , and security modeling with specific interests in Trust-based security frameworks IoT cybersecurity Anonymity protocols Fraud detection in digital systems . His recent publications emphasize the intersection of cybersecurity and emerging technologies , particularly in Internet of Things environments and e-commerce platforms. Key research trends include collaborative intrusion detection , adaptive user interfaces , and machine learning for threat analysis . Contact: grzegorz.kolaczek@pwr.edu.pl
V.Prof.Dr. Nevzudin Buzađija is an Associate Professor at the Software Engineering Department , Faculty of Philosophy, University of Zenica, Bosnia and Herzegovina. He holds leadership roles as Head of the Software Engineering Department and Vice Dean for Teaching and Student Affairs at the Polytechnic Faculty. Research focuses on Software Engineering , Blended Learning , Blockchain Applications , and Educational Technology Courses taught include Computer Architectures , Databases , and Informatics Methodology across multiple departments Pioneer in applying fuzzy logic and blockchain to educational systems Recent Publications highlight advancements in: DevOps Methodology for modern software development Microservices with RabbitMQ message brokers Smart Contract optimization and blockchain for digital certificates Scratch Programming in K-12 education Artificial Intelligence for multimedia content analysis His work bridges academic research and educational practice , with significant contributions to curriculum design and ICT integration in transitional economies.
Rita Kuo is a Visiting Assistant Professor in the Department of Computer Science and Engineering at New Mexico Institute of Mining and Technology (New Mexico Tech), where she teaches foundational and advanced courses in computer science, including Python programming, object-oriented programming, web development, and human-computer interaction. She holds a Ph.D. in Electronic Engineering from Chung-Yuan Christian University, Taiwan, and has prior academic experience at Mingdao University and Knowledge Square, Inc. Ph.D., Electronic Engineering, Chung-Yuan Christian University (2007) M.S., Information and Computer Engineering, Chung-Yuan Christian University (2002) B.S., Information and Computer Engineering, Chung-Yuan Christian University (2000) Her research focuses on innovative educational technologies, especially game-based learning, mobile and ubiquitous learning, automatic item generation, and intelligent tutoring systems. She explores how gamification, cognitive theory, and AI can enhance student engagement and learning outcomes. Her work integrates computational intelligence with pedagogical design to create adaptive and motivating learning environments. The most recent publications highlight trends in educational game design, learning analytics via Moodle plugins, gamified reward systems, and tools for improving cybersecurity awareness. These works emphasize usability, student engagement, and the integration of cognitive and motivational theories into digital learning platforms. Her scientific contributions have been recognized with awards including the Best Technical Design Paper Award at GCCCE 2018 and an Excellent Paper Award at the International Conference on Technology in Education (2018). Best Technical Design Paper Award, GCCCE 2018 Excellent Paper Award, International Conference on Technology in Education, 2018 Rita Kuo has led and co-led multiple research grants, including projects funded by Google CSR, New Mexico Department of Transportation, and the Computing Research Association. She mentors undergraduate and graduate students in research related to educational technology, gamification, and learning analytics. Her leadership extends to professional service as Vice Chair in Equity, Diversity & Inclusion for IEEE TCLT and Chair of the Educational Gamification SIG in APSCE. She is actively involved in the development of platforms such as GRACE (annotation and clustering), ICER (in-game rewards), and ERIC API, and leads the design of educational games like MEGA World. Her current research emphasizes behavior analytics, mobile learning tools, and inclusive educational technologies.
Mohammad Masudur Rahman is an Associate Professor in the Faculty of Computer Science at Dalhousie University. His research focuses on intelligent automation of software maintenance and evolution , combining Artificial Intelligence (AI) and Software Engineering (SE) to address challenges in bug detection, diagnosis, and reproducibility. He leads the RAISE Lab , which aligns with Dalhousie’s strategic goals in Advanced AI & Digital Innovation , particularly Sustainable Software Innovation and Sustainable AI . Dr. Rahman earned his PhD in Computer Science/Software Engineering from the University of Saskatchewan (2019), advised by Prof. Dr. Chanchal Roy, and completed a postdoc at Polytechnique Montreal under Prof. Dr. Foutse Khomh. He has published 50+ papers in top venues like ICSE , ESEC/FSE , ASE , and TOSEM , with research funded by NSERC Discovery Grant, Mitacs Accelerate International, and Dalhousie Startup Fund. His work investigates the challenges of software bugs, crashes, vulnerabilities, and technical debt , particularly in AI-driven systems like Large Language Models and Deep Learning frameworks. He develops tools to automate bug diagnosis, leveraging code structures and neural machine translation. Recent articles analyze deep learning bug reproducibility , fault diagnosis in attention models , and code smell impacts . Scientific Awards : Governor General's Gold Medal, U of S Doctoral Thesis Award, Dalhousie Belong Research Fellowship, President Gold Medal (Bangladesh). Grants : $475K+ (PI) and $4.3M+ (Co-PI) from NSERC, Mitacs, Climate Action Fund, and Dalhousie.
