Vadim Bulitko is a Professor in the Faculty of Science at the University of Alberta, affiliated with the Department of Computing Science. He holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. Research Interests: His work spans heuristic search, program synthesis, and deep learning applications for sound. Recent projects focus on AI-driven puzzle generation, pathfinding in dynamic game environments, and neural network classification. Publications: His 15 most recent articles explore AI advancements in puzzle design, video-game navigation, and bioacoustic classification, emphasizing heuristic optimization and explainable AI techniques.
Dr. Aneesha Bakharia is a Senior Lecturer - Teaching Focussed at the School of Electrical Engineering and Computer Science within the Faculty of Engineering, Architecture and Information Technology at the University of Queensland. She has established herself as a prominent researcher in educational technology and learning analytics with numerous publications spanning over a decade. Her educational background includes a Bachelor (Honours) of Engineering, a Postgraduate Diploma, and a Masters (Coursework) of Digital Design from Griffith University, along with a Postgraduate Diploma in Open and Distance Learning from the University of Southern Queensland. These qualifications form a strong foundation for her interdisciplinary approach to educational technology research. Dr. Bakharia's research primarily focuses on learning analytics, educational technology, and the application of artificial intelligence in educational contexts. Her work explores how data-driven approaches can enhance teaching practices and student learning experiences. She has made significant contributions to the development of learning analytics dashboards, the integration of AI in education, and the design of effective online learning environments. Her recent research has particularly emphasized generative AI applications in educational settings, examining how these technologies can transform teaching and learning practices while addressing associated challenges and ethical considerations. Analysis of her recent publications reveals a clear progression toward AI-integrated educational technologies, with an increasing focus on generative AI applications in teaching and learning. Her work spans multiple domains including programming education, language learning, work-integrated learning, and medical education, demonstrating the versatility of her research approach. The consistent thread throughout her publications is the application of data analytics and technological innovation to solve practical educational challenges. Dr. Bakharia is actively engaged in supervision, as indicated by her availability for student supervision at the University of Queensland. Her collaborative approach is evident in her extensive co-authorship with researchers across various disciplines, particularly in projects involving dashboard design, learning analytics implementation, and AI in education initiatives. Her research has been implemented through various collaborative projects, including the development of tools like PerspectivesX for collaborative learning activities and SNAPP (Social Networks Adapting Pedagogical Practice), which provides visualizations of student interaction networks. These projects often involve interdisciplinary teams working at the intersection of computer science, education, and domain-specific teaching contexts.
Akos Ledeczi is a Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on computer science education and wireless sensor networks (WSN) , with notable contributions to visual programming tools like NetsBlox and anti-poaching systems like WIPER. He holds a Ph.D. from Vanderbilt University and a Diploma from the Technical University of Budapest. His education initiatives include the NetsBlox platform for K-12 STEM education and a popular Coursera MOOC on introductory programming. In WSN, his team developed a countersniper system with real-time shooter localization and a wearable system for military applications. He is also a leader in Model Integrated Computing , creating tools like the Web-based Generic Modeling Environment. Recent work includes NSF-funded projects on cybersecurity education in middle schools and animal-borne acoustic monitoring. His awards include the ACM SenSys Test of Time Award (2014) and the Best Showpiece Award at IEEE VL/HCC (2021). Key grants and collaborations span NSF projects, Vodafone innovation programs, and the Cyber Makerspace initiative. His lab develops tools like DeepForge and RoboScape Online , emphasizing open-source and collaborative platforms. Students supervised include Devin Jean (K-12 tools), Gordon Stein (robotics simulations), and Brian Broll (NetsBlox extensions).
Dr. Ilia Kuznetsov is a Senior Postdoctoral Researcher at the Ubiquitous Knowledge Processing Lab (UKP Lab) of the Technical University of Darmstadt. He coordinates the InterText group, focusing on cross-document NLP and AI-assisted peer review systems. His research emphasizes responsible AI, human-AI collaboration, and empirical approaches to AI evaluation. He co-leads the "Ethics for Natural Language Processing" course at TU Darmstadt and has advised numerous students in PhD and master’s programs. Education includes a Candidate of Sciences (Mathematical and Applied Linguistics) from Lomonosov Moscow State University and work at the Higher School of Economics, Russia. His PhD at TU Darmstadt explored "The Role of Linguistics in Probing Task Design" . Research interests span peer review automation, cross-document modeling, and interpretable NLP. Key projects include NLPeer (a peer review resource) and CARE (a collaborative AI-assisted reading environment). Recent work focuses on large-language model applications in citation generation and task design. Publications emphasize peer review analysis, document structure modeling, and probing tasks. He actively collaborates on interdisciplinary projects addressing AI ethics and scholarly communication challenges.
Dr. Wenbin Li is a Senior Lecturer (Associate Professor) in Robotics at the University of Bath's Department of Computer Science. He leads the Pering Laboratory (Perceptual Intelligence Laboratory), affiliated with the AI & Machine Learning and Visual Computing groups. Previously, he held postdoctoral positions at Imperial College London (2016-2018) and UCL (2014-2016), and earned his PhD from the University of Bath in 2013, with earlier degrees from Imperial College London (MSc, 2009) and Xidian University (B.Eng, 2008). His research focuses on unified autonomous systems, including multi-sensory localization/mapping, dynamic motion capture, and uncontrolled scene understanding with applications in manufacturing and professional capture. Key areas include Robotics, Computer Vision, Graphics, and Machine Learning. He actively supervises doctoral students in these fields and has funded PhD openings. Dr. Li has been involved in major initiatives such as the My World - Strength in Places Fund (2021–2027), SLAM with Reinforcement Learning (2022–2023), and the CAMERA MC2 Award (2019–2023). His work aligns with UN Sustainable Development Goals, particularly in advancing technology for societal benefit. Recent publications emphasize aerial robotics, autonomous systems, and computer vision applications, including UAV package delivery reviews, Bayesian optimization for balloon station-keeping, and generative models for intrinsic image decomposition.
Professor Matt Bower is a leading academic in educational technology at Macquarie University's School of Education. Specialising in technology-enhanced learning, his work explores AI, AR, VR, and other tools to improve cognitive and collaborative learning. He has published over 100 peer-reviewed articles, led over 30 funded projects (totaling $3M+), and advised educational policymakers. His research spans teacher education, computing education, and learning design frameworks. Notable contributions include the Design of Technology-Enhanced Learning textbook (2018 AECT Award winner) and leadership in the Australian Technologies Teacher Educators Network (2019–2024). Research interests include AI in education, blended synchronous learning, and the impact of emerging technologies like wearable devices and generative AI on pedagogy. He collaborates with industry and education sectors to develop innovative learning solutions. Awards include the 2021 Australian Teaching Excellence Award and multiple Macquarie Vice-Chancellor awards. Current projects focus on screen use in education, teacher attitudes toward AI, and post-pandemic learning strategies. Professional activities include roles on ACARA’s Technologies Panel and NSW Educational Standards Authority committees. His work bridges research and practice, emphasizing teacher training and policy engagement. Projects like the ChatGPT survey and analyses of remote learning during the pandemic highlight his focus on real-world educational challenges.
Dr. Pamela Carreno-Medrano is a Lecturer and Early Career Research Representative in the Department of Electrical and Computer Systems Engineering at Monash University. Her research focuses on Human-Robot Interaction (HRI), robot learning, and socially assistive robotics. She holds a PhD in Information & Communication Sciences (Université de Bretagne-Sud), Master's in Computer Science (École Nationale d’Ingénieurs de Brest), and a Bachelor's in Computer Systems Engineering (Universidad EAFIT). Her work emphasizes human-centered design for intelligent systems, including adaptive navigation algorithms, human-robot collaboration models, and affective computing applications. She leads projects on long-term human-robot interaction and has contributed to interdisciplinary studies on robot ethics and public space integration. Dr. Carreno-Medrano also serves as an Adjunct Lecturer at Universidad EAFIT and collaborates internationally on sustainable aging technologies through the ARC Training Centre for Optimal Ageing. Current research themes include aligning task representations between humans and robots, modeling non-goal-driven human behaviors, and socially aware navigation strategies. She actively supervises postgraduate students in HRI, offering projects on interactive robot learning and embodied AI systems.
Marianne Bradford is a Professor of Accounting at the Department of Accounting, North Carolina State University, within the Poole College of Management. She holds a Ph.D. in Accounting from the University of Tennessee (2001). Her research focuses on Enterprise Resource Planning (ERP) systems, data security and classification, audit technology, and sustainability reporting. She has contributed to studies such as 'The Critical First Step to Data Security' (2021), emphasizing the role of management accountants in defining security KPIs, and has been recognized with the Best Education Paper Award (2010). Her academic work spans ERP implementation strategies, robotic process automation governance, and the application of AI tools like ChatGPT in accounting education. She collaborates with organizations like SAP, integrating ERP modules into curricula, and has advised on ERP post-implementation maintenance and identity access management. Her engagement with industry challenges includes analyzing barriers to generalized audit software adoption and exploring stakeholder expectations in sustainability reporting. Bradford is affiliated with the Business Analytics and AI Initiative (BAI) and contributes to the Poole College's thought leadership through publications in the ISACA Journal and articles in Strategic Finance. Her teaching emphasizes ERP systems and process mapping, reflecting her commitment to bridging academic research with practical business solutions.
Garth V. Crosby is an Associate Professor at Texas A&M University's Department of Engineering Technology and Industrial Distribution within the College of Engineering. He is also affiliated with the Multidisciplinary Engineering program. His research focuses on IoT and IIoT security, cyber-physical systems, and STEM education innovation. Crosby holds a Ph.D. in Electrical Engineering from Florida International University (2007), an M.S. in Computer Engineering, and a B.S. in Electronics (Applied Physics) from the University of the West Indies. His work spans cybersecurity frameworks for emerging technologies, including blockchain-based federated learning, post-quantum cryptography, and IoT threat mitigation. He has contributed to educational advancements through online lab design and faculty efficacy studies in hybrid learning environments. Crosby's recent publications emphasize securing robotic IoT systems, supply chain blockchain applications, and ransomware evasion techniques using generative AI. His research portfolio includes over 40 peer-reviewed articles in journals like IEEE Transactions and conferences such as ASEE and FiCloud. Key themes include volunteer cloud reliability models (ProTrust), edge computing security, and educational technology evaluation. Crosby's interdisciplinary approach bridges engineering systems with pedagogical innovation, addressing both technical and human factors in modern technological challenges.
Peter Kedron is an Associate Professor in the Department of Geography at the University of California, Santa Barbara (UCSB), and a member of the Center for Spatial Data Science. Previously, he held faculty positions at Arizona State University (2018–2023), Oklahoma State University (2016–2018), and Ryerson University (2012–2016). He earned his Ph.D. in Geography from SUNY Buffalo, an MA in Economics from the University of Michigan, and BAs in Economics and Psychology from SUNY Buffalo. His research focuses on spatial analytical methods, particularly replication in geographic research, and improving evidence accumulation through statistical approaches. Key areas include computational reproducibility, spatial causal inference, and the integration of replication into GIScience education. He has published over 55 peer-reviewed articles and been consistently funded by the National Science Foundation (NSF). Dr. Kedron emphasizes bridging spatial data science with policy relevance, addressing challenges in urban inequality, environmental conservation, and healthcare accessibility. His work often employs cutting-edge techniques like digital twins, machine learning, and multi-source remote sensing to address complex spatial problems. He has supervised over 20 graduate students and post-doctoral scholars, fostering a collaborative environment. Notable contributions include frameworks for reproducible geospatial research and studies on urban-rural disparities, wildfire risk, and renewable energy sector dynamics. Labs/Teams: Active in UCSB’s Center for Spatial Data Science and collaborates with interdisciplinary teams on projects funded by NSF and industry partnerships.
Xavier Ochoa is an Assistant Professor of Learning Analytics and Doctoral Program Coordinator at the Steinhardt School of Culture, Education, and Human Development, New York University. He holds a Ph.D. in Engineering (Computer Sciences) from the University of Leuven, Belgium (2008), an M.Sc. in Applied Computer Sciences from Vrije Universiteit Brussels (2002), and a B.S. in Computer Science from ESPOL, Ecuador (2000). His research focuses on Multimodal Learning Analytics, blending AI, sensors, and educational practices to enhance learning environments. He leads the Augment-Ed research group and has held roles such as Vice-President of SoLAR and Editor-in-Chief of the Journal of Learning Analytics. His academic career includes over a decade at ESPOL, where he directed the Information Technology Center and TEA research group. Awards include Best Researcher (2012, 2018), Best Professor (2013), and IEEE’s Best Researcher in Computer Science (2014). His work emphasizes tools for self-reflection, decision-making, and 21st-century skill development in education. Education: Ph.D. (2008, KU Leuven), M.Sc. (2002, VUB), B.S. (2000, ESPOL) Labs/Teams: Augment-Ed Research Group, Former Lead of TEA Group Key Contributions: RAP system for oral presentation feedback, OpenOPAF open-source tool, CrossMMLA initiatives Xavier’s research bridges education and technology, with publications in journals like the Journal of Learning Analytics and conferences such as LAK. His work addresses challenges in collaborative learning, feedback systems, and scalability of learning analytics tools.
Ruth Breu is a Full Professor and Dean of the Faculty of Mathematics, Computer Science and Physics at the Universität Innsbruck, where she also leads the Quality Engineering research group. She has been a key figure in the Department of Computer Science since 2002 and served as its Head from 2013 to 2024. Her academic journey began with a PhD summa cum laude from the University of Passau in 1991, followed by a habilitation at the Technical University of Munich in 1999. Her research interests include: Quality Engineering Model and Security Engineering Requirements and Software Development Processes Enterprise Architecture Management Threat Intelligence and Digital Twins Her recent publications reflect a strong focus on model-based systems, automated programming assessment, security engineering, and digital twins in construction and energy systems. She frequently collaborates with researchers such as Michael Felderer, Clemens Sauerwein, and Philipp Zech, contributing to advancements in software testing, threat intelligence sharing, and cyber-physical systems. Notable awards include her PhD awarded summa cum laude. She has also been actively involved in national research governance, serving on the board of the Austrian Science Fund (FWF) from 2011 to 2020. She co-founded Txture GmbH in 2017 and holds advisory roles at Universität Passau and FH OST. Ruth Breu advises several students and leads a vibrant research group. Her leadership extends to organizing workshops and contributing to major conferences in software engineering and enterprise modeling. She is deeply engaged in both academic and applied research, bridging theory and practice in IT quality and security.
Francesco Regazzoni is a Senior Researcher at the Faculty of Informatics, Università della Svizzera italiana (USI), and affiliated with the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). His work bridges embedded systems, cybersecurity, and artificial intelligence, with a focus on securing hardware and cyber-physical systems. Research Interests: His expertise spans embedded and cyber-physical systems security, side-channel attacks, post-quantum cryptography, hardware trojans, random number generators, and the security of AI and approximate computing. He also contributes to hardware/software co-design and operating systems security. The analysis of his recent publications reveals a consistent focus on hardware and system-level security , particularly in resource-constrained environments like IoT and embedded devices. His work integrates machine learning for attack detection and applies formal methods to ensure trust in hardware. A growing emphasis is placed on securing AI systems from physical and adversarial threats. Scientific Contributions: Over 100 peer-reviewed publications One book and one patent Extensive international collaboration (Belgium, Netherlands, USA, Switzerland, Singapore) Advising and Grants: While specific advisees and grants are not listed, his leadership in funded research projects and involvement with ALaRI and IDSIA suggest active mentorship and project coordination. His work has been supported by industry (e.g., ST Microelectronics, HP), the Swiss National Foundation, and the European Union. Labs and Teams: He is part of the Graph Machine Learning Group (GMLG) at IDSIA, which evolved from the Advanced Learning and Research Institute (ALaRI). This group focuses on graph machine learning, reinforcement learning, and dynamical systems, particularly in non-stationary environments.
Overview Prof. Gudrun Klinker is a Professor at Technische Universität München (TUM), leading the Chair of Computer Science Applications in Medicine & Augmented Reality. She holds a PhD from Carnegie-Mellon University and has extensive experience in academia and industry, including roles at Digital Equipment Corporation and Fraunhofer Institute. Affiliations Professor (C3/W2) since 2000 Head of the FAR (Augmented Reality) research group Member of the CAMP (Computer Aided Medical Procedures) interdisciplinary team Research Dr. Klinker specializes in augmented reality (AR) with focuses on industrial applications, sensor fusion, 3D interaction, and healthcare integration. Her work bridges computer science with medical and industrial challenges, emphasizing user-centric design and real-world deployment. Key projects include: AR-based maintenance systems for complex machinery Healthcare applications like serious games for nutrition education VR/AR training environments for medical and aerospace domains Awards and Recognition Robert Sauer Prize (2010) for contributions to Bavarian science ISMAR Lasting Impact Award (2014) for influential AR research Teaching and Mentorship Prof. Klinker teaches courses on 3D user interfaces, AR fundamentals, and game design. She advises students in thesis projects, focusing on AR applications, HCI, and medical computing. Labs and Collaborations Her research is supported by partnerships with industry and institutions, leveraging TUM's interdisciplinary environment to advance AR/VR systems for real-world impact.
Bestoun S. Ahmed Al-Beywanee is a Professor in AI and Software Engineering at the Department of Mathematics and Computer Science, Karlstad University, Sweden. He joined the university as a Senior Lecturer in 2019, was promoted to Associate Professor in 2020, and to Professor in 2023. His roles include teaching advanced courses such as AI Engineering, Automated Software Engineering, and Software Testing Fundamentals. His research focuses on software quality assurance, trustworthy AI systems, and MLOps, with a strong emphasis on combinatorial testing, IoT systems, and applied optimization techniques. Education: BSc (Electrical and Electronic Engineering, University of Salahaddin-Erbil, 2004); MSc (University Putra Malaysia, 2009); PhD (Software Engineering, University Sains Malaysia, 2012). Postdoctoral research at the Swiss AI Lab IDSIA (2015) and positions at Salahaddin University and Czech Technical University further enriched his expertise. Research interests span Quality Assurance of machine learning systems, software testing methodologies, trustworthy AI, IoT system reliability, and optimization algorithms. He has pioneered frameworks like PatrIoT for IoT testing and contributed to MLOps robustness. His work integrates machine learning with anomaly detection, adaptive systems, and industrial applications. Recent articles highlight advancements in data-driven heat pump management, MLOps robustness, and edge-cloud AR/VR optimization. Collaborations include projects on digital twins, smart manufacturing, and industrial IoT. His contributions bridge theoretical research with practical industrial solutions, emphasizing system reliability and AI ethics.
