Martin Mozina serves as an Assistant Professor and Researcher at the Faculty of Computer and Information Science, University of Ljubljana, where he has been affiliated with the Artificial Intelligence Laboratory since 2004. His primary institutional role focuses on advancing machine learning methodologies integrated with domain knowledge. His research centers on developing machine learning algorithms that incorporate prior knowledge alongside training data, with significant contributions to model visualization through nomograms and automated chess position analysis. Key innovations include argument-based machine learning frameworks and techniques for resolving knowledge acquisition bottlenecks in intelligent systems. Analysis of his 2004-2009 publications reveals consistent emphasis on interpretable AI, combining symbolic reasoning with statistical learning. His work bridges theoretical machine learning with practical applications in medical diagnostics, game AI, and decision support systems, particularly through nomogram-based classifier visualization and chess tutoring systems. He actively participates in major research initiatives including: DRIFT (L2-4436): Real-time optimization of low-voltage networks using deep incentivized learning (2022-2025) Umetna inteligenca in inteligentni sistemi: Agency-funded AI research program (2015-2020) Strojno učenje v gradnji inteligentnih sistemov: Machine learning for intelligent tutoring systems (2011-2014, 2013-2014) Molecular markers for lung cancer research (2011-2014, 2016-2018) X-MEDIA: Large-scale knowledge sharing across media (EU project, 2006-2009) Mozina's work within the Artificial Intelligence Laboratory demonstrates sustained focus on making machine learning more transparent and applicable to complex real-world problems through hybrid symbolic-statistical approaches.
Abhraneel Sarma is a PhD candidate in Computer Science at Northwestern University, advised by Professors Matthew Kay and Jessica Hullman. His research focuses on addressing uncertainty in data analysis through tools like multiverse (an R package for sensitivity analysis) and Milliways (a visualization system for multiverse analysis validation). Uncertainty visualization Multiverse analysis Bayesian inference Reproducibility in research His work combines empirical studies and system development to improve data-driven decision-making. Publications include best paper awards at CHI 2019 and honorable mentions at CHI 2024, CHI 2023, and VIS 2022. 2025 : CHI 2024 : CHI (Best Paper Honorable Mention) 2023 : CHI (Best Paper Honorable Mention) 2022 : VIS (Best Paper Honorable Mention) 2019 : CHI (Best Paper Award) Email: abhraneel@u.northwestern.edu
Dr. Robyn Tamblyn is a Professor in the Department of Medicine, Division of Clinical Epidemiology at McGill University's Faculty of Medicine and Health Sciences. She serves as a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) within the Cardiovascular Health Across the Lifespan Program and the Centre for Outcomes Research and Evaluation (CORE). Dr. Tamblyn's research focuses on conducting observational and interventional studies in public health and health services delivery aimed at improving healthcare safety and quality. Her work centers on identifying modifiable determinants of adverse events and improved health outcomes through analysis of large linked clinical and administrative databases. She leads a research team that develops and evaluates computer-enabled interventions to address modifiable risk factors, including computerized decision-support systems, personal health record portals, self-management tools, and automated surveillance systems. Analysis of Dr. Tamblyn's publication record reveals a strong emphasis on medication safety, pharmacoepidemiology, and healthcare informatics. Her research spans multiple domains including medication adherence, inappropriate prescribing, deprescribing interventions, medication reconciliation, and the use of electronic health records for pharmacosurveillance. A notable trend in her work is the development and evaluation of technology-enabled interventions to improve medication management and reduce adverse drug events across various healthcare settings. As a Senior Scientist at RI-MUHC, Dr. Tamblyn leads research initiatives within the Centre for Outcomes Research and Evaluation, focusing on healthcare quality improvement and patient safety. Her work bridges clinical medicine, epidemiology, and health informatics to address critical gaps in healthcare delivery systems. She collaborates extensively with clinicians, pharmacists, and health services researchers to implement evidence-based interventions that directly impact patient care.
Dominic Henze is a Professor at the Technical University of Munich (TUM), affiliated with the Faculty of Informatics and the Chair of Software Engineering . He leads research initiatives in Cyber-Physical Systems , Smart Environments , and Machine Learning Applications , with a particular focus on Fog Computing architectures. His research spans theoretical frameworks and real-world implementations, including collaborations with institutions like Carnegie Mellon University and industry partners such as Siemens AG and Zeiss IMT . His work addresses challenges in resource allocation , predictive maintenance , and blockchain integration within industrial contexts. Dr. Henze's publications reveal a consistent focus on Fog Computing architectures, IoT resource management, and educational software engineering. Key trends include self-organizing network systems , decentralized supply chain traceability , and smart environment coordination . He has advised numerous students on topics ranging from QoS negotiation to autonomous drone coordination . As an educator, he has taught multiple iPraktikum courses and seminars on iOS development and Agile Project Management since 2014, with publications exploring team composition strategies and distributed programming pedagogy.
Ruzica Piskac is a Professor of Computer Science at Yale University, where she leads the Rigorous Software Engineering (ROSE) group. She has made significant contributions to the fields of software verification, security, automated reasoning, and code synthesis, focusing on improving software reliability and trustworthiness through formal techniques. Dr. Piskac received her PhD from the Swiss Federal Institute of Technology (EPFL) in 2011, where her dissertation won the Patrick Denantes Prize. Prior to joining Yale, she led an independent research group at the Max Planck Institute for Software Systems in Germany (2012-2013). Her research spans several key areas: symbolic execution for Haskell (G2), privacy-preserving formal methods (PPFM), functional reactive synthesis, verification of configuration files, and analysis of software updates. Her work consistently bridges theoretical formal methods with practical applications in real-world systems. Dr. Piskac's recent publications demonstrate a strong trend toward applying formal verification techniques to emerging challenges including large language models, quantum computing security, legal accountability of automated systems, and cyber-physical systems. Her research increasingly intersects with AI, cryptography, and legal domains while maintaining strong foundations in formal methods. Her scientific achievements have been recognized with numerous prestigious awards: Multiple Amazon Research Awards Yale University's Ackerman Award for Teaching and Mentoring Facebook Communications and Networking Award Microsoft Research Award for the Software Engineering Innovation Foundation (SEIF) Patrick Denantes Prize for her PhD dissertation Dr. Piskac has graduated five PhD students, four of whom have gone on to become assistant professors of computer science. She has served as Program Chair of the 37th International Conference on Computer Aided Verification and is on the Steering Committee of the Formal Methods in Computer-Aided Design conference. She leads the Rigorous Software Engineering (ROSE) group at Yale, which focuses on several key projects including: Symbolic Execution Engine for Haskell (G2) Privacy Preserving Formal Methods (PPFM) Functional Reactive Synthesis Verifications for Configuration Files Analysis of Software Updates and Configuration Files
Dr. Mustafa Demir serves as an Associate Research Scientist at Arizona State University's Biodesign Center for Applied Structural Discovery and Faculty Associate in the Ira A. Fulton Schools of Engineering. His interdisciplinary work integrates cognitive science and engineering to optimize human-AI collaborative systems across healthcare, transportation, and defense domains through human-centered design principles. Education: Ph.D. in Simulation, Modeling, and Applied Cognitive Science, Arizona State University (2017) Dr. Demir's research centers on human-machine teaming dynamics, employing advanced statistical and nonlinear dynamical systems modeling. His expertise includes quantum cognitive approaches to decision-making, team cognition analysis, and machine learning applications for real-time physiological monitoring. Current projects focus on AI-powered stress management tools, curiosity-driven STEM education systems, and human-autonomy coordination in driving and command environments using eye-tracking and biometric sensing. Analysis of his 2023-2025 publications reveals methodological innovation in dynamical systems analysis (DSA Toolbox) and quantum probability modeling applied to trust calibration in autonomous vehicles, educational technology, and digital health interventions. His work consistently bridges theoretical modeling with real-world implementation in complex sociotechnical systems. Dr. Demir mentors students in cognitive engineering and applied data science while leading multi-institutional research initiatives funded by NSF, AFRL, and DARPA. His grant portfolio supports experimental work across simulated and operational environments including remotely piloted aircraft systems and urban search-and-rescue scenarios. He contributes to the Biodesign Center for Applied Structural Discovery and HLA-Inception research group, developing computational models of team interaction and adaptive AI systems for healthcare and education applications.
Martina Lindorfer serves as a tenure-track Assistant Professor at TU Wien since 2018 and is a key researcher at SBA Research, Austria's largest dedicated information security research center. Her academic foundation includes a PhD from TU Wien (2016) followed by a two-year postdoctoral position at the University of California, Santa Barbara. Her research centers on applied systems security and privacy, specializing in automated static and dynamic analysis techniques for large-scale application evaluation targeting malicious behavior, security flaws, and privacy violations. Building on extensive malware analysis expertise, she currently pioneers mobile app analysis frameworks to enforce transparency in private data handling and sharing practices, uncovering novel privacy breaches through innovative tooling. Her exceptional contributions have earned recognition through: ERCIM Cor Baayen Young Researcher Award ACM CyberW Early Career Award for Women in Cybersecurity Research Hedy Lamarr Award from the City of Vienna Through her dual role at TU Wien and SBA Research, she drives critical advancements in security transparency while mentoring emerging researchers in the field.
Dr. Chetan Arora is a Senior Lecturer in Software Engineering at Deakin University's School of Information Technology, part of the Faculty of Science Engineering and Built Environment. He holds a PhD from the University of Luxembourg where he received the best PhD thesis award in the ICT domain. His research focuses on applied Artificial Intelligence in Software Engineering, with particular emphasis on Empirical Software Engineering, Requirements Engineering, and Applied Natural Language Processing. PhD in Computer Science from University of Luxembourg Masters in Software Engineering from Technische Universitat Kaiserslautern (Germany) Bachelors in Engineering (CS) from Thapar University (India) Arora's research interests center on the intersection of AI and Software Engineering, particularly how machine learning and natural language processing can enhance software development processes. His work explores requirements engineering, test automation, software trustworthiness, and human-centric software development. He investigates how large language models can be effectively deployed for tasks like test case generation, requirements analysis, and traceability. His recent publications reveal a strong focus on practical applications of AI in software engineering, with numerous studies examining the real-world implementation challenges and benefits. His publication record shows significant activity in top software engineering venues, with a notable emphasis on AI applications in software engineering processes. His recent work demonstrates expertise in retrieval-augmented generation systems, requirements-driven testing, and human-centric software development approaches. The publications collectively highlight his focus on bridging theoretical AI advancements with practical software engineering challenges. Best Ph.D. thesis award in the ICT domain at University of Luxembourg Arora actively supervises doctoral students working on cutting-edge topics including satellite communication systems, extended reality applications, and human-centered AI requirements engineering. His industry collaborations include work with Department of Defence on projects like Contextually Situated Anomaly Detection and Planning and Optimisation of Resources in Defence Satellite Communication Systems. He previously worked at SES Satellites on applied AI for IoT and Satcom, and as an FNR-PPP research fellow at the University of Luxembourg in software quality assurance. His laboratory work focuses on developing practical AI solutions for software engineering challenges, particularly in requirements engineering and test automation. Current projects involve multi-orbit satellite constellation optimization, dynamic radio resource management, and extended reality enabled human-centric requirements engineering.
Hoa Khanh Dam is Professor and Deputy Head of School (Research) & Head of Postgraduate Studies in the School of Computing and Information Technology at the University of Wollongong, Australia. He serves as Co-Director of the Decision System Lab where he leads research at the intersection of Software Engineering and Artificial Intelligence. His research focuses on developing AI-driven solutions for software quality, cybersecurity, and productivity enhancement. Key interest areas include: AI/IoT autonomous and cyber resilient systems Software Analytics and Mining Software Repositories Large Language Models for software engineering tasks Defect prediction and vulnerability analysis Agile project management optimization Analysis of Dam's 12 publications from 2018-2025 reveals consistent application of machine learning to software engineering challenges. His work shows progressive evolution from traditional ML techniques toward LLM-based frameworks, with major contributions in defect prediction (DeepJIT), vulnerability analysis, microservice recommendation, and agile effort estimation. The research demonstrates strong industry relevance through practical implementations in code review, component prediction, and security systems. Dam co-leads the Decision System Lab at UOW, which develops intelligent decision support systems using AI and data analytics. The lab's work bridges theoretical AI advancements with real-world software engineering applications, particularly in cybersecurity and autonomous systems development.
Taha Mansouri is a Lecturer in Artificial Intelligence at the University of Salford's School of Science, Engineering & Environment. He leads the High Performance Computing facilities within the school and chairs the Salford AI Club, an inclusive community focused on AI applications in Higher Education. Mansouri holds dual PhDs - one in Artificial Intelligence and Deep Learning from the University of Salford and another in Information Technology Management from Allameh Tabataba'i University in Iran. His research interests span multiple critical areas in modern AI development, with particular emphasis on ethical considerations in AI systems. Mansouri actively investigates fairness, explainability, and transparency in AI algorithms, with specific focus on computer vision systems and large language models. His work addresses bias in facial emotion detection across age, gender, ethnicity, and cultural backgrounds, highlighting important concerns about equity in automated systems. Mansouri's recent publications demonstrate a strong trend toward practical applications of AI for social good, including detecting mold in social housing, ethical compliance in legal AI systems, and developing AI-resilient assessment tools for education. His research bridges theoretical AI development with real-world implementation challenges across healthcare, education, and industrial applications. Fellowship of the Higher Education Academy Senior Fellowship of the Higher Education Academy Mansouri actively supervises multiple PhD students working on diverse AI applications and leads significant research projects including the £500,000 Innovate UK Smart Grant-funded Expert Legal Intelligence (ELI) project. He serves on prestigious review panels including the EPSRC Peer Review College, the EDI Hub+ Flexible Fund Peer Review College, and the British Council's International Science Partnerships Fund Review College. His grant portfolio includes projects on ethical ASR models (£30,000 collaboration), WATCH-AI benchmarking tools, and inclusive AI emotion recognition systems. As leader of the High Performance Computing facilities, Mansouri supports interdisciplinary research across the university. He also chairs the Salford AI Club, fostering collaboration among individuals from diverse backgrounds interested in AI applications, particularly in Higher Education.
Dr. Siobahn Day Grady is an Assistant Professor of Information Science/Systems at North Carolina Central University (NCCU) and serves as the Founding Director of the Institute for Artificial Intelligence and Emerging Research (IAIER), which she established in 2025. She also holds leadership roles as Co-Director of The Center fOr Data Equity (CODE), Program Director of the Information Science Program, and Faculty Fellow in the Office of Faculty and Professional Development. Dr. Grady reports to the Provost with oversight of a $1M+ annual budget and $3M+ grant portfolio, managing a staff of 5 plus advisory boards. Ph.D. in Computer Science, North Carolina Agricultural & Technical State University (2018) M.S. in Computer Science, North Carolina Agricultural & Technical State University (2018) M.S. in Information Science, North Carolina Central University (2009) B.S. in Computer Science, Winston-Salem State University (2005) Dr. Grady's research focuses on the ethical implementation of artificial intelligence, with particular emphasis on fairness, bias mitigation, and equity in AI systems. Her work bridges technical AI development with social justice considerations, especially in healthcare applications and educational contexts. She has pioneered initiatives to increase AI literacy at HBCUs and developed frameworks for operationalizing fairness in AI governance. Her research interests include natural language processing, machine learning applications for social good, digital literacy programs for marginalized communities, and strategies to increase diversity in STEM fields through her STEM-It-Yourself program. Analysis of Dr. Grady's recent publications reveals a strong trajectory toward practical applications of AI ethics in real-world settings, particularly in healthcare and education. Her work demonstrates a consistent focus on creating frameworks that translate theoretical AI ethics principles into actionable guidelines for practitioners. There's a clear progression from technical AI research toward more interdisciplinary work that bridges computer science with social sciences, nursing, and education. Her publications increasingly address the needs of underrepresented communities and focus on practical implementation strategies rather than purely theoretical contributions. Winston-Salem State University 2023 Distinguished Alumni Award Durham Section of the National Council of Negro Women 2024 Distinguished Educator Sigma Iota Omega Chapter of Alpha Kappa Alpha Sorority, Incorporated® 2022 Soaring to Greater Heights in Science Technology Engineering Arts Mathematics Honoree The Links, Inc., Raleigh (NC) Chapter 2022 Emerald Award Honoree Association for Educational Communications and Technology (AECT) Culture, Learning, and Technology (CLT) Division 2023 Outstanding Publication Award Dr. Grady has secured significant grant funding totaling over $3 million, including a $1 million Google.org investment, $100K+ from Cisco, $15K from FICO, and funding from NTIA and NIH. She serves as Principal Investigator for the Digital Equity Leadership Program (DELP) and the Genomic Research and Data Science Center for Computation and Cloud Computing (GRADS-4C). Her mentoring extends to numerous students through programs like STEM-It-Yourself, which focuses on cultivating STEM identity among adolescent girls. Dr. Grady has established three endowed scholarships supporting economically disadvantaged students at multiple HBCUs, demonstrating her commitment to educational access. As Founding Director of the Institute for Artificial Intelligence and Emerging Research (IAIER), Dr. Grady leads North Carolina Central University's strategic vision for AI education, research, and policy. The institute includes the AI Emerging Scholars and Leaders Programs, which engage students, faculty, and staff in cross-disciplinary AI innovation. She has developed NCCU's first AI minor (pending approval) and serves as co-facilitator for the UNC AI Faculty Learning Community. Dr. Grady also holds leadership positions on the Governor's AI Council and multiple advisory boards, positioning NCCU as a national leader in responsible AI development and implementation.
Matthias Stürmer serves as a Professor at Bern University of Applied Sciences (BFH) within the School of Management and Head of the Institute for Public Sector Transformation (IPST). He concurrently holds a lecturer position at the University of Bern. His professional identity centers on Swiss digital governance initiatives, with active leadership roles in @Parldigi, @DigitalImpactCH, @CH_Open, and @OpendataCH advocating for open source, open data, and transparent public sector innovation. His research program bridges legal technology and digital governance, specializing in multilingual (German/French/Italian) processing of Swiss jurisprudence. Core focus areas include developing AI systems for judicial summarization and criticality prediction, advancing digital sovereignty frameworks, and analyzing sustainable public procurement practices. He investigates the tension between open justice principles and privacy preservation in court documentation, while pioneering methods for anonymizing legal texts against re-identification threats from large language models. Stürmer's publication trajectory reveals a strategic shift toward legal AI applications since 2020, with 12 of his 15 most recent works addressing multilingual legal processing challenges. His scholarship consistently targets Swiss institutional contexts, creating specialized datasets like Multilegalpile and Lextreme while examining practical implementation barriers for open source adoption in public administration. As director of IPST at BFH, he leads institutional efforts to transform public sector services through open standards and collaborative governance models. His team develops practical frameworks for digital sovereignty implementation and sustainable ICT procurement, directly influencing Swiss federal policies on open data and public sector technology adoption.
Prof. Jannis Angelis is a Visiting Professor at ISM and a Docent/Reader in Operations Strategy at Indek. Previously, he held roles at Cambridge Judge Business School, Warwick, and Stockholm, and served as a country champion for teaching excellence at Oxford University’s education society. His academic journey includes a PhD in operations management from Cambridge, MPhil in political economy (Cambridge), MA in China studies from SOAS, and an MSc in international relations from Stockholm. His research focuses on the intersection of technology and management, exploring areas such as blockchain applications in supply chains, circular economy strategies for EV batteries, and digital transformation in manufacturing. Notable contributions include studies on blockchain in food supply chains, DLT ecosystems, and lean operational excellence, as evidenced by his receipt of the Shingo Prize and Skinner/Voss best paper awards. Angelis has supervised 9 PhDs and 400 student projects, secured €1.4m in grants, and led major research initiatives. His professional experience spans roles at the ILO, venture capital firms, and international consultancies like ITC (WTO/UNCTAD). He currently leads research at the Gunilla Bradley Centre and IFN Research Institute, focusing on digitalization and operational excellence. Teaching Awards: Four teaching awards, including recognition for pedagogical innovation. Research Grants: Over €1.4m secured, with leadership in three major projects. Labs/Teams: Active in the Gunilla Bradley Centre (Digitalisation) and IFN Research Institute (Industrial Economics).
Albert Gatt is a Professor of Natural Language Processing at Utrecht University's Department of Information and Computing Sciences, where he also serves as Programme Director for AI & Data Science. He holds an Associate Professor position (on leave) at the University of Malta's Institute of Linguistics and Language Technology. His research focuses on Natural Language Generation (NLG), multimodal models, and under-resourced language support, particularly for Maltese. He leads projects like NL4XAI and MASRI, addressing challenges in explainable AI and speech recognition. Education: Advanced degrees in computational linguistics and AI (not explicitly detailed in text). Key Projects: Multilingual NLG, Vision-Language benchmarks, Maltese ASR, and NLP evaluation methodologies. Research interests span data-to-text generation, vision-language interfaces, and evaluation practices. His work bridges computational linguistics with cognitive science, emphasizing human-AI collaboration. Notable contributions include the TUNA corpus, SimpleNLG toolkit, and foundational studies on referring expression generation. Publications (2025-2024) explore robust fine-tuning, LLM evaluation, and visual-linguistic grounding. Collaborations span academia and industry, addressing ethical AI and language equity. Supervises a global team of researchers and PhD students across multiple institutions, fostering innovation in NLG, multimodal AI, and Maltese language tech.
Rashida Richardson is an Assistant Professor of Law and Political Science at Northeastern University’s College of Social Sciences and Humanities (CSSH). She specializes in the intersections of race, emerging technologies, and law, focusing on the social and civil rights implications of data-driven systems like AI. Her work addresses government surveillance, algorithmic discrimination, and regulatory strategies to ensure equitable technology use. Education: B.A. with Honors in College of Social Studies (interdisciplinary major: Economics, Government, History, Social Theory) from Wesleyan University (2008) J.D. from Northeastern University School of Law (2011) Research Interests: Dr. Richardson examines how data-driven technologies perpetuate racial and social inequities through projects like Suspect Development Systems and Racial Segregation and the Data-Driven Society . She advocates for policies that ensure accountability in algorithmic systems and equitable data practices. Key Awards: Reidenberg-Kerr Award (2021) Schmidt Futures International Strategy Forum Fellow (2021) Wired Magazine’s 32 Innovators (2020) Grants & Fellowships: German Marshall Fund Senior Fellowship (2020–present) Open Society Foundation Research Grant (2020–2021) Ford Foundation, MacArthur Foundation, and Annie E. Casey Foundation grants (2020–2021) Teaching: Teaches POLS 3323: Race, Inequality, and the Law, integrating her research on technology and civil rights into undergraduate education.
