جست‌وجوی استاد و پژوهشگر

Keng-Chi Changمشاهده پروفایل

استادیار

• Computational Social Science
• Political Methodology
• Digital Politics
• +۵ مورد دیگر

Keng-Chi Chang serves as Assistant Professor in Quantitative Social Science within Dartmouth College's Faculty of Arts and Sciences. His research program integrates artificial intelligence and computational methodologies to investigate critical questions about technology's impact on political systems and democratic processes, with particular focus on censorship circumvention mechanisms, visual media dynamics in online ecosystems, and algorithmic recommendation systems. Professor Chang's academic foundation spans multiple disciplines: PhD in Political Science with Specialization in Computational Social Science, University of California, San Diego MS in Computer Science, University of California, San Diego BA in Economics, National Taiwan University His research synthesizes computational social science with political methodology to address pressing questions about digital politics. Key investigations examine how citizens circumvent censorship during crises like COVID-19, how visual content influences news credibility perceptions, and how social media chat environments alter political debate experiences. This work consistently bridges computer science innovation with social science theory through rigorous analysis of large-scale behavioral datasets. Recent publications reveal evolving methodological sophistication, progressing from social media election prediction models to advanced AI applications for neuron-level model explanations. His work spans political communication, computer vision, and causal inference, appearing in premier interdisciplinary venues including PNAS and top communication journals. Research support includes competitive awards: NSF/APSA Dissertation Research Fellowship Rapoport Family Foundation Fellowship As an emerging faculty member, Professor Chang builds his research program through active grant acquisition and interdisciplinary collaboration. His mentorship develops students' capabilities in computational methods while addressing substantive questions about technology's societal impacts. Though no formal lab structure is specified, his projects involve collaborative teams working at the computer science-social science interface.

• Environmental Geochemistry
• Inorganic Geochemistry
• Natural Resource Management
• +۳ مورد دیگر

Dr. Clare Miller serves as an Adjunct Researcher in Environmental Geochemistry at the CODES ARC Centre within the School of Natural Sciences at the University of Tasmania. Simultaneously, she works as a Senior Scientific Officer at the Environmental Protection Agency, Tasmania (EPA), where she focuses on the Savage River Rehabilitation Project - a unique joint arrangement between Government and Grange Resources aimed at reducing impacts of past mining at Savage River. Dr. Miller earned her PhD from Queen's University Canada in 2020 with research titled 'Arsenic mobility in a changing northern climate: Implications for geochemical baselines and long-term stability of contaminants in lake systems.' Her undergraduate studies also took place at Queen's University Canada, where she completed a BScH in 2013 with research on 'Removal of arsenic trioxide from a simulated human gastrointestinal system through adsorption onto Fe-oxides.' Dr. Miller's research spans three primary areas: (1) informing remediation activities at legacy mine sites; (2) developing innovative strategies to mitigate mining impacts on environmental and community health; and (3) understanding climate change effects on mining activities, metal mobility, and baseline geochemical conditions. Through field-based sampling and microanalytical laboratory techniques, her work aims to minimize natural resource development impacts on ecosystems and human health. Her research often focuses on mineralogical controls on metal(loid) mobility in mine waste and environmental systems, with particular attention to arsenic behavior in changing environments. Analysis of Dr. Miller's publication record reveals a strong focus on environmental geochemistry with emphasis on mining impacts and climate change interactions. Her research consistently examines how contaminants move through ecosystems, particularly in northern environments, with special attention to arsenic mobility. Much of her work combines field-based sampling with advanced laboratory techniques to understand long-term contaminant stability. A significant portion of her recent publications addresses remediation strategies for legacy mine sites, particularly in Western Tasmania, demonstrating practical applications of her research. Beach Meadows Teaching Assistant Award, 2019 Greg Heath Teaching Assistant Award, 2018 Gord and Katherine Keep Teaching Assistant Award, 2017 Hemmera Teaching Assistant Award, 2017 Griff Murphy and Anny Raymond Teaching Assistant Award, 2016 Dr. Miller actively supervises doctoral students on projects related to mine waste characterization, remediation strategies, and geoenvironmental studies. She has secured substantial research funding through multiple consultancy and contract research projects, totaling over $500,000, primarily from the Department of State Growth (Tasmania) and Natural Resources Canada. Her funded projects focus on innovative solutions for mine rehabilitation, geoenvironmental characterization of mine wastes, and understanding climate change impacts on mining activities. Dr. Miller's teaching experience spans geoscience subject areas including geological field methods, earth systems engineering, hydrogeology, and engineering site investigation. Dr. Miller collaborates extensively through the CODES ARC Centre at the University of Tasmania and the Off-Campus Collaboration Network. Her work with indigenous communities in northern Canada during her graduate studies has informed her approach to community engagement in environmental research. At the EPA, she works within multidisciplinary teams focused on environmental protection and remediation projects, particularly the Savage River Rehabilitation Project which represents a significant government-industry partnership.

Michael Longمشاهده پروفایل

مدرس

• Geotechnical Engineering
• Environmental Engineering
• Sustainable Construction
• +۳ مورد دیگر

Dr. Michael Long is a Lecturer in the UCD School of Civil Engineering at University College Dublin, specializing in geotechnical engineering and sustainable ground improvement techniques. He is a key researcher in the Science Foundation Ireland (SFI) funded iCRAG center, focusing on bio- and enzyme-induced carbonate precipitation (MICP/ECIP) to strengthen granular soils while reducing carbon emissions. His work spans collaborations with Queen’s University Belfast, Arizona State University, Georgia Tech, and University of California, Davis. Research Interests: His projects address critical gaps in Ground improvement using eco-friendly methods Compliance with Eurocode 7 standards Utilization of calcite-bearing Irish sands Karst-related geotechnical challenges with implications for tunneling, coastal development, and urban infrastructure resilience. Collaborative Networks: Dr. Long works closely with geologists, chemists, and engineers across the UCD College of Engineering & Architecture, leveraging both laboratory-scale experiments and full-field trials to advance sustainable construction practices.

• Urban resilience
• Vacancy and underuse
• Town revitalization
• +۷ مورد دیگر

Dr. Philip Crowe is a Lecturer/Assistant Professor at University College Dublin's School of Architecture, Planning and Environmental Policy (APEP), where he also serves as Director of Research. He holds a joint appointment with the School of Civil Engineering and is actively involved in multiple research initiatives focused on urban resilience, climate action, and sustainable development. His academic leadership extends to roles as co-Director of the UCD Centre for Irish Towns and Programme Director of the MSc in Architecture, Urbanism and Climate Action. Dr. Crowe's educational background includes a Dip Arch and MA from the University of Edinburgh, an MSc in Applied Carbon Management from the University of Glasgow (2011), and a PhD from University College Dublin. His doctoral research explored urban resilience through the lens of Scottish polymath Patrick Geddes, connecting historical precedents with contemporary climate challenges. His research interests focus on how the built environment can respond to crises like climate change, biodiversity loss, and resource depletion. With over 25 years of experience in both professional practice and academic research, Dr. Crowe's work spans urban resilience frameworks, vacancy and underuse analysis, town revitalization strategies, and innovative citizen engagement methods. His recent publications reveal a strong emphasis on practical applications of resilience theory, particularly in the Irish context, with projects addressing housing challenges, water infrastructure, and adaptive reuse of buildings. Among his notable achievements is the Ripple project in Ballina, which became the first Irish project to receive a New European Bauhaus Award in the Reconnecting with Nature Champion Category. His TREBUChEt project addresses the adaptive reuse of buildings in Ireland's towns through circular economy principles. Dr. Crowe has also made significant contributions to understanding how coworking spaces can provide social, urban, and environmental co-benefits to Irish towns. College Level Teaching Excellence Award (2024) New European Bauhaus Award: Reconnecting with Nature Champion (2023) THRIVE Leadership in Research (2023) EIT Climate KIC Accelerator Programme (2017) THINKTECH Award (2016) Dr. Crowe actively mentors PhD students including Stephen Wall, Merlo Kelly, Sarah Cremin, and Miriam Lins, with research focusing on urban resilience, town revitalization, and sustainable architecture. His grant portfolio includes significant projects funded by the Environmental Protection Agency, European Regional Development Fund, and Science Foundation Ireland. Through the UCD Centre for Irish Towns and the Urban Institute of Ireland, he leads collaborative efforts to address Ireland's urban challenges while contributing to broader European initiatives like the HeritACT project and New European Bauhaus movement.

Sam Goreeمشاهده پروفایل

استادیار

• computer vision
• human-computer interaction
• digital humanities
• +۴ مورد دیگر

Sam Goree is an assistant professor of computer science at Stonehill College, specializing in the intersection of computer vision, human-computer interaction, and digital humanities. His work critically examines how AI systems evaluate aesthetic quality and human-centered aspects of AI, with particular focus on subjectivity in machine learning models and evaluation methodologies. PhD in Informatics from Indiana University's Luddy School of Informatics, Computing and Engineering Goree's research explores aesthetic phenomenon problems in computer vision, particularly image aesthetic quality assessment. He investigates how subjective human perceptions of beauty and aesthetics can be modeled and evaluated in AI systems, challenging traditional approaches that assume a universal standard of beauty. His work draws from feminist theory, philosophy of science, and media archaeology to develop more human-centered evaluation methods for AI systems. Goree is particularly interested in how subjectivity manifests in both data and models, and how this affects algorithmic bias. His recent publications reveal a strong trend toward human-centered evaluation of AI systems, with increasing focus on subjectivity, personalization, and philosophical foundations of aesthetics in computer vision. Goree's work bridges technical computer vision research with critical humanities perspectives, examining how historical contexts shape current AI practices. He has developed novel evaluation frameworks that incorporate qualitative human feedback, moving beyond traditional quantitative metrics to better understand how AI systems interact with human perception and values. Goree actively engages with teaching challenges in the era of generative AI, developing pedagogical approaches that help students develop critical thinking skills while navigating new AI tools. His teaching philosophy emphasizes maintaining human-centered learning experiences even as AI transforms educational landscapes. He advocates for assignments that require contextual understanding and creativity, which are difficult for AI to replicate. His research is organized around understanding the "aesthetic gap" - the difference between information extractable from image pixels and the feelings images evoke in humans. Goree's lab explores how to build more transparent and accountable AI systems that acknowledge their subjective nature rather than claiming false objectivity.

• Data Mining
• Machine Learning
• Text Summarization
• +۶ مورد دیگر

Mark Last is a Professor at Ben-Gurion University in Beersheba, Israel, with a distinguished career spanning over three decades in computer science research. His work primarily focuses on data mining, machine learning, and natural language processing applications. His research interests encompass stream data mining, text summarization, fuzzy logic systems, and classification algorithms. Last has made significant contributions to developing techniques for analyzing dynamic data streams, multilingual text processing, and applying machine learning to real-world problems in healthcare, social media analysis, and security informatics. His work often bridges theoretical advancements with practical applications, particularly in handling non-stationary data and developing interpretable models. Recent research trends show a continued focus on stream data analysis, with applications expanding into social media monitoring, healthcare prediction systems, and multilingual content analysis. His work demonstrates consistent innovation in adapting machine learning techniques to evolving data environments and practical challenges. Mark Last has maintained a prolific publication record with over 175 publications documented in DBLP, collaborating extensively with researchers including Abraham Kandel, Marina Litvak, and Oded Maimon. His work has been published in top venues including IEEE Access, Machine Learning journal, and Expert Systems with Applications.

Marie Purenمشاهده پروفایل

دانشیار

• History
• Digital Humanities
• Political Ideologies
• +۲ مورد دیگر

Marie Puren is an Associate Professor in history and digital humanities at EPITECH Paris , where she leads the Digital Methods for Humanities and Social Sciences (MNSHS) team since 2022. She also holds research affiliations with the LRE laboratory , Jean-Mabillon Center , and LARHRA in Lyon. Her work bridges historical analysis with computational techniques, focusing on political ideologies, cultural heritage preservation, and digital methodologies. Her research interests include: Digital Humanities and Computational History Political Ideologies in the French Third Republic Cultural Heritage Modeling Textual Analysis with NLP and XML-TEI History of Publishing and Literary Collaboration Marie contributes to major projects like AGODA (parliamentary debates analysis) and SILKNOW (silk heritage preservation). She teaches courses on digital methodologies, historical research, and environmental impacts of technology. Her leadership in Humanistica and participation in international conferences highlight her academic influence.

• Urban History
• Holocaust Studies
• Soviet History
• +۵ مورد دیگر

Eric Le Bourhis is a Lecturer at INALCO (Institut National des Langues et Civilisations Orientales) in the Europe department, where he also serves as Head of the Latvian course and Racism/Anti-Semitism advisor. His research focuses on urban history across Soviet Union, Latvia, and France, with particular emphasis on housing practices, Holocaust studies, and Baltic region history. Current affiliations: INALCO, Europe-Eurasia Research Center (CREE) Teaching areas: Baltic region history, Latvian grammar/culture, Holocaust history Research Interests include social history embedded in spatial analysis, with micro-historical approaches to housing spoliation in Paris (1940-1946), Soviet urban planning in Riga (1945-1990), and Holocaust-related urban dynamics. His work connects housing policies with broader societal transformations. Recent publications (2021-2025) analyze: Jewish housing spoliation in Paris; Soviet architectural practices in Latvia; Holocaust urban geography; and Cold War nuclear threat planning. These works implement archival research across multiple languages and comparative analysis frameworks. Scientific distinctions include: Académie d’Architecture first prize (2017) Société française d'histoire urbaine special thesis prize (2016) Administrative roles cover Latvian course leadership and Holocaust-related advisory functions. He co-organizes research seminars at EHESS on Baltic spaces and Soviet historiography, while maintaining cross-disciplinary collaborations through CREE research center.

• Construction Sector Policy
• Construction Procurement
• Project Organizing
• +۷ مورد دیگر

Professor Stuart Green (University of Reading) is a leading scholar in construction management with over £7.5M research income as Principal Investigator. His work focuses on construction sector policy analysis, project organizing, and identity work in projects. Currently chairing the University of Reading Environment and Sustainability Committee, he contributes to policy development through roles like Commission for Sustainable London 2012 (2007-2013) and EPSRC Peer Review College (2000-present). Guest Professor, Chongqing University (China) Visiting Professor, Hong Kong Polytechnic University (2014) Co-Editor, Construction Management and Economics (2009-2012) His research employs narrative and sensemaking methods to analyze policy unintended consequences and project risk management. Recent publications include the second edition of Making Sense of Construction Improvement (2023) and work on Turkish international contracting through historical narratives. With a 1996 PhD from Reading, he holds professional qualifications including CEng, MICE, FCIOB, and FRICS. Scientific recognition includes: Top 1.5% Global Scholar (Elsevier/Stanford, 2021) QE II Silver Scholarship (1988-1990) He supervises postgraduates on topics including: Professionalism in built environment Strategic briefing practices Chinese construction market dynamics Construction claims management Turkish contractor identity work Construction innovation narratives

• Structural Mechanics
• Nonlinear Dynamics
• Finite Element Analysis
• +۲ مورد دیگر

Dr. NÉMETH Róbert is an Associate Professor and Head of the Department of Structural Mechanics at the Budapest University of Technology and Economics . With a PhD in Civil Engineering (2004), he has contributed significantly to nonlinear structural mechanics, particularly in elastic rod analysis and finite element modeling. Current roles: Associate Professor, Department Head Key affiliations: Budapest University of Technology and Economics, Cornell University (visiting scientist) His research focuses on nonlinear dynamics of elastic systems, with applications to: Nonlinear normal modes Free vibration analysis Seismic response of masonry structures Elastic filament networks Continuum mechanics Finite element modeling Article trends show a consistent exploration of piecewise linear systems and cracked structures across decades, combining analytical and numerical approaches. Scientific awards include: DAAD Scholarships (1999, 2001) Dr. Imre Korányi Civil Engineering Scholarship (2004-2005) He has taught courses in structural dynamics, finite element methods, and mechanics in Hungarian, German, and English, while also serving on university committees.

Claire Delusمشاهده پروفایل

مدرس

• Continental Hydrology
• Water Cycle Dynamics
• Watershed Hydrology
• +۷ مورد دیگر

Claire Delus is a Lecturer in Geography at the University of Lorraine, specializing in continental hydrology at the intersection of engineering and geographical approaches. Her work emphasizes statistical and modeling methods, supported by naturalist observations of flow processes in watersheds influenced by physiographic contexts. Education: Doctorate in Geography (2007), Paul-Verlaine University of Metz, under Jeannine Corbonnois and Emmanuel Gille Research Activities: Water cycle dynamics Hydrosystems analysis Drought and low water level modeling Rainfall-runoff hydrological forecasting Multidisciplinary historical reconstructions Key Projects: ANR CIPRHES (2021-2024): Integrated hydrometeorological forecasting for droughts PESTINTER (2021-2023): Pesticide impacts on La Cleurie (Vosges) aquatic ecosystems RECRET (2017-2021): Moselle flood and drought history via sediment cores Technical Expertise: Hydrometry and sedimentology GIS applications in hydrology Field instrumentation Remote sensing and drone imaging

Bo Huiمشاهده پروفایل

استادیار

• Data Mining
• Machine Learning
• Graph Neural Networks
• +۶ مورد دیگر

Bo Hui is an Assistant Professor of Computer Science at The University of Tulsa's College of Engineering & Computer Science. He received his Ph.D. in Computer Science and Software Engineering from Auburn University in 2023 and earned his B.S. in Computer Science from Xi'an Jiaotong University in 2013. Prior to his Ph.D., he worked as a senior software engineer in the industry. Education: Ph.D., Computer Science and Technology, Auburn University, 2023 B.S., Computer Science and Technology, Xi'an Jiaotong University, 2013 Dr. Hui's research focuses on data mining and machine learning, particularly in designing machine learning methods for complex real-world data while addressing social concerns such as privacy in AI. His work spans multiple application domains including traffic prediction, social recommendation systems, and biological data analysis. He has made significant contributions to graph neural networks, knowledge graph unlearning, and federated learning systems. Dr. Hui's publication record demonstrates a strong focus on machine unlearning (the 'right to be forgotten' in AI models), graph neural networks, and traffic prediction systems. His work bridges theoretical machine learning with practical applications, with a growing emphasis on privacy-preserving AI techniques. He frequently publishes in top-tier venues including ICCV, ICLR, KDD, and AAAI. Awards and Honors: NSF award #2348177 for machine unlearning research AAAI student scholarship award Dr. Hui currently advises two Ph.D. students (Ruimeng Ye and Yang Xiao) who began their studies in Fall 2024. His research is supported by an NSF grant (#2348177) focused on machine unlearning. He has served as a reviewer for major conferences including ICLR, AAAI, KDD, CVPR, ACL, and EMNLP. His teaching includes Data Mining (2024 Spring) and Interaction Design (2023 Fall). His research group appears to focus on data mining and machine learning with applications to real-world problems requiring privacy-aware solutions.

Mohammad Namiمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Clinical Neuropsychology
• Sleep Neuroscience
• +۳ مورد دیگر

Dr. Mohammad Nami serves as Associate Professor of Cognitive Neuroscience and Clinical Neuropsychology at the School of Health Sciences and Psychology, Canadian University Dubai. He concurrently directs the Brain, Cognition, and Behavior Unit at BrainHub UAE and maintains associate membership in the Harvard Medical School Alumni network. Previously, he held leadership roles as Head of Neuroscience Department and Vice Chancellor for Research at Shiraz University of Medical Sciences. His academic credentials include: PhD in Cognitive Neuroscience from Institute for Cognitive Science Studies Dr. Nami's research centers on the interdependence of mental health and sleep health, with primary expertise in cognitive neuroscience, clinical neuropsychology, and sleep disorder interventions. He advocates that cognitive and affective potential can only be fully realized through integrated sleep-mental health approaches, emphasizing neuro-cognitive fitness and neurological aspects of sleep pathologies. His work bridges clinical practice with neuroscience to develop practical interventions for cognitive optimization. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) Sleep-neuroscience interfaces using quantitative EEG for insomnia and sleep disorder diagnostics, (2) Cognitive performance assessment in safety-critical occupations like aviation and industrial control rooms, and (3) Neurocognitive rehabilitation techniques for stroke, cerebral palsy, and neurodegenerative conditions. His methodology frequently combines clinical trials with advanced neuroimaging and computational modeling. As an associate member of Harvard Medical School Alumni and Harvard Alumni Entrepreneurs, Dr. Nami contributes to academic-industry knowledge translation. The provided text does not reference specific scientific awards. With 173 peer-reviewed publications (H-index 27, i10-index 77 as of August 2025), his research program demonstrates significant scholarly impact. While student mentorship details are absent, his leadership of the Brain, Cognition, and Behavior Unit suggests active supervision of research personnel. His publication record indicates consistent grant funding, particularly for sleep-neuroscience and occupational safety projects. The Brain, Cognition, and Behavior Unit at BrainHub UAE functions as his primary research hub, conducting studies on sleep-cognition interactions, neurocognitive fitness metrics, and real-world applications of neuroscience findings. Current initiatives appear focused on digital health tools for stress management and neurophysiological monitoring in occupational settings.

Roman Fedorovych Sukhonosمشاهده پروفایل

مدرس ارشد

• Internal combustion engines
• Thermal dynamics
• Gas-dynamic processes
• +۴ مورد دیگر

Roman Fedorovych Sukhonos is a Senior Lecturer at the Department of Automobiles, Heat Engines and Hybrid Power Plants within the Faculty of Transport at National University "Zaporizhzhia Polytechnic". He has been affiliated with the university since 2011, contributing to both teaching and research activities in the field of internal combustion engines and automotive systems. His educational background includes: Bachelor's degree in Engineering Mechanics from Zaporizhzhia National Technical University (2010) Master's degree in Internal Combustion Engines from Zaporizhzhia National Technical University (2011), with qualifications as "Master in Internal Combustion Engines, Researcher (Engineering Mechanics), Lecturer at Universities and Higher Educational Institutions" Roman Sukhonos specializes in thermal and gas-dynamic processes in internal combustion engines. His research focuses on improving engine performance, efficiency, and emissions characteristics through innovative design approaches and diagnostic methods. He has particular expertise in two-stroke engine technology, resonant supercharging systems, and the analysis of engine misfires and their effects on performance. His recent publications demonstrate a strong focus on practical applications of engine technology, ranging from chainsaw engines to high-performance automotive systems like Ferrari V12 engines. There's a clear trend toward integrating modern diagnostic techniques, including acoustic monitoring and neural networks, with traditional engine design principles. His work spans both theoretical analysis and experimental validation of engine performance characteristics. Dr. Sukhonos has received numerous awards and recognitions for his contributions: Letter of appreciation from Zaporizhzhia Regional State Administration (June 2023) Honorary certificate from Zaporizhzhia Regional Council (June 2022) Letter of appreciation from Rector of National University "Zaporizhzhia Polytechnic" (May 2022) Honorary certificate from Executive Committee of Zaporizhzhia City Council (November 2021) Certificate from Rector of National University "Zaporizhzhia Polytechnic" (December 2019) Certificate from Oleksandrivka District Administration (December 2018) Third degree diploma from Ministry of Education and Science, Youth and Sports of Ukraine (July 2012) Certificate from Executive Committee of Zaporizhzhia City Council (December 2005) While specific details about his advising activities are not explicitly mentioned, his extensive publication record with multiple co-authors suggests active involvement in research mentoring. His participation in numerous conferences and publication of textbooks indicates significant contributions to curriculum development and student education. His research appears to be supported through university affiliations and collaborations with colleagues. Dr. Sukhonos is part of a research team at the Department of Automobiles, Heat Engines and Hybrid Power Plants that focuses on engine diagnostics, performance optimization, and alternative engine designs. His collaborations with colleagues like Georgy Slynko indicate a strong research group working on advancing internal combustion engine technology despite the industry's shift toward electric propulsion.

Ivan Bratkoمشاهده پروفایل

استاد

• Machine Learning
• Knowledge-Based Systems
• Qualitative Modelling
• +۵ مورد دیگر

Ivan Bratko is a Professor of Computer Science at the University of Ljubljana's Faculty of Computer and Information Science. He founded the Artificial Intelligence Laboratory in 1985 and served as its head until 2017, remaining an active member. Until 2002, he also directed the AI group at the Jožef Stefan Institute. His academic journey includes B.Sc., M.Sc., and Ph.D. degrees in electrical engineering and computer science, all from the University of Ljubljana. Bratko's research spans machine learning, knowledge-based systems, qualitative modeling, intelligent robotics, heuristic programming, and computer chess. His work focuses on learning from noisy data, combining learning with qualitative reasoning, constructive induction, Inductive Logic Programming, and applications in medicine and dynamic system control. He has authored over 200 scientific papers and influential books including Prolog Programming for Artificial Intelligence (third edition, 2001), KARDIO: A Study in Deep and Qualitative Knowledge for Expert Systems (MIT Press, 1989), and Machine Learning and Data Mining: Methods and Applications (Wiley, 1998). His publication portfolio demonstrates consistent contributions to AI, with recent work emphasizing argument-based machine learning, qualitative modeling applications, and medical AI systems. These publications reveal strong interdisciplinary connections between theoretical AI and practical applications in environmental science, healthcare, and robotics. Fellow of the European Coordinating Committee for Artificial Intelligence (ECCAI) Member of the Slovene Academy of Arts and Sciences (SAZU) Former editorial board member of Artificial Intelligence , Machine Learning , Journal of AI Research , and other leading journals Co-founder and first chairman of the Slovenian AI Society (SLAIS) Bratko has secured numerous research projects including ARRS programs on artificial intelligence (2009-2020), the PARKINSCHECK project for Parkinson's disease detection, and European projects like X-MEDIA and XPERO. His laboratory serves as the central hub for AI research at the University of Ljubljana, fostering collaborations across medical, environmental, and industrial domains. He has mentored numerous researchers and maintained active collaborations through visiting positions at institutions including Edinburgh University, University of New South Wales, and Delft University of Technology.