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نمایش ۷۲۱-۷۳۵ از ۴٬۳۵۲ استاد راهنما
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Miroslav Stankovic is a researcher at TU Wien's Research Area Cyber-Physical Systems , focusing on probabilistic programming, invariant synthesis, and moment-based analysis of probabilistic loops. His work bridges theoretical computer science and machine learning, particularly in analyzing Bayesian networks and distribution recovery.
Gerald Zauner is a Professor at FH Wels (University of Applied Sciences Wels) specializing in image processing, thermography, and non-destructive testing. His research primarily focuses on railway infrastructure, computer vision, and artificial intelligence applications in engineering contexts. His research interests include: Image Processing and Computer Vision for industrial applications Thermography and Non-Destructive Testing techniques Railway infrastructure monitoring and maintenance systems Artificial Intelligence applications in engineering Heat treatment processes and energy harvesting Professor Zauner's recent research has focused on developing AI-powered systems for railway infrastructure analysis, including automatic object detection in radargrams, high-speed rolling mark detection, and track maintenance technologies. His work bridges the gap between theoretical computer vision techniques and practical engineering applications, particularly in the railway sector. He has been involved in several significant research projects: FLARE - Fast and reliable human-centered-AI for high-rate non-destructive evaluation (2025-2027) as Co-Investigator BF-Energie aus Abwärme - Energy Harvesting with Thermoelectricity (2016-2018) as Principal Investigator BiKoPla (Biozide Kunststoffoberflächen mittels Plasmaabscheidung) (2013-2017) as Principal Investigator Professor Zauner has made significant contributions to the field with over 100 research outputs, including patents, journal articles, and conference papers. His work has been cited over 300 times, demonstrating its impact in the engineering and computer vision communities.
استاد بالینی
Jennifer Coats is a Senior Clinical Professor in the Department of Finance and Real Estate at Colorado State University's College of Business, serving as Academic Director of the Master of Finance Program. She teaches Financial Markets and Methods in the Global Social and Sustainable Enterprise (GSSE) MBA program and International Finance. Her research employs experimental methodologies to investigate microfinance systems, private provision of public goods, and common property resource management. With publications in Economic Inquiry and the Journal of Public Economics , her work bridges behavioral finance, public economics, and environmental sustainability. She was a 2011-2012 Resident Research Fellow at Colorado State University's School of Global Environmental Sustainability. Analysis of her recent publications reveals consistent focus on behavioral aspects of economic decision-making, including financial well-being interventions, insurance choice anomalies, budgeting processes, and public goods dynamics. Her experimental approach provides empirical insights into how institutional structures shape individual and group financial behaviors across diverse contexts. Her scientific recognition includes: Resident Research Fellow, School of Global Environmental Sustainability, Colorado State University (2011-2012) Dr. Coats actively contributes to academic service through the First Generation Awards Committee, supporting initiatives for first-generation college students. She volunteers with the Poudre School District and maintains an active research agenda with publications spanning 28 years, including 2024 work on financial well-being improvement strategies.
Thomas Schön serves as the Beijer Professor of Artificial Intelligence at Uppsala University's Department of Information Technology within the Faculty of Science and Technology. His research focuses on developing probabilistic models and algorithms for extracting knowledge from data, with particular emphasis on dynamical systems. His research interests span multiple disciplines at the intersection of Machine Learning and statistics, signal processing, automatic control, and computer vision . He takes a systematic approach to representing and manipulating uncertainty through probability theory. His work encompasses both basic and applied research, with strong collaborations with industry partners including ABB Crane Systems, Autoliv, Saab, Sectra, and Xsens Technologies. Schön's research output demonstrates significant contributions to probabilistic modeling of dynamical systems , with particular expertise in sequential Monte Carlo methods (particle filters), Markov chain Monte Carlo, Gaussian processes, and deep learning. His recent work includes advancements in incorporating background knowledge into machine learning models and developing flexible probabilistic frameworks. Schön actively supervises numerous PhD students working on diverse topics including Bayesian nonparametric models, deep learning applications, uncertainty-aware systems, and probabilistic computer vision. His research is funded by The Swedish Research Council (VR), The Swedish Foundation for Strategic Research (SSF), and Vinnova.
Alex Steiny Wellsjo is an active Assistant Professor of Economics and Strategy at the Rady School of Management, University of California San Diego. With a PhD in Economics from UC Berkeley and postdoctoral training at the Haas School of Business, Wellsjo combines economic theory with psychological insights to study individual behavior. Education : PhD in Economics (UC Berkeley), Postdoctoral Training (Haas School of Business) Research Focus : Applied microeconomics with emphasis on behavioral economics, health economics, and household finance. Key themes include: Habit formation and automaticity in organizational settings Productivity optimization through behavioral interventions Inflation's impact on housing market decisions Data-driven fintech innovations and their economic consequences Recent Publications demonstrate interdisciplinary trends in behavioral economics, with applications spanning healthcare compliance, financial decision-making, and productivity management. His work employs audit studies, longitudinal data, and real-effort experiments. Collaborations include researchers from multiple institutions in economics, psychology, and business fields. Wellsjo maintains active research in: Behavioral interventions for organizational performance Self-regulation across life-course stages Technological impacts on financial services
Ana-Sabina Uban is an Associate Professor at the Faculty of Mathematics and Computer Science, University of Bucharest . She earned her Ph.D. in Computer Science in 2020 under the supervision of Professor Liviu Dinu with a thesis on distributional and stylistic aspects of natural language. She teaches and coordinates courses in natural language processing, AI, and machine learning for both computer science and digital humanities students. Education: Ph.D. in Computer Science, University of Bucharest (2020) – Thesis: "Distributional aspects of natural language. Semantic and stylistic dimensions of text" Research Interests: Dr. Uban’s research is strongly interdisciplinary, bridging natural language processing , computational linguistics , psychology , and cognitive science . She explores historical computational linguistics , distributional semantics , and multilingualism , while also investigating explainability in AI models and mental health disorder detection using social media data. Research Trends & Publication Focus: Her recent publications span clinical NLP , mental health detection , historical linguistics , and multilingual cognate identification . A recurring theme is the application of advanced NLP techniques—such as transformer models, contrastive learning, and ensemble classification—to real-world problems in health, literature, and historical language study. Teaching & Student Supervision: Dr. Uban currently teaches and coordinates the following courses: Bio-medical NLP – Master’s level (English) Artificial Intelligence – Bachelor’s level for Mathematics students Practical Introduction to Machine Learning – Master’s level for Digital Humanities students Natural Language Processing 1 & 2 – Master’s labs and projects Contact: auban@fmi.unibuc.ro
Marta Vivar Garcia serves as a Contracted Professor within the Department of Electronic and Automatic Engineering at the University of Jaén, actively contributing to the Center for Advanced Studies in Earth Sciences, Energy. Her work centers on the Research and Development in Solar Energy group, where she pioneers hybrid photovoltaic-water treatment technologies with global sustainability applications. She earned her PhD from Universidad Politécnica de Madrid in 2009 with a dissertation on Optimization of Euclidean Concentration Photovoltaic Technology , supervised by Dr. Gabriel Sala Pano. Her academic foundation integrates electronics engineering with renewable energy systems. Vivar Garcia's research focuses on solving critical water-energy challenges through innovations like the SolWat system, which simultaneously generates electricity and disinfects water using photovoltaic modules. Her work spans solar disinfection kinetics, hybrid system optimization, IoT-based monitoring for remote installations, and practical implementations in arid regions and refugee camps. She emphasizes scalable solutions for developing communities while addressing environmental and economic viability. Analysis of her 15 most recent publications reveals three dominant trends: (1) Evolution from basic SolWat prototypes to grid-integrated wastewater treatment systems compliant with EU regulations; (2) Increasing sophistication in pathogen-specific disinfection modeling using UV-LEDs and solar optics; (3) Strategic expansion into IoT-enabled mass monitoring for off-grid solar systems in resource-constrained settings. Her work consistently bridges fundamental engineering principles with urgent global sustainability needs. As leader of the Research and Development in Solar Energy group, she directs projects focused on photovoltaic-water synergy, with field trials spanning Mexico's rural communities to Saharawi refugee camps. Her team specializes in converting theoretical solar energy concepts into field-deployable technologies that address both electricity access and water safety challenges.
Miroslaw Pawlak is affiliated with Adam Mickiewicz University in Poznan, Poland, focusing on second language acquisition and language learning psychology. Key research areas: Emotional dynamics in language classrooms, strategic grammar instruction, blended learning environments Recent work explores foreign language enjoyment/boredom, grit in SLA, and technology-mediated learning Publications from 2025 investigate: Emotion mediation in Chinese student engagement Pronunciation knowledge development through explicit/implicit learning Playfulness as a counterbalance to language learning boredom His work employs advanced statistical modeling and mediation analysis to understand affective factors in multilingual education contexts.
Jie Wang is a Professor of Computer Science at the University of Massachusetts Lowell's R. Miner School of Computer and Information Sciences. He joined UMass Lowell in 2001 as a Full Professor and chaired the department for 9 years from 2007 to 2016. He serves as Director for China Partnership of the US-based Consortium for Mathematics and Its Applications (COMAP) since 2011. Prior to UMass Lowell, he was Assistant Professor and then Associate Professor of Computer Science at the University of North Carolina. Professor Wang's research spans multiple areas including text mining algorithms and systems, data modeling, combinatorial optimizations, network security, wireless sensor networks, and computational complexity theory. His work has evolved from theoretical foundations in computational complexity (1980s-early 2000s) to practical applications in data analysis, intelligent text automation, and AI systems. His recent publications focus on AI-Oracle machines, LLMs, text mining, document engineering, and network security. His research portfolio demonstrates a clear evolution from theoretical computer science to applied research with practical impact. The publications show increasing focus on AI, text mining, and document engineering in recent years, while maintaining foundations in algorithm design and network security. His work bridges theoretical computer science with real-world applications across multiple domains. Honorary Advisor (2013) - NeoUnion Hong Kong Education Science Culture Organization MHE Scholar (2012) - Ministry of Higher Education, China PMYR Award for Major New Initiatives (2010) - University of Massachusetts Lowell Teaching Excellence Award (2002) - University of Massachusetts Lowell Nominee of Board of Governors' Teaching Excellence Award (2000) - University of North Carolina Professor Wang has graduated 18 PhD students and is currently directing 5 PhD students. His research has been funded by the National Science Foundation, IBM, Intel, and other companies totaling approximately $4.8 million. He is active in professional service, including chairing conference program committees, serving as journal editors, and as editor-in-chief of a book series on mathematical and interdisciplinary modeling. His laboratory work focuses on text mining systems, network security applications, and computational models for practical problems.
استادیار
Hannah MacNaul, Ph.D. , BCBA-D, LBA, LSSP is an Assistant Professor in the Department of Educational Psychology at the University of Texas at San Antonio (UTSA) , affiliated with the College of Education and Human Development (COEHD) . Her work focuses on applied behavior analysis (ABA) for individuals with Autism Spectrum Disorder (ASD) and developmental disabilities. Education: Master of Arts in School Psychology, University of Texas at San Antonio Ph.D. in Applied Behavior Analysis, University of South Florida Research Interests: Dr. MacNaul evaluates translational approaches to severe behavior assessment and treatment, develops non-obtrusive interventions for ASD, and investigates multidisciplinary training in higher education. Her projects include validating a severity tool for challenging behavior and testing functional communication training without extinction. Research Trends: Recent publications emphasize preference assessments , telehealth interventions , technology integration in ABA, and group contingency strategies for early childhood classrooms. She also explores the stability of behavioral assessment outcomes and caregiver involvement in autism care. Labs & Teams: Dr. MacNaul contributes to the TEACH Lab and Severe Behavior Lab at UTSA, collaborating with teams like the ABA Teacher Project and Project EARLY to address behavioral challenges in educational and clinical settings. Contact: hannah.macnaul@utsa.edu | UTSA Downtown Campus, Durango Building 4.340
دانشیار
Professor Viktor Avrutin is an extraordinary professor (Apl. Prof.) at the University of Stuttgart, Germany, affiliated with the Institute for Systems Theory and Automatic Control. He holds a Dr. rer. nat. habil. degree in Computer Science from the University of Stuttgart, where he was appointed as an extraordinary professor in 2020 after obtaining his Privatdozent status in 2011. Avrutin completed his academic journey with a B.Sc. from St. Petersburg State Polytechnical University (1992), an M.Sc. in Computer Science with Mathematics from the University of Stuttgart (1997), and a Ph.D. from the University of Stuttgart (2003) with a thesis on piecewise-smooth dynamical systems. His research focuses on nonlinear dynamics with particular emphasis on bifurcation theory for piecewise smooth systems, border collision and homoclinic bifurcations, low-dimensional chaos, and bifurcations of chaotic attractors (crises). He also investigates numerics, simulation software, algorithms, and neural networks. His work spans multiple disciplines including electrical engineering (power converters and inverters), mechanical systems (vibration machines), biological modeling (Goodwin's oscillator), and ecological systems (predator-prey models). Analysis of his recent publications reveals a consistent focus on piecewise smooth dynamical systems, with particular attention to border collision bifurcations, chaotic attractors, and their transformations. His research demonstrates strong interdisciplinary applications, connecting theoretical mathematics with practical engineering problems in power electronics, mechanical systems, and biological modeling. The recurring themes across his work include the study of complex nonlinear phenomena in systems with discontinuities, transformation of attractors, and the interplay between deterministic and stochastic elements in nonlinear systems. Professor Avrutin teaches courses including Nonlinear Dynamics and Chaos Theory I (summer term), Dynamics of Nonsmooth Systems, and Nonlinear Dynamics and Chaos Theory II (winter term) at the University of Stuttgart.
Marcel Campen is a Professor at Osnabrück University specializing in Computer Graphics and Geometry Processing. His research focuses on surface parametrization, quad mesh generation, and computational geometry. He has made significant contributions to the field of geometry processing, particularly in developing algorithms for quad layout generation, surface mapping, and mesh repair. His research interests span Computer Graphics, Geometry Processing, Surface Parametrization, Quad Mesh Generation, 3D Modeling, and Mesh Repair. Campen's work addresses fundamental challenges in representing and processing complex geometric shapes, with applications ranging from animation and simulation to reverse engineering and meshing. His research often combines theoretical insights with practical implementations, resulting in algorithms that are both mathematically sound and computationally efficient. Campen's publications demonstrate a strong focus on developing robust and efficient methods for geometry processing. His work on quad layout generation, parametrization techniques, and surface mapping has resulted in several award-winning papers, including Best Paper Awards at SGP 2021 and 2022. His research often bridges theoretical concepts with practical implementations, making his contributions highly influential in both academic and industrial settings. Best Paper Award (1st place) at SGP 2022 Best Paper Award at SGP 2021 Campen has made significant contributions to the field through his doctoral thesis on quad layout generation and numerous publications in top-tier conferences including SIGGRAPH, Eurographics, and SGP. His work on directional field synthesis, similarity maps, and bijective mappings has advanced the state of the art in geometry processing. He has also contributed to practical tools like libQEx for robust quad mesh extraction, demonstrating his commitment to making theoretical advances accessible to practitioners.
عضو هیئت علمی
Andrew S. Gordon is a Research Associate Professor of Computer Science at the University of Southern California and Director of Interactive Narrative Research at the Institute for Creative Technologies. His work integrates artificial intelligence, cognitive science, and interactive storytelling to create systems that automatically interpret and generate narrative structures, with a special focus on commonsense reasoning and abductive inference. Education Ph.D. in Computer Science, Northwestern University, 1999 Research Interests Gordon’s research converges on computational narrative intelligence . He develops formal models of commonsense psychology that enable machines to reason about human intentions, beliefs, and emotions. His group designs interactive narrative systems for training and education, builds large-scale story corpora, and pioneers abductive reasoning techniques that combine symbolic logic and statistical learning to interpret temporal data. Recent work explores how large language models can be guided to co-create interactive fiction and how vision–language models can be benchmarked for causal understanding. Publication Trends Across more than two decades, his publications reveal consistent themes: (1) foundational theories of commonsense psychology and strategy representation, (2) narrative technologies that blend AI planning with human creativity, and (3) practical training simulations for defense and education. The 2024-2025 papers highlight a pivot toward evaluating and steering large language models for narrative tasks, while earlier work established abductive reasoning frameworks such as “Etcetera Abduction.” Awards & Honors Best Paper Award, System Lifecycle and Technologies Track, Simulation Interoperability Standards Organization (SIW 2021) Advising & Grants He has successfully mentored three PhD students—Reid Swanson (2010), Christopher Wienberg (2017), and Melissa Roemmele (2018)—whose dissertations span computational narrative, commonsense reasoning, and interactive fiction. His research has been continuously supported by agencies including the U.S. Army, DARPA, and NSF for projects on virtual training environments, narrative-centered learning, and large-scale commonsense knowledge acquisition. Labs & Teams Gordon directs the Interactive Narrative Research Group at USC’s Institute for Creative Technologies, where interdisciplinary teams of computer scientists, cognitive psychologists, and interactive media designers collaborate on systems such as the Rapid Integration & Development Environment (RIDE) for embodied conversational agents and story-driven training simulations.
مدرس ارشد
Dr. Anton Ragni is a Senior Lecturer in Speech and Language Technologies at the University of Sheffield's School of Computer Science, where he serves as Assessments Lead and contributes to the Speech and Hearing (SpandH) research group. His educational background includes: BEng in Information Technology from the University of Tartu (2005) MEng in Information Technology from the University of Tartu (2007) PhD from the University of Cambridge (2013) Ragni's research centers on machine learning approaches for speech and language processing, with core expertise in automatic speech recognition (ASR), expressive speech synthesis, spoken language translation, information retrieval, and conversation modeling. His work increasingly integrates self-supervised learning and foundation models to address challenges in speech technology and cross-domain applications like music processing. Analysis of his recent publications reveals a strong trend toward applying speech processing techniques to music understanding and developing robust ASR systems for specialized populations, including hearing-impaired users and children. His work demonstrates consistent innovation in leveraging contextual information and novel architectures like energy-based models. His scientific recognition includes: Best Student Paper Award at IEEE ASRU 2011 for 'Generative kernels for noise robust ASR' Ragni has secured significant research funding as Principal Investigator and Co-Principal Investigator: EPSRC grant 'Exemplar-based Expressive Speech Synthesis' (2021-2023, £218,290) as PI Innovate UK grant 'Automatic voice conversion for transforming professional adult voice actors to artificial child voice actors' (2021-2023, £173,605) as Co-PI He actively contributes to the Speech and Hearing research group, focusing on advancing speech technology through interdisciplinary collaboration and real-world applications.
Professor Balázs Adam Kulcsár is a faculty member in the Automatic Control research group at the School of Electrical Engineering and Computer Science, Chalmers University of Technology. With 104 publications and involvement in 34 research projects, he is a prominent researcher in intelligent transportation systems. His work spans multiple domains within transportation engineering and control theory, with significant contributions to traffic flow modeling, electric vehicle routing, and advanced control systems. Professor Kulcsár's research primarily focuses on intelligent transportation systems design, traffic flow modeling for control, Linear Parameter Varying systems, and failure diagnostics. His work demonstrates a strong integration of control theory with practical transportation challenges, particularly in the context of electric mobility and sustainable transportation. Recent research shows a growing emphasis on machine learning applications for transportation optimization, electric vehicle infrastructure, and urban traffic management. Analysis of his recent publications reveals a clear trajectory toward sustainable transportation solutions, with electric vehicle charging infrastructure, fleet management, and public transit optimization as dominant themes. His work increasingly incorporates machine learning techniques, particularly graph neural networks and reinforcement learning, to address complex transportation challenges. The research demonstrates strong interdisciplinary collaboration across engineering disciplines, with a focus on practical implementation of theoretical advances. Professor Kulcsár leads and participates in numerous research projects focused on future transportation systems, including projects on electric mobility, traffic optimization, and intelligent transportation infrastructure. His research group collaborates extensively with industry partners like Volvo and Heart Aerospace, as well as with other academic institutions. Current projects include Rethinking the Sustainability of V2G, Quantum computing for future mobility solutions, and Digital Twin for Energy Prediction. His research group maintains strong connections with transportation industry stakeholders and contributes to major initiatives such as the Transport Area on Advance project, which aims to achieve leading competence in future green, safe, and efficient transport systems. The team operates at the intersection of theoretical control systems and practical transportation applications, with particular expertise in modeling complex traffic phenomena and developing implementable control solutions.
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