جست‌وجوی استاد و پژوهشگر

Floriana Espositoمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Programming Languages
• +۳ مورد دیگر

Floriana Esposito is a Full Professor and current Director of the Department of Computer Science at the University of Bari, Italy. With a career spanning over 50 years since her 1974 appointment, she has held pivotal leadership roles including Dean of the Faculty of Computer Science (1997-2002) and Director of the Interdepartmental Center for Logic and Applications (1997-2001). She teaches core courses including Algorithms and Data Structures, Knowledge Engineering, and Machine Learning. Education: Degree in Electronic Physics from University of Bari (1970) First Academic Appointment at University of Bari (1974) Research Focus: Her work centers on Artificial Intelligence and Machine Learning with emphasis on logical/algebraic foundations. Initial research in statistical pattern recognition evolved into Intelligent Tutoring Systems and Machine Learning, now focusing on similarity-based learning, multistrategy approaches, and integration of symbolic/numeric methods. Major applications target Document Analysis and Understanding for paper-based systems, with significant contributions to symbolic data analysis and knowledge discovery. Publication Trends: Recent work shows strong continuity in multistrategy and incremental learning techniques applied to document processing and symbolic data analysis. Her research consistently bridges theoretical foundations (logical theories, concept drift handling) with practical implementations in spatial data mining, e-learning systems, and urban planning, demonstrating a 30-year trajectory from knowledge acquisition fundamentals to real-world AI deployment. Scientific Awards: No specific awards were mentioned in the source text. Advising & Grants: As founder of LACAM Laboratory (1986), she has mentored numerous PhD students and researchers. Her group secured extensive EU funding through ESPRIT, IST, and Framework programs including MLNet, KDNET, and DELOS Networks of Excellence, focusing on machine learning applications in document analysis, digital libraries, and spatial data mining across 15+ European collaborative projects. Labs & Teams: She chairs LACAM Laboratory (2 full professors, 3 associate professors, 5 assistant professors, multiple PhD students), which serves as a European hub for AI research. The lab has been integral to ESPRIT Intrepid (document processing), CONCERTO (digital document retrieval), COLLATE (historical archive systems), and SODAS (symbolic data analysis), maintaining continuous involvement in EU Networks of Excellence since the 1990s.

Antonietta Lanzaمشاهده پروفایل

استادیار

• Man-Machine Interaction
• Machine Learning
• Knowledge Acquisition
• +۴ مورد دیگر

Antonietta Lanza is an Assistant Professor of Computer Science at the Department of Informatics, University of Bari, Italy. She earned her degree in Information Science from the same university in 1978 and has been a faculty member since 1984. Her research spans man-machine interaction, machine learning, and knowledge acquisition with applications in technical document processing and geospatial data interpretation. Education : Degree in Information Science (University of Bari, 1978) Affiliations : Department of Informatics, University of Bari Her research focuses on integrating machine learning with geospatial analysis, particularly for wind speed forecasting, topographic map interpretation, and cadastral data processing. She has developed algorithms for spatio-temporal modeling and spatial clustering of structured data. Recent publications primarily address wind power prediction, spatio-temporal lazy learning, and cluster-based time series modeling. Applications span renewable energy, environmental planning, and maritime AIS data analysis. She actively contributes to academic associations AI*IA (Italian Association for Artificial Intelligence) IAPR-IC (International Association of Pattern Recognition - Italian Chapter) and has created software like PS_package , a tool for line-drawing segmentation.

Ferdinand Riveraمشاهده پروفایل

استاد

• Mathematical Cognition
• Visualization in Mathematics
• Teacher Preparation
• +۳ مورد دیگر

Ferdinand Rivera is a Professor in the Department of Mathematics & Statistics at San José State University. His research focuses on mathematical cognition, particularly the emergence of structural thinking in children and adults, and the role of visualization in mathematical understanding. He leads initiatives to develop inclusive mathematics teacher preparation programs and explores technology-mediated learning tools, including virtual reality applications for linear algebra education. Dr. Rivera holds a Doctor of Philosophy from Ohio State University and a Postgraduate Diploma in Cultural Studies from the University of Bonn. He directs three NSF-funded projects: (i) Developing 21st century inclusive mathematics teachers (DUE 2151134), (ii) Creating VR tools for linear algebra (DUE 2315756), and (iii) Studying math teacher effectiveness (DUE 2345187). His SJSU RSCA grant supports VR app development and classroom scalability. Rivera's research examines how learners develop pattern generalization abilities and utilize visual representations to construct mathematical knowledge. His work spans cognitive psychology, educational technology, and equity-focused pedagogy. Recent publications explore extended reality in STEM education, cognitive foundations of algebraic reasoning, and inclusive teaching practices. His research has been recognized through multiple National Science Foundation grants supporting mathematics education innovation. Current investigations focus on virtual reality's potential to enhance conceptual understanding and the longitudinal analysis of teacher development programs.

Tim Loboschefskiمشاهده پروفایل

استاد

• Developmental Psychology
• Cognition Across Lifespan
• Attention-Deficit Hyperactivity Disorder (ADHD) Diagnostics
• +۳ مورد دیگر

Tim Loboschefski is a Professor of Psychology at Sweet Briar College. He holds a B.A., M.A., and Ph.D. in Developmental Psychology from the University of Toledo. His research focuses on identity formation in Millennials and Gen-Z generations and its impact on legal/moral reasoning, alongside earlier work on ADHD diagnostics and infant cognition. He teaches courses including Developmental Psychology, Statistics for Behavioral Sciences, and Family Systems. Education: B.A. in Psychology, University of Toledo M.A. in Developmental Psychology, University of Toledo Ph.D. in Developmental Psychology, University of Toledo His research explores cognitive development across the lifespan, with notable contributions to EEG-based ADHD diagnostics and infant memory studies. He has secured grants from the Thomas F. Jeffress Memorial Trust and Virginia’s Commonwealth Health Research Board, and directs community engagement initiatives like the PACE program. His work appears in journals such as Applied Psychophysiology and Biofeedback and Current Pediatric Reviews . Publications highlight trends in developmental neuroscience, STEM education outreach, and longitudinal studies on infant behavior. His career combines academic research with active community partnerships.

Ekaterina Shurkovaمشاهده پروفایل

مدرس

• Cognitive Psychology
• Analogical Reasoning
• Creative Problem Solving
• +۴ مورد دیگر

Ekaterina Shurkova is a Lecturer in Psychology at the School of Philosophy, Psychology and Language Sciences, University of Edinburgh. She holds a PhD in Cognitive Psychology and has interdisciplinary expertise spanning Computer Science and Mathematics. Her research focuses on mental representation mechanisms, analogical reasoning, and creative problem-solving processes. She designs and teaches courses on psychological research methods, data analysis (using R), and cognitive neuroscience. Educations: PhD in Cognitive Psychology, University of Edinburgh MS in Psychology (Old Dominion University) MS in Computer Science (Old Dominion University) BS/MS in Applied Mathematics (Saratov State University) Her research integrates symbolic-connectionist models to study relation learning and visual reasoning. Current projects explore how embodied cognition influences insight-based problem-solving and the role of 'aha!' moments in creativity. She actively develops computational models to simulate cognitive processes in structured relational environments. Teaching responsibilities include core undergraduate courses and supervision of honors/MSc thesis projects on embodied cognition and creative problem-solving. Active in curriculum development for R-based data analysis and psychological research methodologies. Recent work examines neural correlates of social anxiety and explores optimization challenges in wireless sensor networks from her earlier computer science research phase.

Md Imbesat Hassan Rizviمشاهده پروفایل

پژوهشگر

• Scientific Machine Learning
• Natural Language Processing
• Reinforcement Learning
• +۳ مورد دیگر

Md Imbesat Hassan Rizvi is a Technical (Research) Associate at the Robert Bosch Centre for Cyber-Physical Systems (RBCCPS), Indian Institute of Science (IISc). His research focuses on Scientific Machine Learning, Natural Language Processing (NLP), Reinforcement Learning, Robotics, Human-Robot Interaction, and Multi-modal Machine Learning. He is actively involved in projects such as enabling natural interactions with social robots like 'Asha,' which includes speech communication, lip synchronization, and NLP-based instruction execution. His work combines robotics with NLP and reinforcement learning, leading to open-source contributions like the sonorus package and imperio repository. Rizvi's academic background includes an M.Tech. in Computational and Data Sciences from IISc (2015-2017) and a B.Tech. in Mechanical Engineering from IIT(ISM) Dhanbad (2008-2012). His research has spanned diverse areas including causal relation extraction from clinical notes (MIMICause corpus), diabetes-related tweet analysis, and molecular descriptor-based drug discovery. He has been recognized as a finalist in ICSR 2021 and a semi-finalist in the ANA Avatar XPRIZE competition. Notable contributions include publications on causal language modeling, medical informatics, and thermodynamics of nanofluids. His technical expertise extends to parallel computing optimizations and customer review analysis at HP Inc. Rizvi’s projects also include language identification systems and retrofitting word vectors to semantic lexicons, showcasing his versatility in both theoretical and applied research domains.

Teo Paolettiمشاهده پروفایل

دانشیار

• Mathematics Education
• Student Understanding of Mathematical Concepts
• Design-Based Research
• +۳ مورد دیگر

Teo Paoletti is an Associate Professor in the School of Education at the University of Delaware, specializing in mathematics education. His research focuses on student understanding of mathematical concepts across K-12 and post-secondary levels, leveraging design-based methods and dynamic software tools like GeoGebra. He holds a Ph.D. from the University of Georgia and previously taught middle/high school mathematics in New Jersey. Education: Ph.D., Mathematics Education, University of Georgia (2015) M.S., Mathematics, Texas A&M University (2010) B.A., Mathematics with Teacher Certification, The College of New Jersey (2007) Research Interests: Dr. Paoletti investigates how students develop covariational reasoning and construct mathematical concepts through dynamic software. Key areas include: coordinate systems, graphical shape thinking, function classes, and inequalities. He emphasizes the role of reasoning about quantitative relationships in fostering deep mathematical understanding. Recent Publications Trends: His work explores covariational reasoning’s role in graph interpretation, task design for middle-schoolers, and cross-disciplinary applications of TIMSS data. Recent articles highlight innovations in graphing conventions, coordinate system meanings, and student reasoning trajectories. Awards: 2016 Honorable Mention, CRUME Best Paper Award 2016 AMTE STaR Fellow Grants & Collaborations: PI of the Spencer Foundation-funded Mid-CoS project (2017–present). Co-PI on NSF-funded initiatives to improve precalculus teaching. His research has been published in leading journals including Journal of Mathematical Behavior and For the Learning of Mathematics . Professional Contributions: Editorial board member of Journal of Mathematical Behavior . Active in teacher education, having transitioned from classroom teaching to university research.

Jianbo Jiaoمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Healthcare
• +۳ مورد دیگر

Jianbo Jiao is an Associate Professor at the School of Computer Science, University of Birmingham . He leads the MIx (Machine Intelligence + x) research group and holds a Fellowship of the Higher Education Academy . His academic journey includes a PhD in Computer Science from City University of Hong Kong (supported by the Hong Kong PhD Fellowship), postdoctoral work at University of Oxford (BioMedIA and VGG groups), and visiting roles at University of Illinois Urbana-Champaign (IFP group) and Tencent AI Lab . Research Interests: Computer Vision Machine Learning Healthcare Applications AI for Science His work focuses on open-world representation learning with reduced supervision, leveraging multi-modal auxiliary information. This includes significant contributions to medical imaging , 3D scene reconstruction , and AI4Science applications. He also explores transformer models , few-shot learning , and cross-modal knowledge transfer . Publication Trends: Recent articles highlight advancements in medical imaging (fetal ultrasound analysis), 3D scene modeling (Gaussian splatting, novel view synthesis), and multi-modal learning (audio-visual fusion). Key venues include ICLR , CVPR , NeurIPS , and ECCV . Scientific Recognition: Best Paper & Best Presentation (Runner-Up) at MICCAI 2024 ASMUS Workshop Amazon Research Award (2024) Royal Society Short Industry Fellowship (2023) International Exchanges Grant (2023) Outstanding Reviewer Awards at NeurIPS, ICML, and ACCV Academic Service: He serves as Area Chair for NeurIPS , ICML , and ACM MM , and as Associate Editor for T-CSVT , TMLR , and The Visual Computer .

Arnaud Revelمشاهده پروفایل

استاد

• Machine Learning
• Human-Computer Interaction
• Robotics
• +۶ مورد دیگر

Arnaud Revel is a Professor at the University of La Rochelle, holding the position of Deputy Director of the Science and Technology Department since April 2015 and Deputy Director of the S2IM doctoral school (Sciences and Engineering for Information, Mathematics) since June 2012. His academic career spans multiple institutions including ENSEA, where he was initially recruited in 1998, and the University of La Rochelle where he was promoted to professor in 2009. He has served in various administrative roles including co-directing the IMAGIN team at L3I laboratory and as deputy director of the L3I laboratory for AERES evaluation. Revel's research interests focus on three interconnected themes: Learning (structuring complex information and data mining), Human/Machine Interaction (modeling interaction dynamics in robotics and multi-agent systems), and Art and Science (notably the LINK Human/Robot project collaborating with the Cambrai School of Art). His work bridges theoretical computer science with practical applications in robotics, digital art, and interactive systems. Recent publications demonstrate his continued focus on mobile agent security, human-robot interaction, and content-based image retrieval, with notable collaborations across disciplines and international borders. His work on the LINK Human/Robot project, despite not receiving ANR funding, has been presented at prestigious venues including Le Fresnoy (2012), Bains numériques (2012), Futur en Seine (2013), VIA (2014), University of La Rochelle (2014), and Le Cube (2015), culminating in a collaborative art and science book published by Van Dieren in 2015. Professor Revel has supervised multiple doctoral students including K.Prepin (co-supervision, 2008), M.Rojas-Castro (co-supervision since 2012), and H.Idrissi (co-supervision since 2013 in a cotutelle with Morocco). His teaching activities span various institutions including the University of La Rochelle where he teaches Logic Programming, Smartphone programming, and Video Game Programming at the undergraduate level, and Data Mining and Python Programming at the Master's level.

• Data Warehousing
• Database Systems
• Information Integration
• +۵ مورد دیگر

Dr. Mukesh Mohania serves as an Adjunct Professor at UNSW Canberra within the School of Business. His extensive academic career spans over three decades with continuous scholarly contributions from 1994 through 2025. His research bridges theoretical database systems with practical applications across multiple domains including educational technology, blockchain, and business intelligence. Professor Mohania's research interests demonstrate remarkable breadth and evolution over time. Beginning with foundational work in data warehousing and database systems, his research trajectory expanded into information integration, privacy management, and more recently, educational technology and blockchain applications. His scholarly work shows a consistent pattern of addressing emerging technological challenges while maintaining connections to core database principles. A distinctive characteristic of his research is the practical application of theoretical concepts to solve real-world business and educational problems. The analysis of his recent publications reveals a strong focus on educational technology applications, with approximately 40% of his 2022-2025 publications addressing AI-driven educational systems, question categorization, and learning analytics. Another significant portion (around 30%) focuses on security, privacy, and blockchain applications. The remaining publications continue his longstanding interest in database systems, data mining, and information integration. This distribution indicates a strategic pivot toward educational technology while maintaining expertise in his foundational areas. Professor Mohania has established a prolific publication record with over 100 scholarly contributions including book chapters, journal articles, and conference papers. His work appears in prestigious venues such as IEEE Transactions on Knowledge and Data Engineering, ACM conferences, and Springer publications. While specific awards aren't documented in the available information, his sustained publication record across multiple decades demonstrates significant scholarly impact. His research collaborations span numerous institutions and researchers globally, with frequent co-authorship patterns suggesting established research teams focused on educational technology and database systems. The consistent output across decades indicates successful grant funding and sustained research activity, though specific grant details aren't provided in the available information. Professor Mohania's work shows particular strength in translating database research into practical business and educational applications.

Ralph Ewerthمشاهده پروفایل

استاد

• Multimedia Retrieval
• Machine Learning
• Visual Analytics
• +۵ مورد دیگر

Prof. Ralph Ewerth is a Professor leading the Visual Analytics research group at the Technische Informationsbibliothek (TIB) since 2015. His work bridges computer science, information science, and education, focusing on multimedia retrieval, machine learning, and visual analytics. He has pioneered research in areas like content-based video retrieval, image-text relation analysis, and educational technology platforms. Key research interests include: Development of AI-driven tools for educational analytics (e.g., learning platforms for chemistry education) Advancements in multimedia retrieval systems (e.g., TIB AV-Analytics platform) Analysis of sports data through spatiotemporal event detection Design of open research knowledge graphs and journal recommendation systems (B!SON project) Recent publications (2022-2024) emphasize multimodal misinformation detection, search behavior analysis, and fusion of vision-language models. He has edited conference proceedings and contributed to over 150 peer-reviewed works across domains like digital libraries, computer vision, and educational technology. His research infrastructure includes the TIB AV-Analytics platform for scholarly video analysis and the B!SON open access journal recommendation tool. Collaborative projects focus on integrating semantic web technologies with educational and sports data analysis.

Eva Navarro Lópezمشاهده پروفایل

استاد

• hybrid dynamical systems
• cyber-physical systems
• network science
• +۱۷ مورد دیگر

Eva Navarro López is a Full Professor in Computing within the School of Interactive Games and Media at the Golisano College of Computing and Information Sciences at Rochester Institute of Technology (RIT). She previously served as Director of the School of Information (iSchool) at RIT and directs the Artificial intelligence and DAta science Research Lab (AiDAs). Navarro is a scientist of international standing with extensive contributions across multiple fields including hybrid dynamical systems, cyber-physical systems, and computational neuroscience. She has held significant positions including member of the Science and Methodology Committee at the International Panel on the Information Environment (IPIE) and affiliate at the Minderoo Centre for Technology and Democracy at University of Cambridge. Eva earned her Ph.D. from the Polytechnics University of Catalonia (Spain) and completed her MSc, BEng, and BSc at the University of Alicante (Spain). Her educational journey reflects her multidisciplinary approach, bridging computer science, mathematics, and engineering disciplines that would later define her research career. Her academic path has taken her through prestigious institutions across four countries: USA, UK, Mexico, and Spain, where she shadowed the footsteps of Alan Turing in Manchester and Santiago Ramón y Cajal in Madrid. Navarro's research interests defy easy compartmentalization, spanning hybrid dynamical systems, cyber-physical systems, network science, mathematical modelling, symbolic AI, control engineering, computational neuroscience, and collective intelligence. Her unique contribution lies in building bridges between traditionally separate fields , transferring ideas from one domain to another to create novel approaches. She approaches research as a 'scientist artist,' viewing both science and art as attempts to understand the world better. Her work on neuroplasticity and brain-inspired computing has led to innovative AI architectures that incorporate knowledge of astrocytes and other brain cells beyond just neurons. Analysis of Navarro's recent publications reveals a strong trend toward interdisciplinary applications of computational methods. Her work spans from fundamental theoretical contributions in hybrid systems and formal verification to practical applications in medical imaging, epidemic modeling, and gender equity in technology. A notable pattern is her consistent focus on nature-inspired models of computation across diverse domains, whether modeling brain function, urban structures, or information ecosystems. Her research increasingly addresses societal implications of technology, particularly regarding gender equity and ethical AI development. 100 Brilliant Women in AI Ethics - 2025 Distinguished Alumni Ambassador 2024 at University of Alicante Women Leader of the Business Ecosystem 2024 Recognized in Spain's Guide to Women Leaders of the Business Ecosystem Navarro has supervised an extensive research team across multiple institutions, mentoring numerous PhD students, postdocs, and research assistants from diverse backgrounds. Her mentoring philosophy emphasizes building communities and education as pathways to change the world. She co-founded ACM-Women Europe and the womENcourage conference series, creating spaces for women in computing. Her research has been supported by significant projects including the UK-funded 'Dynamically Driven Verification of Systems With Energy Considerations,' where she served as principal investigator for the first UK project dedicated to formal verification of nonlinear hybrid systems. As director of AiDAs (Artificial intelligence and DAta science Research Lab), Navarro leads a multidisciplinary team exploring nature-inspired models of computation, learning, and evolution for complex systems. The lab's work integrates insights from neuroscience, mathematics, and computer science to develop new paradigms in AI. Navarro also contributes to TechnoLatinas, a self-organized community focused on supporting technologists and scientists from Latin America, and serves on the Advisory Council for Gender Music Tech, demonstrating her commitment to creating inclusive technology ecosystems.

• Deep Learning
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Dr. Ulf Krumnack is a researcher at the Institute of Cognitive Science, University of Osnabrück, affiliated with the LE Cognitive Science faculty. His research focuses on Deep Learning, Computer Vision, Machine Learning, and the theoretical foundations of analogical reasoning. He has contributed to projects on neural network architecture optimization, malaria detection via computer vision, and cognitive models for analogy-making. Krumnack teaches courses such as Advanced Topics in Deep Learning and Computer Vision, emphasizing practical applications in AI. His work integrates interdisciplinary approaches, bridging cognitive science and computational methods. Research interests include developing algorithms for structure from neural networks, visual analytics of gaze data, and ethical implications of AI. He collaborates on international projects like the I-Cog framework for integrated cognition. His publications span conferences like IEEE WACV and journals like the Journal of Computers. Teaching highlights include machine learning and computer vision seminars, alongside study projects on AI applications in animal communication. Krumnack’s contributions to cognitive systems emphasize human-like rationality and spatial cognition modeling.

Mark Crovellaمشاهده پروفایل

استاد

• Computer Science
• Networking
• Data Mining
• +۳ مورد دیگر

Mark Crovella is a Professor and Chair of Academic Affairs in the Faculty of Computing & Data Sciences at Boston University, with a primary appointment in the Department of Computer Science. He holds affiliations with the Department of Electrical and Computer Engineering, Graduate Program in Bioinformatics, Center for Information Systems and Engineering, and Division of Systems Engineering. His research spans networking, data science, bioinformatics, and algorithmic systems. Notable contributions include studies on network traffic analysis, machine learning applications in biology, and greedy routing algorithms in hyperbolic spaces. Education lineage traces back to prominent figures like d'Alembert and Laplace, highlighting a strong academic heritage. Awards include the Applied Networking Research Prize (2013) and Best Student Paper Award (2012). Over 150 peer-reviewed articles and multiple patents reflect his prolific output. His work bridges theoretical computer science with practical applications in bioinformatics and network engineering. Key grants and collaborations involve large-scale network measurement, cybersecurity, and systems biology. Advised doctoral students' work is documented in his CV. Active in curriculum development and academic leadership through his role as Chair of Academic Affairs.

Peter Pachowiczمشاهده پروفایل

دانشیار

• CubeSats
• Satellite Communications (SatCom)
• Space Communications (SpaceCom)
• +۶ مورد دیگر

Dr. Peter Pachowicz is an Associate Professor in the Department of Electrical and Computer Engineering at George Mason University (GMU). He leads research initiatives in CubeSats, satellite communications (SatCom), and space systems engineering within the College of Engineering and Computing (CEC). His work focuses on ultra-small satellite bus architectures, resilient systems, and rad-hard embedded software. He oversees the development of CEC's SatCom ground stations, including a 9.1-meter satellite dish and the ECE CubeSat Engineering Lab, supporting lunar missions and student projects. Dr. Pachowicz also manages a SmallSat Engineering certificate program and Space-Based Systems specialization for graduate students. Dr. Pachowicz holds a PhD, MS, and BS in Electrical and Computer Engineering from the AGH University of Science and Technology. His research has been funded by DARPA, the Air Force Office of Scientific Research (AFOSR), and industry partners. His early work explored intelligent systems, machine vision, and data fusion, with applications in defense and aerospace. Over a decade of industrial consulting experience includes roles at SAIC and U.S. Army NVL, focusing on transitioning theoretical frameworks to practical engineering solutions. His current projects include the NASA/GMU Landolt mission payload development (launching in 2028) and advancing antenna design for CubeSats. His research spans signal processing, embedded systems, and AI integration into aerospace systems. His team collaborates on student competitions and lunar relay systems, emphasizing hands-on learning and mission readiness. Publications highlight contributions to satellite subsystems, machine learning applications in defense, and adaptive algorithms for dynamic environments. His work bridges academia and industry, emphasizing real-world implementation of innovative engineering solutions.