جست‌وجوی استاد و پژوهشگر

Rodrigo I. Silveiraمشاهده پروفایل

دانشیار

• Computational Geometry
• Combinatorial Geometry
• Geographic Information Science (GIS)
• +۷ مورد دیگر

Rodrigo I. Silveira is an Associate Professor in the Department of Mathematics at Universitat Politècnica de Catalunya (UPC), where he conducts research in computational and combinatorial geometry. He is a member of the UPC research group on Discrete, Combinatorial and Computational Geometry and has a strong academic background, having earned his PhD at Utrecht University under Marc van Kreveld and completed prior studies at the Universidad de Buenos Aires. His research focuses on Computational Geometry , particularly problems arising from Geographic Information Science (GIS) , such as map construction, trajectory analysis, and visibility. He also works on Graph Drawing and algorithms for geometric structures. His work combines theoretical algorithm design with practical applications in spatial data. His recent publications reflect a consistent trend in geometric algorithms, including shortest paths in complex environments (e.g., portalgons), Voronoi diagrams with color constraints, robot motion coordination, and map inference from GPS data. These works appear in top-tier journals and conferences such as Algorithmica , Computational Geometry: Theory and Applications , SoCG, WADS, and LATIN. He has received scientific recognition, including a Best Paper Award at AGILE 2009 and another at SpatialGems 2021. He has supervised several PhD students to completion, including Guilermo Esteban (2024) and Pilar Cano (2020), and continues to advise current students. Rodrigo has been deeply involved in the academic community, organizing major events such as the European Workshop on Computational Geometry (EuroCG 2023), Graph Drawing 2018, and the Intensive Research Program on Discrete Geometry (2018). He has served on the program committees of SoCG, WADS, LATIN, and CCCG, and has chaired tracks for EGC and CG:YRF. His work is supported by collaborations with leading researchers such as Kevin Buchin, Maarten Löffler, Prosenjit Bose, and Vera Sacristán, and he contributes to both theoretical advances and practical implementations in geometric computing.

Camil Demetrescuمشاهده پروفایل

استاد

• Performance profiling
• Programming languages
• Algorithmics
• +۳ مورد دیگر

Camil Demetrescu is a Professor of Computer Science at Sapienza University of Rome, with a Ph.D. in Computer Engineering from the same institution (2001). His research spans performance profiling, programming language design, algorithmics, and computer security, focusing on software reliability and optimization. Education: Ph.D. in Computer Engineering from Sapienza University of Rome (2001) Research Interests include performance analysis of software systems, graph algorithm implementation, incremental computing, symbolic execution, and computer security. As a glider aircraft pilot, he combines technical rigor with a passion for aviation. Recent Publications (2011-2022) address concolic execution, path profiling, runtime code replacement, and symbolic fuzzer development. Key themes: software diagnostics, program analysis, and security engineering. Conference Contributions : Active in PLDI, ICSE, ASE, and SPLASH series as author and committee member since 2011.

Maximilian Pfostمشاهده پروفایل

دانشیار

• Educational Psychology
• Reading Development
• Self-Regulated Learning
• +۳ مورد دیگر

Maximilian Pfost is an Associate Professor at the University of Bamberg's Department of Educational Research, Faculty of Human Sciences and Education. His work focuses on self-regulated learning, reading comprehension, and literacy development across educational stages. Education: Habilitation (2016), PhD in Psychology (2011), Diploma in Psychology (2008) Professional Positions: Associate Professor (since 2017), Assistant Professor (2011-2017), Research Scientist (2008-2011) His research examines: Self-regulated learning mechanisms in higher education Impact of digital media on emergent literacy Interrelations between reading motivation and comprehension Longitudinal studies on academic self-concept development Recent publications highlight his focus on academic risk-taking, error-based learning strategies, and digital tools for self-regulated learning. He employs interdisciplinary methodologies spanning educational psychology, literacy studies, and behavioral research. Scientific recognition includes: Habilitation Award, University of Bamberg (2016) Friedrich-Ebert-Foundation Scholarship (2003–2007) Collaborations include projects with Prof. Dr. Cordula Artelt and international engagements in Rwanda. His work appears in journals like Learning and Instruction , Frontiers in Education , and Reading and Writing .

Sherine Antounمشاهده پروفایل

استادیار

• Robotics
• Autonomous Navigation
• Biologically Inspired Perception
• +۲ مورد دیگر

Sherine Antoun is an Assistant Professor of Computer Science at Colorado Mesa University. He is based in Confluence Hall 335 and can be reached at 970.248.1148 or santoun@coloradomesa.edu. His research focuses on robotics and autonomous systems, particularly in navigation and perception using ultrasonic sensors. Dr. Antoun's educational background includes: PhD in Robotics and Applied Computer Science from the University of Wollongong, Australia Research Masters (MPhil) in Computer Science from the University of Wollongong, Australia BCS in Computer Science from the University of Wollongong, Australia Dr. Antoun's research spans robotics, autonomous navigation, and biologically inspired perception. He specializes in ultrasonic sensing, particularly CTFM (Chirp Time-Frequency Modulated) sensors, for applications in hostile environments. His work includes mimicking human echolocation for robot navigation and wall tracking algorithms. His interests also extend to signal processing for navigation, sensor fusion, and adaptive perception systems. He has published extensively on mobile robot navigation using single and multiple ultrasonic sensors. Dr. Antoun's recent publications (2019-2007) demonstrate a consistent focus on ultrasonic sensing for robot navigation. His work explores CTFM sensors for echo signal data mining, wall tracking, and corridor perception. He has also investigated biologically inspired techniques, such as mimicking blind navigation, to enhance robot autonomy in challenging environments. The research trends show an evolution from basic wall following (2007-2010) to more complex signal processing and data mining (2013-2019), indicating a progression towards sophisticated autonomous navigation systems. Dr. Antoun has not been listed as receiving any scientific awards in the provided information. Dr. Antoun is dedicated to student-centered teaching, adapting to diverse learning styles. He has served as a guest lecturer at several international conferences, including the IEEE Intelligent Systems Conference (2018) and the Biologically Inspired Cognitive Architectures conference (2015). However, no specific grants or funded projects are detailed in the provided text.

Maria Liakataمشاهده پروفایل

استاد

• Natural Language Processing
• Semantics and Discourse
• Social Media Analysis
• +۷ مورد دیگر

Maria Liakata is a Professor of Natural Language Processing at Queen Mary University of London, where she serves as Deputy Centre Lead and 'Health and Wellbeing' Theme Lead for the Centre for Human-Centred Computing within the School of Electronic Engineering and Computer Science. She leads multiple research initiatives focusing on applying NLP techniques to healthcare applications, particularly mental health monitoring through social media and longitudinal user-generated content analysis. Her research interests span Natural Language Processing, Semantics and Discourse, Social Media analysis, Machine Learning, BioNLP, and NLP for Mental Health. Dr. Liakata has made significant contributions to knowledge discovery from corpora, automation of scientific experimentation, and automatic extraction of information from scientific literature. Her work has practical applications in mental health monitoring, dementia diagnosis, and rumor verification systems. Her recent publications demonstrate a strong focus on longitudinal analysis of language for mental health applications, temporal modeling of user-generated content, and healthcare AI. She has developed novel techniques for detecting changes in user representations over time, which have applications in mental health monitoring and early dementia diagnosis. Her research bridges the gap between technical NLP advancements and real-world healthcare challenges. EPSRC/UKRI Turing AI fellowship award on Creating Time Sensitive Sensors from Language & Heterogeneous User-Generated Content (2019-2025) IBM Faculty Award for work on emotion sensing from heterogeneous mobile phone data EU Project PHEME co-investigator (2014-2017) studying the spread of rumours in social media Early Career Fellowship from the Leverhulme Trust (2010-2013) on reasoning with scientific articles Dr. Liakata supervises a diverse group of PhD students working on cutting-edge NLP applications for healthcare, including mental health monitoring, dementia diagnosis, and medical imaging analysis. She leads multiple substantial research grants totaling millions of pounds from EPSRC, MRC, Wellcome Trust, and industry partners. Her current projects include 'Addressing socio-technical limitations of LLMs for medical and social computing' and 'Social media, Smartphone use and Self harm in Young People (3S-YP study)'. She leads the 'Health and Wellbeing' research theme within the Centre for Human-Centred Computing and collaborates closely with the Centre for Multimodal AI. Her interdisciplinary research team combines expertise in NLP, machine learning, clinical psychology, and healthcare informatics to develop practical AI solutions for real-world health challenges.

• Automated vehicle systems
• Connected vehicles
• Mobility engineering
• +۵ مورد دیگر

Mauro Velardocchia is a Full Professor at the Polytechnic University of Turin , affiliated with the Department of Mechanical and Aerospace Engineering (DIMEAS) . With over 20 years of academic leadership, he specializes in automated vehicles, connected mobility systems, and advanced powertrain engineering . Research focus on vehicle dynamics, magnetic transmission systems, and energy-efficient automotive technologies Active in European and national research projects including OWHEEL, EFFEREST, and CliMAFlux Teaching contributions to Mechanical Engineering programs since 2000 His recent publications analyze autonomous off-road navigation, tracked vehicle dynamics, and digital twin technologies . Current research projects emphasize sustainable mobility (Goal 9), climate action (Goal 13), and engineering education (Goal 4). Key technical expertise in nonlinear vehicle modeling Leadership in EU-funded MSCA and Horizon Europe projects

Verner Peter Bingmanمشاهده پروفایل

استاد پژوهشی

• Animal Navigation
• Hippocampus
• Comparative Brain
• +۲ مورد دیگر

Verner Peter Bingman is a Research Professor at Bowling Green State University 's Department of Psychology within the College of Arts and Sciences. Holding a Ph.D. from the State University of New York-Albany, he teaches courses in ornithology and cognitive neuroscience. His research focuses on animal navigation and hippocampal function across vertebrate species. Research areas include: Spatial cognition in birds and arthropods Hippocampal neurobiology Comparative brain organization Environmental navigation cues Recent publications demonstrate interdisciplinary work spanning Neuroscience , Zoology , and Cognitive Science , with a 2021 study on whip spider refuge learning and 2020 research on age-related hippocampal changes in homing pigeons. His 2015 comprehensive review of avian hippocampal formation highlights enduring contributions to navigation research. Key collaborations include work with scientists from institutions across four continents. Lab studies involve advanced neuroimaging and behavioral tracking methodologies.

Bruce Doranمشاهده پروفایل

دانشیار

• Geographic Information Systems (GIS)
• Social Applications of GIS
• Commercial Gambling Impact Analysis
• +۵ مورد دیگر

Bruce Doran is an Associate Professor at the Australian National University (ANU) , affiliated with the Fenner School of Environment and Society . His research focuses on social applications of Geographic Information Systems (GIS) , particularly in commercial gambling impact analysis , mapping fear of crime , and Indigenous land management . Education: BSc(Hons) and PhD from ANU Teaching: Courses on GIS theory and practice (EVNS2015/6015), Social Applications of GIS (ENVS3045), and advanced remote sensing His work includes leading the ANU Grand Challenge Project "Mapping a New Path" (2020-2025), which integrates Indigenous and Western knowledge for community-led research. He has a long-standing partnership with the Yawuru people of Western Australia, focusing on GIS tools for Native Title decision-making. Research Trends: His recent articles emphasize ecosystem accounting , Indigenous cultural landscapes , and spatial modeling for conservation . Key themes include cross-disciplinary GIS applications, Indigenous knowledge systems, and environmental policy reform. Scientific Awards: ANU Vice Chancellor's Award for Indigenous Education (2016) Collaborations: Co-led projects with Associate Professor Janelle Stevenson , Professor Albert Van Dijk , and Dr Lorrae van Kerkhoff . Active in Indigenous estate mapping, gambling harm studies, and wildlife-environment interactions.

• Perception and Robotics
• Computer Vision
• Unmanned Aerial Vehicles (UAVs)
• +۴ مورد دیگر

Claude PEGARD is a University Professor of Perception and Robotics at Université de Picardie Jules Verne (UPJV) , France, affiliated with research unit UR 4290. His office is located in PR-305 and he can be reached via internal phone extension 5922. His research lies at the intersection of computer vision, robotics, and intelligent control . Over three decades he has advanced autonomous navigation of aerial vehicles , sensor fusion between infrared and visible cameras , robust human detection , and fuzzy-logic-based flight control . Recent work explores AI applications in healthcare , highlighting both opportunities and ethical limits. Vision-based UAV navigation and path planning Photometric visual servoing for micro-air vehicles Multi-spectral human detection for search-and-rescue Nonlinear and fuzzy control of quadrotor platforms His publication trajectory from 1990-2024 shows a clear evolution from foundational work on omnidirectional vision and mobile-robot localization to cutting-edge neural-network-driven control and AI ethics. The 2020-2024 articles emphasize AI integration in safety-critical systems , robust control under uncertainty , and real-time vision algorithms . Laboratory & Teams: While the specific laboratory name is not stated, Prof. PEGARD leads activities within the Perception and Robotics group at UR 4290, mentoring graduate students and collaborating on UAV platform development and vision-based control systems.

• Vehicle Mechatronics
• Embedded Control Systems
• Reinforcement Learning
• +۴ مورد دیگر

Dr. Aradi Szilárd serves as Associate Professor at Budapest University of Technology and Economics, Faculty of Transportation Engineering, Department of Control for Transportation and Vehicle Systems. He also holds a Senior Research Fellow position at SZTAKI since 2022. His academic career shows steady progression from PhD Student (2005-2009) to Assistant Lecturer (2009-2016), Senior Lecturer (2016-2021), and finally Associate Professor (2021-present). His educational background includes an MSc in Transportation Engineering (2005) and PhD (2015). His research spans vehicle mechatronics, embedded control systems, reinforcement learning applications in transportation, and railway traffic management. Dr. Aradi has led significant projects including TruckDAS (2009-2011), Integrated Railway Energy System (2013-2015), Bosch R&D Project 'Umbrella' (2014-2016), VKE 2018-40 (2018-2022), and the Autonomous Systems National Laboratory (2020-present). His recent publication trend reveals a strategic shift toward reinforcement learning applications in transportation systems, with particular emphasis on rail traffic optimization and autonomous vehicle control. Since 2020, over 70% of his work involves reinforcement learning techniques applied to real-world transportation challenges, demonstrating his commitment to bridging theoretical AI with practical engineering solutions. Dr. Aradi teaches Vehicle On-board Systems I-II, On-board Communication, Automotive Environmental Sensing, and I&C Technologies courses while supervising PhD students. His industrial collaborations with Bosch, Siemens, and other transportation technology companies provide valuable real-world context for his academic work. His research laboratory focuses on vehicle mechatronics, with specialized facilities for railway traffic control, automotive environmental sensing, and reinforcement learning applications. The department maintains strong connections with industry partners including HungaroControl, Műszer Automatika, PowerQuattro, SWARCO Traffic Hungária, Robert Bosch, and SIEMENS.

• Autonomous Vehicle Control
• Reinforcement Learning
• Traffic Management Systems
• +۵ مورد دیگر

Bécsi Tamás is an Associate Professor at the Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering, Budapest University of Technology and Economics. His academic career spans from PhD student (2002-2005) to Professor's Assistant (2005-2009), Senior Lecturer (2009-2014), and finally Associate Professor (2014-present). His research primarily focuses on autonomous vehicle control systems, reinforcement learning applications, and transportation automation across road, rail, and air domains. His research interests center on Autonomous Vehicle Control and Reinforcement Learning methodologies for transportation systems. Key areas include sensor fusion for automotive perception, motion planning algorithms, particle filtering techniques, and multi-agent traffic control systems. His work bridges theoretical control theory with practical implementations in vehicle mechatronics and transportation infrastructure. Analysis of his 15 most recent publications reveals a dominant focus on reinforcement learning applications (80% of works), particularly in autonomous driving (path planning, lane keeping) and traffic management (signal control, highway platooning). Recent trends show increasing integration of Rapidly-exploring Random Trees (RRT) with RL, particle filtering innovations for localization, and multi-object tracking advancements for automotive perception systems. His research maintains strong connections to real-world validation through field tests and industrial collaborations. His academic journey includes an MSc in Transportation Engineering (2002) and PhD (2008) from BUTE. Teaching responsibilities cover Computing Science I-II and Control Theory I-II courses, alongside specialized Erasmus programs in Intelligent Solutions in Transportation and Transportation Automation Research Techniques.

Eric Desjardinsمشاهده پروفایل

دانشیار

• Philosophy of Biology
• Philosophy of Science
• Environmental Philosophy
• +۳ مورد دیگر

Eric Desjardins is an Associate Professor in the Department of Philosophy at Western University , affiliated with the Rotman Institute of Philosophy . His research focuses on the philosophical implications of biological and environmental sciences, particularly historical contingency, biological entanglement, and socio-ecological coevolution. Education: Ph.D. in Philosophy from the University of British Columbia. His work bridges theoretical representations with real-world applications, addressing ethical decision-making in human-impacted environments. Key projects include: Replaying Life’s Tape: Historical Contingency and the Historical Sciences (SSHRC Insight Grant, 2020–2025) The Extended Synbio Network: Synthetic Biology as Social Practice Socio-Ecological Resilience and Coevolution: Tracking Human-Nature Dynamics He teaches undergraduate and graduate courses such as Philosophy of Science , Synthetic Biology and Philosophy , and Environmental Philosophy . His publications span topics like evolutionary biology, resilience theory, and AI in immunology.

Sanda-Maria Avramمشاهده پروفایل

مدرس

• Authorship Attribution
• Artificial Intelligence
• Natural Language Processing
• +۷ مورد دیگر

Dr. Sanda-Maria Avram is a faculty member at Babeș-Bolyai University in Cluj-Napoca, Romania, where she teaches in the Faculty of Mathematics and Computer Science. She currently instructs courses in Operating Systems for bachelor's students and oversees the elaboration of Bachelor Theses. Her teaching approach emphasizes practical application and student engagement in both undergraduate and master's programs, having recently completed the sixth iteration of her Adaptive Web Design course with 81 master's students across six sections. Dr. Avram's research spans multiple domains with a current focus on authorship attribution through artificial intelligence, natural language processing, and stylometry. Her work aims to achieve and surpass AI-based results through mathematical approaches. Previously, her research encompassed knowledge discovery, data visualization, web mining, e-learning systems, and networking. She has developed several educational platforms including SINE, PULSE, and PULSE Extended for student evaluation in laboratory settings, addressing the specific needs of Romanian universities where laboratory sessions are mandatory and guided by a single tutor. Her publication record reveals a strong trend toward applying computational methods to solve practical problems in education and networking. Recent work focuses on linguistic analysis and authorship attribution using advanced AI techniques, while earlier publications address educational analytics and network routing protocols. She has demonstrated that integrated analytics using authentication data provide more reliable insights for e-learning environments than standard tools like Google Analytics. Dr. Avram leads a student research group focused on mathematical approaches to authorship attribution, encouraging students with strong mathematical skills to collaborate. She actively maintains academic profiles on Google Scholar, ResearchGate, and Academia.edu (under the names SandaDragos and SandaMariaAvram), where she has established a network of academic collaborators and shares her research findings with the broader scholarly community.

Thomas Needhamمشاهده پروفایل

دانشیار

• Geometry
• Topology
• Optimal Transport
• +۴ مورد دیگر

Thomas (Tom) Needham is an Associate Professor of Mathematics at Florida State University, where his work bridges pure geometry and topology with modern data-science challenges. Research Interests: Needham’s research centers on applying geometric and topological ideas—particularly optimal transport, Riemannian and symplectic geometry, and topological data analysis—to large and complex data sets. He develops theoretical frameworks, algorithms, and computational tools that reveal shape, structure, and relationships within high-dimensional data. Optimal transport theory and its generalizations (Gromov-Wasserstein, unbalanced transport) Metric and symplectic geometry in data contexts Topological summaries (persistence diagrams, Reeb/Merge trees) Statistical shape analysis and geometric statistics Funding & Support: His program is currently supported by the U.S. National Science Foundation through grants DMS–2324962 and CIF–2526630; prior support includes DMS–2107808. Laboratory & Collaboration: Needham collaborates extensively across mathematics, computer science, statistics, and application domains such as neuroscience and imaging. While no dedicated lab name is given, his projects involve multi-institutional teams and graduate students working at the intersection of geometry, topology, and data science.

Timo Kaiserمشاهده پروفایل

پژوهشگر

• Object Detection
• Multiple Object Tracking
• Person Re-identification
• +۳ مورد دیگر

Timo Kaiser is a doctoral researcher at the Institute of Information Processing (TNT) within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover. He has been working towards his Dr.-Ing. degree since May 2020, conducting research in computer vision with a focus on object detection and tracking systems. His educational background includes a Master of Science in Mechatronics from Leibniz University Hannover, where he focused on digital image processing. His master's thesis addressed the multiple people tracking problem using Conditional Random Fields. His undergraduate studies emphasized robotics. Kaiser's research interests span object detection, multiple object tracking, and person re-identification, with recent work extending into uncertainty quantification, biomedical image analysis, and neural network optimization. His projects include Multiple People Tracking and GreenAutoML4FAS, demonstrating both theoretical and applied research directions. Analysis of his publication record reveals a strong focus on advancing multiple object tracking methodologies, with recent work (2023-2025) expanding into uncertainty quantification, cell tracking for biomedical applications, and novel neural network architectures. His research shows increasing sophistication, moving from traditional tracking algorithms to incorporating deep learning and uncertainty modeling. As a researcher actively contributing to the computer vision community, Kaiser has established collaborations with prominent researchers like Bodo Rosenhahn and has published in top-tier venues including ICML, ICLR, ICCV, and IEEE Transactions. His GitHub activity demonstrates commitment to reproducible research with code repositories supporting his publications.