جست‌وجوی استاد و پژوهشگر

Aline Villavicencioمشاهده پروفایل

استاد

• Lexical Semantics
• Multilinguality
• Cognitively Motivated NLP
• +۴ مورد دیگر

Professor Aline Villavicencio is a Chair in Natural Language Processing at the University of Sheffield's School of Computer Science. She holds a PhD and MPhil from the University of Cambridge and an MSc from the Federal University of Rio Grande do Sul (Brazil). Her research focuses on lexical semantics, multilinguality, and cognitively motivated NLP, with applications including Multiword Expression (MWE) treatment and text simplification for English and Portuguese. She has held a CNPq Research Fellowship (2007–2017) and currently leads projects like Modeling Idiomaticity in Human and Artificial Language Processing (EPSRC grant). Her roles include PC co-chair for CoNLL-2019, Area Chair for ACL-2019 and NAACL-2018, and co-chair of PROPOR 2018. She advises WiNLP, contributes to TACL, JNLE, and other journals, and collaborates with the Neurocomputational and Language Processing Lab in Brazil. Notable work includes corpus development (e.g., BRWAC for Brazilian Portuguese), idiomaticity detection, and cross-lingual transfer learning. Recent grants include £446k from EPSRC and £370k from Horizon Europe (Atrium). Key Projects: Modeling Idiomaticity, Cross-lingual Adaptation, Speech Segmentation Grants: EPSRC (£446k), Horizon Europe (£370k), Royal Society (£74k) Publications: Over 100 papers in ACL, EMNLP, and journals like Natural Language Engineering . Her lab work involves developing NLP tools for under-resourced languages and exploring neural models' limitations in idiomatic understanding. She co-edited books on cognitive aspects of language acquisition and MWE processing, and her teaching includes advanced NLP modules.

Hugues MOUNIERمشاهده پروفایل

استاد

• Control Theory
• Differential Flatness
• Controllability Analysis
• +۵ مورد دیگر

Professor Hugues MOUNIER is affiliated with Paris Saclay University and the Laboratoire des Signaux et Systèmes (L2S) at CentraleSupélec. His primary role is as a Professor leading the COMEDY team, focusing on control systems and their applications. He has been a permanent member of L2S since 2010 and joined Paris Saclay University in 2008. His research spans theoretical and applied domains: differential flatness (for nonlinear and infinite-dimensional systems), Liouvillian systems, controllability/observability properties, and applications in contemplative neuroscience, physiological systems, and engineering systems like drilling, automotive, and network control. He leads the ANR project MindMadeClear, integrating mathematical models for meditation practices with physiological and phenomenological analysis. Key contributions include modeling oilwell drilling vibrations, model-free control strategies for vehicles and data centers, and neuroscientific studies using EEG classification for meditation states. His work bridges abstract theory (e.g., flatness analysis for HPA axes) with real-world applications (e.g., congestion control, energy management). He collaborates internationally, presenting at venues like ECC, IFAC, and IEEE conferences. His lab teams include SYCOMORE and MODESTY, focusing on dynamical systems modeling and estimation. No awards are explicitly listed, but his extensive peer-reviewed publications reflect sustained academic impact.

Bo Tanمشاهده پروفایل

دانشیار

• Wireless Communications
• Signal Processing
• Machine Learning
• +۷ مورد دیگر

Bo Tan is an Associate Professor in Communications Engineering and Signal Processing at the Department of Electronic and Electrical Engineering, University College London (UCL). He previously held positions as Associate and Assistant Professor at Tampere University, Finland, where he retains a Docent title. His research focuses on radio signal processing, wireless communications, integrated sensing and communication (ISAC), machine learning applications in healthcare, and radar systems. He has coordinated major projects such as ANCHOR (Horizon Europe MSCA Doctoral Networks) and SPHERE-DNA (Finland Research Council), and serves as an Associate Editor for IEEE Wireless Communications Letters. Education: PhD in Engineering, University of Edinburgh (United Kingdom) Postdoctoral Researcher roles at: University College London (Computer Science & Electronic Engineering) University of Bristol (Electrical and Electronic Engineering) Research Interests: Wireless communication systems (5G/6G, THz, mmWave) Radar-communication integration and dual-functional systems Machine learning for signal processing and healthcare Integrated sensing and communication (ISAC) architectures Non-invasive healthcare monitoring via passive sensing Key Projects (2021–2025): ANCHOR (2025–2029): Research Coordination Committee lead SPHERE-DNA (2021–2024): PI focusing on federated learning for eHealth ACCESS (2021–2025): PI on wireless network security DIOR (2022–2027): Coordinator for H2020 MSCA Professional Roles: Vice Chair, IEEE Finland AP/ED/MTT Chapter Reviewer for IEEE/ACM/IET journals Labs/Teams: Leading the SPHERE-DNA initiative on privacy-preserving healthcare systems Active contributor to the IEEE's wireless communication standards

Michael Weharمشاهده پروفایل

مدرس

• Computer Science
• Algorithms
• Computational Art
• +۷ مورد دیگر

Michael Wehar is a Lecturer in Computer Science at Bryn Mawr College , where he teaches Introductory Programming Courses. He is a multidisciplinary researcher and developer with a focus on algorithms , computational art , and software engineering , creating innovative tools that bridge computer science with creative applications. Co-founder of AlgoArt.org , a platform for algorithmic art creation and exhibition Creator of Word of The Hour , a multilingual vocabulary learning platform Co-developer of Treegle Dictionary , a structured definition platform His research spans computational complexity, human-computer interaction, and educational technology. Key areas include: Algorithmic Art : Generative design systems, interactive visualizations Pattern Matching : Matrix algorithms, Voronoi diagrams, formal verification Language Technology : Multilingual dictionaries, crowdsourced translation systems Educational Tools : Git repository analysis, interactive learning platforms His 15 most recent publications focus on topics ranging from 2D pattern matching to ETH-based complexity lower bounds , with significant contributions to automata theory and algorithm design. He has received academic recognition including the Best Faculty Poster at CCSC:EA 2022 and Honorable Mention at IFoRE 2022 . As a dedicated mentor, he has guided over 100 students across institutions like Swarthmore College, Temple University, and University at Buffalo in projects spanning: Web development frameworks AI applications in art and education Mobile productivity tools Language learning platforms Game development projects

Yong Hoon Kimمشاهده پروفایل

دانشیار

• Connected and autonomous vehicles (CAVs)
• Intelligent transportation systems (ITS)
• Advanced traveler information systems
• +۲ مورد دیگر

Yong Hoon Kim is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Windsor, Canada. He specializes in intelligent transportation systems with a focus on connected and autonomous vehicles (CAVs), traffic flow modeling, and cybersecurity in transportation networks. Education : BSc & MSc in Civil Engineering from University of Seoul, South Korea PhD in Civil Engineering from Purdue University, West Lafayette, IN, USA Research Interests : Connected and autonomous vehicles (CAVs) integration in urban environments Intelligent transportation systems (ITS) and traffic flow optimization Cybersecurity challenges in vehicle-to-vehicle communication networks Mobility data privacy and advanced traveler information systems Recent Publication Trends : His recent work (2023) explores vehicle malware modeling, collision-free traffic simulation, and mobility data analysis, while earlier studies focus on CAV infrastructure planning and V2V communication dynamics.

Peppino Fazioمشاهده پروفایل

دانشیار

• Telecommunications
• Wireless Networks
• Vehicular Networks
• +۹ مورد دیگر

Peppino Fazio is an Associate Professor at the Department of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice. He holds a degree in Computer Engineering (2004) and a PhD from the University of Calabria (2008). His research focuses on telecommunications, wireless networks, and quantum key distribution, with contributions to vehicular networks, cybersecurity, and IoT systems. Key career milestones include post-doctoral research in Spain (2008), involvement in EU projects (e.g., ORACOLO), and leadership in StartCup-winning ventures like SPITCH (2014). He has authored over 130 publications, with recent work addressing quantum networks, deep learning for intrusion detection, and multi-layer robotic swarm management. Received StartCup Calabria 2012 and Lamarck Award 2014. Co-founder of SPITCH and developer of the Intelligent Remote Controller (IRC). His research spans theoretical and applied domains, including network emulation, mobility prediction in 5G/6G systems, and medical neuroscience modeling through network operators.

Aline Parreauمشاهده پروفایل

پژوهشگر

• Discrete Mathematics
• Combinatorial Optimization
• Combinatorial Game Theory
• +۳ مورد دیگر

Aline Parreau is a junior researcher at CNRS, affiliated with the GOAL team of the LIRIS laboratory at Université Claude Bernard Lyon 1. Her research focuses on discrete mathematics, combinatorial games, graph theory, and positional games. She earned her PhD in Discrete Mathematics from Université Joseph Fourier (Grenoble) in 2012, followed by postdoctoral research at the University of Liège. She coordinates the ANR project P-GASE, studying combinatorial and algorithmic aspects of positional games on graphs. PhD: Identification problems in graphs (2012), supervised by Sylvain Gravier. Postdoctoral work: Discrete Mathematics at University of Liège (2013–2014). Her teaching includes operational research and computer science courses at various institutions, including Lyon 1 University and Lille 1 University. She is actively involved in scientific mediation through initiatives like Maths à modeler and MATh.en.JEANS, promoting mathematical research to the public. Key activities include advising PhD and MSc students, organizing seminars, and contributing to research on graph theory, combinatorial games, and algorithmic optimization.

Robin Thomasمشاهده پروفایل

استاد

• Graph Theory
• Combinatorics
• Combinatorial Optimization
• +۴ مورد دیگر

Robin Thomas was a Regents' Professor at the School of Mathematics , Georgia Institute of Technology . He specialized in Graph Theory , Combinatorics , and Algorithms , with notable contributions to the Four Color Theorem and its generalizations. His research explored graph minors, topological graph theory, and efficient algorithms. Research interests included Hamiltonian graphs on surfaces, embeddings of graphs, and structural graph theory. He collaborated extensively on projects funded by the National Science Foundation . Professional service: Editor, Journal of Combinatorial Theory Series B Editor, Journal of Graph Theory Editor, Graphs and Combinatorics Editor, Advances in Combinatorics Advising & Legacy: Supervised 19 doctoral students, many of whom hold academic or industry positions. His work on the Four Color Theorem revolutionized graph theory. Contact robintho@gmail.com for legacy inquiries.

Nathan A. Ledeboerمشاهده پروفایل

استاد

• Clinical Microbiology
• Molecular Pathology
• Infectious Disease Diagnosis
• +۶ مورد دیگر

Nathan A. Ledeboer is a Professor at the Medical College of Wisconsin (MCW) and holds dual roles as Medical Director for both the Clinical Microbiology and Molecular Diagnostics Laboratories. He oversees assay development, laboratory operations, and consults on diagnostic testing for infectious diseases. His research focuses on rapid molecular diagnostic technologies, host response to infections, AI-driven imaging, respiratory virus epidemiology, and antimicrobial resistance. Ledeboer’s work bridges clinical practice and innovation, emphasizing translational research to improve diagnostic accuracy and patient outcomes. His research interests include molecular techniques for infectious disease detection, host-pathogen interactions, and leveraging digital tools for medical diagnostics. Notable contributions include sepsis diagnostics, pharyngitis biomarker studies, and home-based respiratory virus testing. He collaborates on large-scale pathogen identification projects and evaluates diagnostic technologies’ clinical and economic impacts. Recent publications highlight advancements in sepsis diagnostics, pharyngitis pathogen analysis, and antimicrobial resistance. His work frequently addresses gaps in clinical decision-making and the integration of novel technologies into emergency care. Ledeboer’s leadership in laboratory medicine ensures cutting-edge practices are implemented to enhance patient care standards.

Hubert Brücklمشاهده پروفایل

استاد

• Thin Films
• Magnetism
• Sensors
• +۳ مورد دیگر

Hubert Brückl is a Professor and Head of the Department for Integrated Sensor Systems at the University for Continuing Education Krems. He holds a PhD and habilitation in Physics from the University of Regensburg and has held key roles at institutions like the Technical University of Darmstadt, IFW Dresden, and the AIT Austrian Institute of Technology. His research focuses on thin films, magnetism, sensors, and micro/nanotechnology, with significant contributions to machine learning applications in materials science. Brückl's scientific career includes leadership in over 15 funded research projects, such as the development of AI-based corrosion monitoring systems and advanced magnetic sensors. He has authored numerous publications in high-impact journals, including Nature Scientific Reports , Physical Review Applied , and IEEE Transactions on Magnetics . His work spans interdisciplinary areas, combining physics, engineering, and data science to create innovative sensor technologies. Current projects emphasize AI-driven predictive modeling of materials properties and high-precision magnetic sensor fabrication. Brückl's lab integrates cutting-edge facilities for nanotechnology and sensor development, collaborating with industry partners like Siemens and aerospace firms. His research addresses challenges in sustainable materials, biomedical diagnostics, and industrial monitoring systems.

• Computational Neuroscience
• Machine Learning
• Cognitive Science
• +۳ مورد دیگر

Qiong Zhang is an Assistant Professor jointly appointed in the Psychology Department and Computer Science Department at Rutgers University. Her research bridges human learning and machine learning, focusing on comparing human memory systems with AI solutions and informing intelligent machine design through cognitive insights. She holds a Ph.D. from Carnegie Mellon University's Machine Learning Department under the School of Computer Science and completed postdoctoral training at Princeton University. Education: Ph.D., Machine Learning, Carnegie Mellon University (School of Computer Science) Postdoctoral Training, Princeton University Her research investigates cognitive constraints in memory systems and their neural bases. She employs computational modeling, behavioral experiments, and neural imaging to explore how memory optimizes performance under constraints. Recent work includes an NSF-funded project on external cue benefits/detriments in memory search. Her lab's findings aim to enhance memory interventions and inform AI design. Grants and funding include support from the National Science Foundation and Rutgers Brain Health Institute. She explores interdisciplinary topics like episodic memory in storytelling (comparing humans and LLMs), and cognitive resource modeling during memory encoding.

Ben Wuمشاهده پروفایل

دانشیار

• Optical Communication
• Neuromorphic Computing
• Photonics
• +۳ مورد دیگر

Ben Wu, Ph.D., is an Associate Professor in the Department of Electrical & Computer Engineering at Rowan University’s Henry M. Rowan College of Engineering. He holds a B.S. from Nankai University (2008) and a Ph.D. from Princeton University (2015). His research focuses on photonics, including photonic neuromorphic computing, free-space optical communication, and optical imaging. Dr. Wu’s work emphasizes high-speed, low-latency photonic systems for applications in communication and artificial intelligence. He leads the Ben Wu Lab, which explores photonic neural networks, lidar signal processing, and secure optical communication systems. His research has been supported by grants from organizations like the National Science Foundation and NEC Laboratories America. Notable awards include the 2018 Inspira Health Award. Dr. Wu actively advises graduate students and postdoctoral researchers, with openings for scholars interested in optics, photonics, and wireless communication. His lab collaborates on projects such as noninvasive 3D medical imaging and secure key distribution systems.

• Control Systems
• Water Resource Management
• Data-Driven Methods
• +۳ مورد دیگر

Luis Romero Ben is a Researcher at the Department of Automatic Control, Universitat Politècnica de Catalunya (UPC). His work focuses on advanced monitoring and control systems for water distribution networks, emphasizing real-time leak detection, data-driven methodologies, and sensor network optimization. He is affiliated with the IRI (Institut de Robòtica i Informàtica Industrial) research institute. Key projects include: FUSAGUA (CSIC Project): Real-time sensor fusion for water leak monitoring (2025–). RUBIES (European Project): Pollution-based control of urban drainage systems (2021–). Research interests revolve around: Hydraulic modeling and state estimation (e.g., Unscented Kalman Filters). Graph-based and machine learning techniques for anomaly detection. Optimal sensor placement using genetic algorithms and clustering. Comparative analysis of model-based vs. data-driven approaches. Publications highlight contributions in leak localization algorithms, network resilience strategies, and interdisciplinary methods bridging physics-based models with modern data science.

Gordon Kindlmannمشاهده پروفایل

دانشیار

• Biomedical Image Analysis
• Scientific Visualization
• Systems
• +۵ مورد دیگر

Gordon Kindlmann is an Associate Professor of Computer Science at the University of Chicago, affiliated with the Systems Group research community. His work bridges computational imaging science and visualization theory, focusing on biomedical applications and machine learning integration. He leads projects in diffusion MRI analysis, surgical planning tools like SlicerDMRI, and theoretical advancements in visualization design. Research Interests: Biomedical Image Analysis Scientific Visualization Theory High Performance Computing Medical Imaging Algorithms Machine Learning Applications Recent Articles Trends: His work emphasizes cardiovascular modeling (e.g., aortic dissection prediction) and visualization validation techniques. Recent collaborations include optimizing visualization tools for scalability and accuracy in threaded data exploration. Awards: None explicitly listed in provided text. Grants/Advising: Involved in CDAC Discovery Grants (2019) and actively supports student research, though specific advisees are not listed here. His lab develops open-source tools like Diderot for tensor field visualization. Labs & Teams: Member of the Systems Group, a collaborative environment advancing systems research, programming languages, and software engineering.

Christian Vogtمشاهده پروفایل

مدرس

• IoT and Embedded Systems
• Wireless Sensor Networks
• Medical Electronics
• +۳ مورد دیگر

Dr. Christian Vogt Dr. Christian Vogt is a Lecturer at the Department of Information Technology and Electrical Engineering within the Center for Project-Based Learning at ETH Zürich. His research focuses on IoT systems, embedded electronics, and wearable technology with applications in agriculture, healthcare, and urban computing. He specializes in energy-efficient sensor networks, flexible electronics, and real-time data transmission systems. Research Interests Vogt's work bridges hardware innovation and software optimization, emphasizing practical implementations through project-based learning. Key areas include: IoT and Wireless Sensor Networks Low-power embedded machine learning Wearable biomedical devices Flexible/stretchable electronics Ultra-wideband and radar-based sensing Publications Recent work highlights energy-efficient livestock monitoring systems using LoRa, battery-free sensor nodes powered by human body energy, and real-time gesture recognition with novel sensors. His research often involves interdisciplinary collaborations between computer science, electrical engineering, and biomedical applications. Affiliations ETH Zürich - Center for Project-Based Learning Department of Information Technology and Electrical Engineering Contact: christian.vogt@pbl.ee.ethz.ch