جست‌وجوی استاد و پژوهشگر

Lachlan D. Urquhartمشاهده پروفایل

مدرس ارشد

• Technology Law
• Human-Computer Interaction
• AI Ethics
• +۹ مورد دیگر

Dr. Lachlan D. Urquhart is a Senior Lecturer in Technology Law and Human-Computer Interaction at the University of Edinburgh's School of Law. He co-directs the Scottish Research Centre for Intellectual Property and Technology Law (SCRIPT) and leads the Regulation and Design (RAD) Lab. He is a director of the Centre for Research into Information, Surveillance, and Privacy (CRISP) and contributes to the Designing Responsible NLP Centre for Doctoral Training and the Institute of Design Informatics. Education: LL.B, Hons (Edinburgh); LL.M in IT & Telecoms Law, Distinction (Strathclyde); Ph.D in Computer Science (Nottingham). Research Interests: Focus on socio-technical aspects of designing, regulating, and living with emerging information technologies, including AI ethics, IoT, data privacy, cybersecurity, and responsible innovation. Projects: Principal Investigator of the £1.2m EPSRC 'Fixing the Future: Right to Repair and Equal-IoT' project; Co-Investigator on £9.75m Responsible NLP AI CDT and £3.2m EPSRC Trustworthy Autonomous Systems Governance Node. Visiting Roles: Turing Fellow (2020-22), Research Fellow at Universitá degli Studi di Milano (2022-23), and visiting researcher at Meiji University (2014).

Clément Malletمشاهده پروفایل

پژوهشگر

• Geospatial Computer Vision
• Remote Sensing
• Machine Learning
• +۴ مورد دیگر

Clément Mallet is a Senior Researcher and Director of the LASTIG laboratory at Université Gustave Eiffel, IGN, and École Nationale des Sciences Géographiques (ENSG) in Champs-sur-Marne, France. He leads research in geospatial computer vision, focusing on the intersection of remote sensing, computer vision, and machine learning. His responsibilities include overseeing 75 laboratory members and directing the STRUDEL research team focused on spatio-temporal information modeling. Education: Habilitation (HDR) in Geographical Information Science, Université Paris-Est (2016) PhD in Image and Signal Processing, Télécom ParisTech (2010) Engineering Degree in Geographical Information Science, ENSG (2005) Master's in Remote Sensing, Université Paris 6 (2005) Research Interests: Dr. Mallet specializes in multi-modal land-cover mapping, change detection, geohistorical image analysis, and airborne lidar processing. His work integrates deep learning with geospatial data analysis to solve complex problems in environmental monitoring, urban studies, and historical geography. Current research explores foundation models for earth observation and semantic change detection using hybrid data generation techniques. Publication Trends: Mallet's recent articles (2021-2025) demonstrate strong focus on deep learning applications for geospatial challenges: 40% address land-cover mapping innovations, 30% develop novel change detection methodologies, 20% advance lidar data processing, and 10% explore historical map analysis. His work consistently bridges computer vision theory with operational remote sensing applications. Awards and Recognition: Schwidefsky Medal from ISPRS (2016) 5x Outstanding Reviewer awards (CVPR/ECCV/ICCV 2017-2024) Best Paper Awards at GEOBIA 2016 and ISPRS 2014 Young Researcher Award from GDR ISIS (2010) EuroSDR Best PhD Thesis supervision (2020) Research Leadership: Directs multiple national and international projects including MAESTRIA (ANR-funded multi-modal EO analysis) and HIATUS (historical image analysis). Supervised 14+ PhD students in geospatial AI topics. Secured funding from ANR, CNES, EU H2020 (VOLTA, LandSense), and industrial partners. Leads the STRUDEL team developing cutting-edge methods for territory dynamics analysis. Professional Service: Editor-in-Chief of ISPRS Journal of Photogrammetry and Remote Sensing (2021-present). Organized major conferences including ISPRS Congress (2020-2022 Program Chair) and JURSE events. Active in ISPRS working groups since 2008, currently leading initiatives in large-scale machine learning applications for geospatial data.

Joseph Salmonمشاهده پروفایل

پژوهشگر

• Machine Learning
• Optimization
• Data Science
• +۳ مورد دیگر

Joseph Salmon is a Senior Researcher at Inria (Team Iroko) in Montpellier, working with the Pl@nNet team. He previously served as a Full Professor at Université de Montpellier from 2018 to 2024 and was a Junior member of the Institut Universitaire de France (IUF) from 2021 to 2024. His research focuses on machine learning, optimization, and data science, with applications in citizen science and crowd-sourcing. He leads the doctoral program 'Statistics and Data Science' at Université de Montpellier. Education: Ph.D. in Statistics and Image Processing (2010) from Université Paris Diderot, under supervision of Dominique Picard and Erwan Le Pennec. Earlier roles include Assistant Professor at Telecom Paris (2012-2018), postdoctoral work at Duke University (2011-2012), and visiting positions at UW Statistics (2018) and the Simons Institute (2022). Research interests span isotonic regression, convex optimization algorithms (e.g., PAVA), statistical learning theory, and applications in environmental AI (Pl@ntNet). His work bridges theory and practice, emphasizing scalable algorithms for high-dimensional problems. Key contributions include advancements in PAVA convergence analysis, Slope penalty optimization, and peer-reviewed frameworks for crowdsourced data. Grants include ANR VITE (variable importance/explainability) and CaMeLOt (Cooperative Machine Learning Optimization). Labs/Teams: Active in Inria's Iroko team and collaborates with Pl@ntNet's AI development. Maintains the STATLEARN conference and ML-MTP initiative in Montpellier.

Elaine Jing Zhaoمشاهده پروفایل

دانشیار

• Communication and Media Studies
• Communication Technology and Digital Media Studies
• Film, Television and Digital Media
• +۶ مورد دیگر

Associate Professor Elaine Jing Zhao is based at the School of the Arts and Media , University of New South Wales , with expertise in digital media economies, cultural production, and platform governance in transitional China and the Asia-Pacific region. She authored the monograph Digital China's Informal Circuits: Platforms, Labour and Governance and publishes in journals like New Media and Society and Global Media and Communication . Research Focus: Cultural implications of digital platforms, media globalization, and creative labor dynamics Editorial Roles: Board member, Communication Research and Practice ; reviewer for ARC grants and international journals Her research portfolio emphasizes platform governance , digital media policy , and cultural innovation in China's digital economy. Recent projects examine China's platform internationalization and informal media economies. She supervises PhD candidates in these areas and has secured funding from both Australian Research Council and National Social Science Foundation of China . Scientific Awards: 2020 Faculty of Arts & Social Sciences Dean's Research Award for Best Monograph 2018 ARC Kathleen Fitzpatrick Laureate Fellowship Mentoring Scheme Award 2012 Australia-China Youth Dialogue Delegate 2010 Oxford Internet Institute Summer Doctoral Programme Participant She contributes to digital China scholarship through the Anthem book series and previously worked in the telecom and mobile internet industry before her academic career. Her work bridges sociocultural analysis and platform economy research.

• Cryptography
• Information Security
• Authenticated Encryption
• +۳ مورد دیگر

Assoc Prof Wu Hongjun is an Associate Professor at the Division of Mathematical Sciences, School of Physical & Mathematical Sciences, Nanyang Technological University (NTU). His research focuses on cryptography and information security, with notable contributions to lightweight authenticated encryption algorithms like TinyJAMBU and ACORN, as well as cryptanalysis of stream ciphers (e.g., ZUC, HC-128) and hash functions (e.g., JH, SHA-3 candidates). His academic career includes over 15 years of contributions to cryptographic standards, IoT security frameworks, and secure cloud data management. Key areas of expertise encompass symmetric-key cryptography, algorithm design for resource-constrained devices, and vulnerability analysis of cryptographic primitives. Prof Wu has authored influential papers on authenticated encryption modes (AEGIS, MORUS), lightweight cipher optimizations (ACORN), and cryptanalysis techniques applied to Feistel networks and stream ciphers. His work bridges theoretical cryptography with practical implementations across telecommunications, IoT, and cloud computing domains.

Fred A. Kishمشاهده پروفایل

استاد

• Photonics
• Optoelectronic Devices
• Compound Semiconductor Materials
• +۳ مورد دیگر

Fred A. Kish is the MC Dean Distinguished Professor and Director of the NC State Nanofabrication Facility at North Carolina State University. He holds a Ph.D. in Electrical Engineering from the University of Illinois at Urbana-Champaign (1992). His research focuses on Photonics, Optoelectronic Devices, and Compound Semiconductor Materials , with emphasis on photonic integrated circuits (PICs), quantum information science, and semiconductor material engineering. He has co-invented foundational technologies for LEDs, VCSELs, and large-scale PICs, contributing over $7B in commercialized products. His leadership includes roles at Hewlett-Packard, Agilent Technologies, and Infinera Corporation, where he pioneered optical communication systems. Dr. Kish is a Fellow of the National Academy of Inventors, Optica, and IEEE, and a member of the National Academy of Engineering. His awards include the IEEE David Sarnoff Award and the John S. Risley Entrepreneur of the Year Award. He has authored 170+ peer-reviewed publications, 135+ patents, and 5 book chapters. His current work drives advancements in wide bandgap semiconductors and photonic integration for next-generation communications and sensors. Labs/Teams: Directs the NC State Nanofabrication Facility, a hub for semiconductor innovation. Collaborates on the CLAWS Hub, a $39.4M CHIPS Act-funded regional semiconductor innovation initiative.

Sadaf Salehkalaibarمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Generative models
• +۵ مورد دیگر

Sadaf Salehkalaibar is an Assistant Professor in the Department of Computer Science at the University of Manitoba, Winnipeg, Canada. She holds an office in the EITC building (E2-416) and has previously held academic positions at the University of Tehran, University of Toronto as a research associate, and visiting roles at McMaster University, Telecom Paristech, and National University of Singapore. Her research focuses on explainable artificial intelligence, generative models, and information theory with an emphasis on rate-distortion-perception tradeoffs in video and image processing. Her educational background includes teaching courses such as Signals and Systems, Digital Signal Processing, and Network Security at the University of Tehran. She currently teaches COMP4190 (Artificial Intelligence) at the University of Manitoba. Research interests revolve around developing efficient algorithms for AI systems, with key contributions in learned video compression, federated learning, and privacy-preserving techniques. Notable work includes the M22 algorithm for communication-efficient federated learning and the NSERC Discovery Grant-funded project on data-driven learning efficiency. Recent publications highlight advancements in perception loss functions, Gaussian vector source analysis, and secure distributed hypothesis testing. She actively serves on editorial boards (e.g., IEEE Transactions on Communications) and conferences (ISIT, ITW). Awards include the prestigious NSERC Discovery Grant (2025). Supervision highlights 13 MSc students at the University of Tehran, focusing on topics like privacy-preserving systems and distributed learning. Labs/teams: Leads research group at University of Manitoba focusing on AI and information theory applications in multimedia systems.

Ioannis Emirisمشاهده پروفایل

استاد

• Computational Geometry
• Algebraic Algorithms
• Robotics
• +۴ مورد دیگر

Ioannis Z. Emiris is a Professor in the Department of Informatics & Telecoms at the National & Kapodistrian University of Athens and concurrently serves as President and General Director of the ATHENA Research Center in Greece. He holds a BSc in Computer Science from Princeton University (1989) and a PhD in Computer Science from UC Berkeley (1994). His research spans computational geometry, algebraic algorithms, robotics, structural bioinformatics, and optimization. He is a leading expert in sparse elimination theory, geometric modeling, and algorithmic algebra. Affiliations: ATHENA Research Center, National & Kapodistrian University of Athens, INRIA Sophia Antipolis (France via joint AROMATH team). Education: BSc (Princeton), PhD (UC Berkeley). Research Interests Emiris's work focuses on geometric algorithms, algebraic systems, and their applications. His contributions include advancements in sparse elimination theory, computational geometry for high-dimensional data, and robotics. He has developed algorithms for polynomial system solving, Voronoi diagrams, and geometric predicates for ellipses. Articles Overview His recent work bridges theoretical advances with practical applications, such as deep learning for protein structure prediction (HydraProt) and geometric algorithms for high-dimensional data analysis. He explores intersections between algebraic geometry and computational methods, with applications ranging from robotics to bioinformatics. Scientific Awards Best Paper Award at ISSAC 2003 and 2010 MSCA Network GRAPES (2019-2023) Advising & Grants Emiris has supervised numerous students and researchers, contributing to interdisciplinary projects. He has secured grants for initiatives like the GRAPES network and has led teams in algorithm design and geometric software development. His work on MARS (Maple/Matlab/C Resultant-Based Solver) exemplifies his focus on practical algorithm implementation. Labs & Teams He directs the Lab of Geometric & Algebraic Algorithms and collaborates with the AROMATH team at INRIA. His research group develops open-source tools for computational geometry and algebraic computations.

• Cybersecurity
• Blockchain Technology
• Internet of Things (IoT)
• +۳ مورد دیگر

Prof. Maryline Laurent is a Professor at Telecom SudParis, affiliated with the SAMOVAR research laboratory. Her work focuses on cybersecurity, privacy-preserving technologies, blockchain applications, and IoT security. She has contributed to numerous high-impact publications and conferences, addressing challenges in secure healthcare systems, decentralized identity management, and privacy in distributed systems. Her research spans cryptographic protocols, access control mechanisms, and compliance with EU data protection regulations. Key areas of expertise include secure communication protocols for IoT, blockchain-based solutions for healthcare, and privacy-enhancing technologies. She has collaborated on projects such as self-sovereign identity frameworks, anonymized data aggregation, and privacy-preserving smart grid systems. Her work emphasizes practical methodologies for assessing re-identification risks in anonymized datasets and designing secure systems compliant with evolving regulations. Prof. Laurent’s contributions extend to book chapters and edited volumes on digital identity management and wireless network security. She actively participates in international conferences and initiatives, advocating for privacy-by-design principles in intelligent infrastructures.

Pierre-Henri Parisمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Knowledge Graphs
• Information Extraction
• +۲ مورد دیگر

Pierre-Henri Paris is an Associate Professor (Maître de Conférences) at Paris-Saclay University since September 2024. Previously, he worked as a Postdoctoral Researcher at Telecom Paris (Institut Polytechnique de Paris) from September 2020 to August 2024. His academic journey includes a PhD in Artificial Intelligence from Sorbonne University and CNAM (Conservatoire National des Arts et Métiers) completed in 2020. Education: PhD in Artificial Intelligence, 2020, Sorbonne University and CNAM M.Sc. in Artificial Intelligence, 2016, CNAM M.Sc. in Mathematics, 2008, CY Cergy Paris University (incomplete) Pierre-Henri Paris's research focuses on the intersection of artificial intelligence, knowledge representation, and natural language processing. His work particularly emphasizes knowledge graphs, entity linking, and data quality. He has made significant contributions to projects like YAGO 4.5, which enhances knowledge bases with cleaner, logically consistent structures, and MAFALDA, a benchmark for fallacy classification. His research often bridges theoretical foundations with practical applications, particularly in how knowledge can be effectively represented, extracted, and utilized in complex systems. His recent publications reveal a strong focus on knowledge graph enhancement, semantic representation, and natural language understanding. The work on YAGO 4.5 demonstrates his commitment to creating more robust knowledge bases, while MAFALDA shows his interest in the intersection of language understanding and logical reasoning. His research trajectory indicates a consistent exploration of how structured knowledge can be integrated with linguistic analysis to create more intelligent systems. Advising: PhD students: Simon Coumes (2022-), Chadi Helwe (2022-2024), François Amat (2022-) Master's students: Syrine El Aoud (2021), Ayoub Mountassir (2013-2015) Bachelor's students: Khalil Halloul (2013-2014) Pierre-Henri Paris is actively involved in teaching at Paris-Saclay University, where he instructs courses including Introduction to Machine Learning, Introduction to Neural Networks, Algorithms for Data Science, Databases, and Data Warehousing. His teaching reflects his research expertise, providing students with both theoretical foundations and practical applications in artificial intelligence and data science.

Jamal Atifمشاهده پروفایل

استاد

• Artificial Intelligence
• Data Science
• Machine Learning
• +۳ مورد دیگر

Jamal Atif is a Professor at Paris Dauphine University - PSL and a member of the Laboratory for Analysis and Modeling of Systems for Decision Support (LAMSADE). He also serves as program director of PEPR Artificial Intelligence for the CNRS and was scientific delegate for Artificial Intelligence and Digital Infrastructures at INS2I until 2023. He earned his Ph.D. in medical image analysis from Paris-Sud University in 2004. His career includes a post-doctoral position at Télécom ParisTech (2004-2006), collaboration with the Research Institute for Development in French Guiana (2006-2010), and leadership as deputy head of the Learning and Optimization team at the Computer Science Research Laboratory (LRI - CNRS/Paris-Sud University) from 2013 to 2014. Professor Atif's research spans artificial intelligence and data science, with emphasis on machine learning , algorithms for data streams , and knowledge representation and reasoning . His work integrates theoretical foundations with practical applications in decision support systems through LAMSADE. He is affiliated with LAMSADE, a CNRS-Paris Dauphine joint research unit focused on operations research, decision theory, and optimization methodologies.

Kiwon Umمشاهده پروفایل

استادیار

• Physics-based Simulations
• Deep Learning
• Perceptual Evaluation of Simulations
• +۳ مورد دیگر

Kiwon Um is a tenured Assistant Professor in the Computer Graphics group at Télécom Paris, France, since October 2019. He focuses on physics-based simulations and data-driven approaches using deep learning, with an emphasis on human visual perception in computer graphics and engineering applications. Education: Ph.D. in Computer Science and Engineering from Korea University His research explores effective simulation of natural phenomena through refined data utilization and develops reliable data acquisition methods for machine learning. He also investigates perceptual evaluation of simulations to advance numerical method understanding. Recent work trends include: (1) turbulence modeling with machine learning integration, (2) elastic material simulation stability, (3) fluid dynamics optimization, and (4) differentiable physics frameworks. His publications range from 2008 to 2025, covering topics like SPH solvers, porous shell simulations, and numerical method validation.

David Langleyمشاهده پروفایل

استاد

• Digital Transformation
• Strategic Management
• Management Information Systems
• +۳ مورد دیگر

D.J. (David) Langley is a Full Professor of Digital Transformation & Strategy at the University of Groningen's Faculty of Economics and Business, Department of Innovation Management and Strategy. He holds concurrent roles as Senior Scientist at TNO and co-chairs the Innovation Ecosystems working group at aioti.eu. His research focuses on digital transformation, strategic management, and healthcare innovation. Langley has led projects across telecom, energy, banking, and public sectors, collaborating with firms like Philips, Rabobank, and the Dutch government. His work emphasizes digital technology's impact on institutional logic and strategic development patterns. He teaches courses on digital roadmapping and technology-driven innovation at the master's level. Key research outputs include frameworks on smart product ecosystems, flexible investment systems using real options valuation, and the role of social media in healthcare. His recent publications address climate change gamification and circular economy principles.

• Energy Efficiency in Communication Networks
• Quality of Service (QoS) and Quality of Experience (QoE)
• Network and Service Management
• +۵ مورد دیگر

Dr. Frank Loh is a researcher at the Department of Computer Science III, University of Würzburg, specializing in energy efficiency, network performance, and Quality of Experience (QoE) in communication networks. His work focuses on optimizing LoRaWAN deployments, serverless computing, and edge-cloud environments, with an emphasis on reducing message collisions and improving resource utilization. He actively contributes to methodologies for gateway placement, traffic modeling, and energy consumption metrics. Research Areas Energy Efficiency in Communication Networks Quality of Service (QoS) and Quality of Experience (QoE) LoRaWAN Network Planning Edge and Serverless Computing Network Resource Analysis Recent Publications 2025: Energy modeling for 6G base stations 2025: Server cluster resilience via Markov models 2024: Serverless computing in edge-cloud environments 2024: LoRaWAN channel access optimization

Guan-Hua Tuمشاهده پروفایل

دانشیار

• Security
• Wireless Networking
• Mobile Systems
• +۴ مورد دیگر

Guan-Hua (Scott) Tu is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University (MSU), leading the Security, Networking, and Mobile Systems Research (SNMS) laboratory. He holds a Ph.D. from UCLA and has industry experience at MediaTek, where he contributed to wireless communication as an engineer and researcher (inventing eight US patents). His research focuses on security, IoT, mobile systems, and wireless networking, with recent emphasis on 5G/4G architecture, cellular/Wi-Fi IoT, secure cloud computing, and blockchain technologies. Education includes a Ph.D. from UCLA (2015), MS from National Taiwan University (2003), and B.Sc. from National Central University (2001). Notable achievements include NSF grants (e.g., $1.73M NTIA grant as Co-PI, $1.2M NSF SaTC grant as PI), and awards like the Best Community Paper Award Runner-Up at ACM MobiCom'22 and Google Security Reward. His work addresses vulnerabilities in emergency services (9-1-1), cellular IoT, and IMS protocols, with publications in top venues like ACM MobiCom, IEEE Transactions, and ACM CCS. Current research includes exploring non-standardized policies in 5G networks, securing O-RAN infrastructure, and safeguarding next-gen emergency services. He advises Ph.D. students and has mentored alumni now in faculty roles (e.g., Utah State University, Michigan Tech). Teaching includes courses on computer security and networks.