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Eric PriceView profile

Associate Professor

• Theoretical Computer Science
• Algorithms
• Lower Bounds
• +6 more

Eric Price is an Associate Professor in the Department of Computer Science at the University of Texas at Austin. He received his undergraduate and graduate degrees from MIT under the advisement of Piotr Indyk, and held postdoctoral positions at the Simons Institute (Berkeley) and IBM Almaden Research Center before joining UT in Fall 2014. Starting Fall 2024, he is on leave at Microsoft AI. Education: MIT (Undergraduate and Graduate), advised by Piotr Indyk Research Interests: Theoretical computer science, focusing on data-limited computational problems Algorithms and lower bounds for sparse recovery, streaming, and compressed sensing Integrating deep learning with traditional signal processing Provably efficient methods for high-dimensional estimation Connections between neural networks and algorithmic analysis Computational limits of modern architectures Article Trends: Recent work spans attention mechanisms, diffusion models, and LoRA fine-tuning Focus on theoretical guarantees for generative models, gradient dynamics, and security analysis Active in improving efficiency and robustness of AI systems Benchmark design for evaluating model limitations Scientific Awards: SODA Best Student Paper (2014) George M. Sprowls Award (2013) Simons Graduate Fellowship (2012) NSF Graduate Research Fellowship (2009) Multiple math/CS competition accolades Advising: PhD advisee Zhao Song (2019)

• Computer Vision
• Robotics
• Drone Technology
• +3 more

Halar Haleem is a Research Fellow at the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) within the University of Genoa. Their research spans interdisciplinary domains at the intersection of computer vision, robotics, drone technology, and wireless systems. Academic Rank: Research Fellow Affiliation: University of Genoa, Department of Naval, Electrical, Electronic, and Telecommunications Engineering Contact: halar.haleem@edu.unige.it Research interests focus on drone technology , computer vision , and wireless surveillance systems . They explore applications in traffic monitoring, aerial object detection, and energy-efficient drone operations, with recent work on AI-enabled medical IoT and biomechanical monitoring using smart glasses. Key article trends include: Drone-based traffic analysis using deep learning and image segmentation Privacy-preserving Wi-Fi monitoring systems Monocular vision for activity recognition in makerspaces RF/WiFi signal utilization for UAV surveillance Energy-accuracy trade-offs in drone video processing Trimetallic nanoparticle electrocatalysts for hydrogen production

Wolfgang KellererView profile

Professor

• Communication Networks
• Software Defined Networking (SDN)
• Network Function Virtualization (NFV)
• +7 more

Prof. Dr.-Ing. Wolfgang Kellerer is a full professor at the Chair of Communication Networks within the Department of Computer Engineering , TUM School of Computation, Information and Technology . He also serves as an adjunct professor in the Department of Informatics. His research focuses on adaptive, programmable communication networks, particularly Software Defined Networking (SDN) , Network Function Virtualization (NFV) , and 6G technology . He has contributed to quantifying network flexibility and AI-driven network management. Member of the ERC Peer Review Panel (2023-2024) Scientific Director of TUM Venture Lab Robotics/AI/Communication (2020-present) Editorial roles: IEEE Transactions on Network and Service Management , IEEE Communications Surveys & Tutorials His research spans from 5G to 6G , emphasizing ultra-low latency, resilience, and cross-layer optimization. Key projects include 6G-life , 6G Future Lab Bavaria , and ERC FlexNets , with over 300 publications and 40 patents. Scientific Awards include the ERC Consolidator Grant (2015) , IEEE Fellow (2025) , and multiple best paper awards at IEEE/IFIP CNSM, IEEE Future Networks, and ACM SIGCOMM.

Trinh Viet DoanView profile

Researcher

• Distributed Internet
• Decentralization
• Internet Measurements
• +7 more

Trinh Viet Doan is a researcher at the Chair of Connected Mobility (I11) within the Department of Informatics at Technical University of Munich (TUM) . His research focuses on distributed internet architectures, decentralization, network analysis, and content delivery systems. Current affiliation: Technical University of Munich, College of Informatics Academic rank: Researcher Research Interests: Distributed Internet & Decentralization Internet Measurements & Network Analysis Content Delivery & Privacy Censorship & Anonymity Network Topologies & Security Publication Trends: His work primarily examines decentralized systems (e.g., IPFS, DNS over QUIC/TLS), longitudinal internet infrastructure analysis (Netflix/YouTube content delivery), and web consolidation patterns. Key methodologies include empirical network measurements, protocol evaluation, and large-scale data analysis. Teaching Contributions: Participates in practical courses on recommender systems, computer network simulation, and open-source labs at TUM.

Yago Sánchez de la FuenteView profile

Researcher

• Video Coding
• Adaptive Streaming
• Mobile Networks
• +8 more

Yago Sánchez de la Fuente is a Research Associate at the Image Communication Group of Prof. Thomas Wiegand at Technische Universität Berlin and a guest researcher at Fraunhofer HHI . His work focuses on adaptive streaming services for IPTV/OTT and mobile networks, with technical expertise in HEVC/SHVC, LTE optimization, and satellite backhauling. Key research areas: Adaptive streaming over LTE, compressed domain video processing, and standardization protocols (IETF, 3GPP, MPEG) Project leadership: FP7 OPTIBAND (adaptive streaming optimization), ESA COSAT (satellite backhauling for LTE) Standardization contributions: Co-author of the IETF RTP Payload Format for H.265/HEVC Video Current projects: Mobile TV over LTE, Virtual Reality 360° video, and VVC system integrations He previously collaborated with Alcatel Lucent-Bell Labs (USA) on low-delay HTTP streaming optimization and is actively involved in international research groups like the Multimedia Communications team.

• Machine Learning
• Deep Reinforcement Learning
• Autonomous Driving
• +3 more

Vesa Hirvisalo is a Senior Lecturer in the Department of Computer Science at Aalto University. His professional profile shows active involvement in research related to computing systems and artificial intelligence. Research Focus: His work primarily addresses machine learning applications in autonomous systems, real-time processing, and heterogeneous computing environments. Publications highlight expertise in deep reinforcement learning, computer vision, and industrial informatics. Recent Publication Trends: His research output demonstrates a strong focus on deep reinforcement learning for task scheduling, autonomous driving environments, and optimizing convolutional neural networks for mobile applications. Collaborations span academic and industrial domains. Professional Contact: Email: vesa.hirvisalo@aalto.fi

• Video Encoding
• Video Transmission
• Quality of Experience (QoE)
• +4 more

James Nightingale is a Lecturer at the Computer and Information Sciences department within the Faculty of Engineering at the University of Strathclyde . He holds a BSc (Hons) and PhD from the University of the West of Scotland and brings extensive industrial and commercial experience in software development and project management from the defence, wholesale distribution, and manufacturing sectors. Education: BSc (Hons) and PhD from University of the West of Scotland His research focuses on video encoding and transmission in mobile networks, particularly addressing Quality of Experience (QoE) for multimedia in 5G and impaired/disadvantaged networks. His work explores adaptive streaming, scalable video coding, and network virtualization in high-efficiency scenarios. The trend in his publications reflects expertise in 5G network optimization, video streaming reliability, and SDN/NFV integration. Key subfields include ultra-HD video processing, tactical network resilience, and multimedia big data challenges. Teaching: Course tutor for Graduate Apprenticeship in IT Software Development Scientific Awards : Teaching Excellence Award - Team Award (Recipient, 22 Jun 2022) Teaching Excellence Award - Team Award (Longlisted, 7 Jul 2021)

Michael PaterakisView profile

Professor

• Computer Communication Networks
• Protocol Design
• Wireless Networks
• +4 more

Michael Paterakis is a Professor in the Department of Electronic and Computer Engineering at the Technical University of Crete, where he has served since 1995. His leadership roles include Vice-Rector for Academic Affairs & Personnel (2005-2010), Director of the University Research Institute of Telecommunications Systems (2000-2005), and Department Chair (1999-2001). His education includes a Diploma in Electrical Engineering from NTUA (1984), M.Sc. from University of Connecticut (1986), and Ph.D. from University of Virginia (1988). Prior to TUC, he was Assistant/Associate Professor at University of Delaware (1988-1995). Professor Paterakis's research centers on Computer Communication Networks with emphasis on protocol design , performance modeling of broadband wireless networks, and applied queuing theory . His work spans Wireless Communications , Multimedia Systems , and Network Optimization , addressing challenges in next-generation telecommunications infrastructure through rigorous mathematical analysis. Analysis of his 2006-2016 publications reveals persistent focus on wireless/powerline MAC protocols , multimedia call admission control , and video caching mechanisms . His research evolved from fundamental queuing theory toward practical implementations in heterogeneous networks, consistently prioritizing performance efficiency in resource-constrained environments. He has supervised 5 Ph.D. and 17 M.Sc. students while managing significant projects including the Information Society Operational Programme (2005-2009), which deployed Crete's metropolitan fiber optic networks across six municipalities. His service includes editing ACM journals, co-organizing IEEE workshops, and reviewing for major telecommunications conferences. Based in the Information and Networks Laboratory , his team develops protocols for unified services wireless networks with applications in mobile multimedia delivery and distributed information systems.

Lorenzo SeidenariView profile

Associate Professor

• Computer Vision
• Deep Learning
• Generative AI
• +4 more

Lorenzo Seidenari is an Associate Professor of Computer Engineering at the Department of Information Engineering, University of Florence . He earned his PhD in Computer Engineering (2012) and MEng in Artificial Intelligence (2008) from the University of Florence. As a member of the UNIMORE ELLIS Unit, he contributes to European AI excellence, and co-founded the startup Small Pixels for video processing solutions. PhD in Computer Engineering, University of Florence (2012) MEng in Artificial Intelligence, University of Florence (2008) His research focuses on deep learning applications in computer vision and robotics , particularly generative AI , model uncertainty , and robustness . Recent work includes trajectory forecasting for autonomous systems, 360° video streaming optimization, and synthetic data generation. Key projects like WILD.AI and IMRA-SD address real-world challenges in biodiversity monitoring and multi-agent prediction. Recent publications highlight trends in generative adversarial networks (GANs) , spatio-temporal modeling , and autonomous driving applications. He has received the ELLIS Scholar award and holds habilitations from MIUR for associate professorship in both Computer Science (01/B1) and Computer Engineering (09/H1). As a conference area chair for ACM MM and BMVC, he actively shapes AI research discourse.

• Computer Networks
• Wireless Communication
• Internet of Things
• +2 more

Alexey Vinel is a researcher affiliated with the University of West London, focusing on wireless communication systems, network security, and energy-efficient protocols. His work spans vehicular networks (VANET), IoT architectures, and heterogeneous LTE systems. Key research areas: Computer Networks, Wireless Communication, Energy Efficiency Active publication period: 2013–2017 His publications demonstrate expertise in: QoS optimization for IoT and multimedia streaming Security mechanisms in vehicular and low-power networks Energy cooperation strategies for millimeter-wave networks Radio resource management in LTE/LTE-A systems Collaborations include researchers like Jonathan Loo, Yue Chen, and Magnus Jonsson. Notable journals include IEEE Systems Journal , IEEE Communications Letters , and IEEE Sensors Journal .

Yong WeiView profile

Professor

• Image Processing
• Healthcare Technology
• Multimedia Systems
• +3 more

Dr. Yong Wei serves as a Professor of Computer Science in the Mike Cottrell College of Business at the University of North Georgia. He joined UNG in 2007 after working as a software engineer at SUN Microsystems (2000-2002), where he gained industry experience before transitioning to academia. His office is located in the Cottrell Center, room 312, in Dahlonega, Georgia, and he teaches undergraduate computer science courses including Computer Science I/II, Computer Organization, and Software Engineering. Education Ph.D. in Computer Science, University of Georgia, 2007 M.S. in Artificial Intelligence, University of Georgia, 2000 M.S. in Electrical Engineering, Nanjing University, 1994 B.S. in Acoustics, Nanjing University, 1991 Research Interests Dr. Wei's research program centers on image processing applications in healthcare technology and adaptive multimedia systems. His work bridges computer vision with medical diagnostics through CT image segmentation techniques, while simultaneously exploring resource-efficient video personalization for constrained environments. Key methodologies include fuzzy clustering algorithms and client-centered adaptation frameworks that optimize user experience without compromising computational efficiency. Publication Trends His 2009-2014 publications reveal a cohesive research trajectory applying computer science to healthcare and multimedia challenges. The works demonstrate progression from foundational content adaptation (2009) to specialized medical imaging applications (2014), consistently integrating machine learning with practical healthcare technology constraints. This trajectory shows increasing specialization in medical diagnostics while maintaining focus on adaptive systems for heterogeneous computing environments. Advising and Grants No information regarding graduate student advising or externally funded research grants was included in the provided institutional materials.

Ru XuView profile

Research Fellow

• Earth System Science
• Remote Sensing
• Land Cover Mapping
• +3 more

Dr. Ru Xu is a Postdoctorate Research Associate at the School of Biosciences , University of Sheffield, affiliated with the Leverhulme Centre for Climate Change Mitigation. She holds a Master's in Remote Sensing Science and a PhD in Earth System Science. MSc: Remote Sensing Science PhD: Earth System Science Her research focuses on land cover mapping , climate modeling , and biosphere-atmosphere interactions , utilizing observational data and model simulations. While her primary work involves Earth system science, her publication record also includes interdisciplinary research in machine learning and telecommunications related to video transport optimization. Selected publications (2019-2021) demonstrate expertise in reinforcement learning , deep learning , and mobile video telephony protocols. She joined Dr. Maria Val Martin's research group with 5 years of prior research experience.

• Machine Learning
• Data Analysis
• Data Mining
• +12 more

Hua Wang is a Professor at Victoria University, Melbourne, Australia, affiliated with the Institute for Sustainable Industries and Liveable Cities (ISILC) and the Oceania Cyber Security Centre (OCSC). His research spans machine learning, data analysis, cyber security, and privacy-preserving technologies, with applications in healthcare, IoT, and social media analytics. PhD in Computer Science (University of Southern Queensland, 2004) Research focuses on privacy-preserving data publishing , deep learning for cyber security , graph neural networks for IoT , and EEG-based neurological disorder detection . His work integrates federated learning and transformer models for secure, efficient data processing. Recent publications emphasize multi-objective optimization for privacy, adaptive neural networks , and domain-generalized tracking systems . Collaborations include Japan Society for the Promotion of Science (JSPS) and Data61 University Planning Committee. Hua supervises 14 PhD students, serves as ARC College of Expert (2021–present), and leads editorial roles for EAI Transactions on Scalable Information Systems , PLOS ONE , and World Wide Web Journal . He holds 14 grants totaling $3.1M, including ARC Discovery and Linkage projects.

• Operational Research
• Data Science
• Urban Mobility
• +4 more

Horchani Leïla is a researcher at CESI , affiliated with the National School of Computer Sciences at the University of Manouba, Tunisia. Her expertise spans Operational Research, Data Science, Urban Mobility, and Advanced Algorithms . PhD in Computer Science, University of Manouba, Tunisia (2013) DEA in Modeling and Management Information Systems, University of Tunis (2002) Master's in Applied Mathematics & Optimization, Tunis El Manar University (1998) Research Interests focus on probabilistic optimization models, sensor network applications, and intelligent urban mobility systems. She has contributed to combinatorial optimization, geolocation technologies, and smart city solutions. Her publications analyze probabilistic algorithms, UAV trajectory planning, and mobility balancing in taxi networks, often integrating Operations Research with Computer Science disciplines. Co-supervised Theses : A. Ghabri (Geolocation in sensor networks, 2017) and S. Sassi Mahfoudh (Probabilistic packing, 2018).

• Telematics Engineering
• Wireless Networks
• Energy Efficiency in Networking
• +6 more

Álvaro Suárez Sarmiento is a Professor at the Department of Telematics Engineering within the University of Las Palmas de Gran Canaria . He is affiliated with the IU of Cybernetics, Business and Society (IUCES) and leads the research group GIR IUCES: Architecture and Concurrency . His academic focus includes wireless network optimization, energy efficiency, and mobile service control. Research Areas : Wireless Networks, Energy Efficiency, Parallel Computing, Quality of Service (QoS), Mobile Video Streaming, Augmented Reality, WebRTC, Protocol Design Key Affiliations : Department of Telematics Engineering, IUCES Institute His students have explored topics like energy savings in Wi-Fi networks, mobile streaming interruption control, and algorithm parallelization. Current work includes advancements in hierarchical network topology and mobile service recovery mechanisms. Contact : alvaro.suarez@ulpgc.es