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Bo ChenView profile

Research Fellow

• Networking
• Machine Learning Systems
• Virtual Reality
• +5 more

Bo Chen is a postdoctoral researcher at the Siebel School of Computing and Data Science and the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. His work focuses on AI-system co-design for immersive computing, particularly in extended reality (XR) and multi-modal content delivery over wireless networks. Ph.D. in Computer Science (2022), advised by Klara Nahrstedt B.S. in Computer Science from Shanghai Jiao Tong University (2016) His research integrates AI techniques with system-level optimizations to address challenges in XR infrastructure , including multi-view video streaming , NeRF-based content delivery , and uncertainty management in video transmission . He has pioneered methods like Loose Frame Referencing for learned codecs and Context-Aware NeRF Serving for mobile XR applications. Bo Chen's recent publications span top venues like ACM MobiSys, ACM SenSys, and USENIX NSDI. Key themes include AI-driven compression , dynamic 3D rendering , and reliable streaming over mobile networks . He has received recognition including the Rising Star Best Presentation Award (ACM MobiSys 2025) and Best Student Paper Award (ACM MMSys 2022). Bayesian optimization for XR systems Multi-view video aggregation at edge networks 3D Gaussian Splatting for immersive media

Jerry Zeyu GaoView profile

Professor

• Cloud Computing and Services
• Software as a Service (SaaS)
• Testing as a Service (TaaS)
• +7 more

Jerry Zeyu Gao is a Professor in the Department of Computer Engineering at San Jose State University, part of the Charles W. Davidson College of Engineering. He maintains active office hours and has a strong presence in both academic and industry domains, combining over 15 years of academic experience with more than 10 years in software engineering and IT development management. His research spans a wide range of cutting-edge areas in computing, including: Cloud Computing and Services Software as a Service (SaaS) and Testing as a Service (TaaS) Test Automation Mobile Computing and Mobile Cloud Technologies Software and Service Engineering Mobile Sensor Technologies Smart Cities infrastructure Dr. Gao has published over 180 papers in top-tier IEEE and ACM journals and conferences, and has co-authored three technical books while editing several others in software engineering and mobile computing. His scholarly output reflects a strong focus on practical, scalable solutions in cloud, mobile, and service-oriented systems. The publications show consistent themes in automation, service delivery, distributed architectures, and real-world software validation. He has played a leadership role in the international research community, having served as conference chair, program co-chair, and workshop co-chair for numerous prestigious events such as IEEE MobileCloud, IEEE SOSE, SEKE, and others between 2004 and 2015. These roles highlight his influence and recognition in the software engineering and cloud computing communities. Dr. Gao advises students and contributes to graduate and undergraduate education, although specific advisees are not listed. He is involved in research projects and likely secures external funding given his publication and conference leadership activities, though specific grants are not mentioned. He is associated with research initiatives related to mobile systems, cloud services, and smart city technologies.

Mahadev SatyanarayananView profile

Professor

• Mobile and Pervasive Computing
• Distributed Systems
• Security and Privacy
• +2 more

Mahadev Satyanarayanan is the Jaime Carbonell University Professor of Computer Science at Carnegie Mellon University. His multi-decade research focuses on performance, scalability, availability, and trust in distributed systems spanning cloud to mobile edge computing. He pioneered foundational concepts in mobile computing and Edge Computing through his seminal work on VM-based cloudlets. His current research explores cloudlet-based Edge Computing for latency-sensitive applications, wearable cognitive assistance systems integrating augmented reality, and edge-based machine learning frameworks for efficient training data discovery. He collaborates with Dan Siewiorek, Martial Hebert, and Bobby Klatzky on transformative applications. Dr. Satyanarayanan received his PhD from Carnegie Mellon University after completing Bachelor's and Master's degrees at the Indian Institute of Technology, Madras. His honors include ACM and IEEE Fellowships recognizing his contributions to distributed systems and mobile computing. ACM Fellow IEEE Fellow

• Photonic Interconnects
• Distributed Machine Learning
• Cloud Computing
• +3 more

Rachee Singh is an Assistant Professor of Computer Science at Cornell University, leading the sysphotonics research group. She concurrently serves as an Amazon Scholar within the SageMaker Hyperpod teams, specializing in large-scale machine learning infrastructure development for cloud environments. Her research focuses on photonic interconnect systems for server-scale, rack-scale, and long-haul communication networks, targeting performance optimization for distributed machine learning and planet-scale cloud workloads. Key specialties include optical network design, fault-tolerant WAN architectures, and energy-efficient datacenter interconnects, with strong emphasis on practical deployment in real-world systems. Her group bridges theoretical networking principles with applied AI infrastructure challenges. Recent publications demonstrate concentrated innovation in photonic network optimization for ML workloads, particularly in wavelength management, collective communication algorithms, and chip-to-chip photonic fabrics. This work spans optical physics, distributed systems, and machine learning, revealing a trajectory toward sustainable, high-performance AI infrastructure. Scientific recognition includes: Amazon Research Award (2023) Cisco Research Award Dr. Singh actively mentors graduate researchers including Jonathan Aimuyo, Byungsoo Oh, and Arjun Devraj, whose co-authored publications form the core of her group's output. Research funding is secured through competitive grants from the NSF (including a $1M award for chip-to-chip photonic fabrics), SRC/DARPA JUMP 2.0 program, Cisco, and Cornell's Atkinson Center for Sustainability. The sysphotonics group operates as Cornell's hub for photonic network systems research, developing programmable integrated photonics solutions and collaborating with Amazon on SageMaker Hyperpod for next-generation ML infrastructure.

Janick EdingerView profile

Professor

• Distributed Operating Systems
• Edge Computing
• Computation Offloading
• +7 more

Prof. Dr. Janick Edinger is a Professor of Distributed Operating Systems at the Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, University of Hamburg, Germany. He leads a research group focused on distributed, context-aware, and adaptive computing systems, with a strong emphasis on edge computing, computation offloading, and assistive technologies. Education: PhD in Computer Science, University of Mannheim Studies at National Taiwan University Studies at University of Alberta, Canada Research stays at University of British Columbia, Hong Kong Polytechnic University, and Georgia State University, USA His research explores how edge computing and computation offloading can enable efficient, privacy-preserving processing of sensor and video data close to their sources, particularly in dynamic environments. He investigates the integration of autonomous and heterogeneous systems—such as drone fleets and mobile devices—into scalable middleware platforms for real-time monitoring and decision-making in logistics and industrial operations. His work also emphasizes societal impact, contributing to accessible routing, adaptive interfaces, and crowd-sourced mapping. The recent publications reflect a strong trend in edge computing, federated learning, privacy-preserving analytics, and assistive technologies. Topics include WebAssembly-based offloading, emotion prediction via eye tracking, real-time traffic detection, and predictive maintenance in Industry 4.0, showcasing a blend of foundational systems research and applied human-centered computing. Scientific Awards: PerCom 2021 Mark Weiser Best Paper Award Best Paper Award at IEEE PerCom 2021 for 'Voltaire: Precise Energy-Aware Code Offloading Decisions with Machine Learning' Prof. Edinger actively advises students and leads research projects involving grants and collaborations. His team includes PhD candidates and researchers working on middleware, edge systems, and context-aware applications. He has served on conference program committees, such as shadow PC member for EuroSys 2021, and publishes in top venues including IPDPS, PerCom, CHIIR, and COMPSAC. Labs and Teams: He leads the Distributed Operating Systems research group at the University of Hamburg, where he mentors students and collaborates on projects involving edge computing, IoT, and adaptive systems.

Habeeb OlufowobiView profile

Assistant Professor

• Cyber-Physical System Security
• Embedded Systems Security
• IoT Security
• +10 more

Habeeb Olufowobi is an Assistant Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington (UTA), where he leads the Cyber-Physical System Security Lab. He holds a PhD in Computer Science from Howard University (2019) and previously served as a Lecturer at Howard before joining UTA in 2020. His research is centered on the security and trustworthiness of embedded and distributed systems, particularly in the domains of autonomous vehicles, IoT, and healthcare AI. He investigates cybersecurity challenges at the hardware-software interface in real-time systems and develops AI/ML models that are transparent, explainable, and equitable. His interdisciplinary work integrates principles from cybersecurity, real-time systems, and machine learning. The recent publications reflect a strong trend in securing cyber-physical systems using advanced AI techniques, with emphasis on intrusion detection, secure communication (e.g., named data networking), and robustness of autonomous systems. His work frequently appears in top-tier venues such as IEEE Transactions, VehicleSec, and ICMLA. Project Management Professional (PMP), PMI (2012–Present) Member, Institute of Electrical and Electronics Engineers (IEEE) (2020–Present) Habeeb has secured significant research funding, including an NIH grant on ethical AI for Chagas disease prediction and an AIM-AHEAD grant focused on health equity. He mentors several graduate students, including Paul Agbaje and Afia Anjum, who have received awards and internships at prestigious institutions like Los Alamos National Laboratory. He teaches courses in cloud computing, embedded systems, and information security, and serves as a faculty advisor for the National Society of Black Engineers (NSBE) at UTA. His lab, the Cyber-Physical System Security Lab, focuses on developing scalable and reliable security solutions for critical infrastructure, with growing emphasis on healthcare applications and fairness in algorithmic decision-making.

Kwan-Wu ChinView profile

Professor

• Resource Allocation
• Internet of Things
• Maritime Networks
• +3 more

Kwan-Wu Chin is a Professor in the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong, where he also serves as Head of Postgraduate Studies (HPS) and co-directs the Wireless Technologies Lab (WTL). His research focuses on resource allocation problems in Internet of Things (IoT) systems, maritime networks, edge computing platforms, and integrated sensing-communication systems. Chin leads an active research group currently supervising five PhD students working on UAV networks, edge computing, maritime systems, and metaverse resource allocation. He has graduated over 20 PhD students who now hold positions in academia and industry. Chin serves as editor for Elsevier Computer Communications and IEEE Internet of Things Journal. His work develops optimization techniques using graph theory, stochastic processes, and machine learning for next-generation wireless systems.

Andrea FumagalliView profile

Professor

• Optical Networking
• Photonic Slot Routing
• Wavelength Routing and Protection
• +7 more

Andrea Fumagalli is a Professor in the Department of Electrical Engineering at the Erik Jonsson School of Engineering and Computer Science , The University of Texas at Dallas. He earned his Ph.D. (1992) and Laurea (1987) in Electrical Engineering from Politecnico di Torino, Italy. Research Interests: All-Optical Network Architectures, Photonic Slot Routing, Wavelength Routing and Protection, Sensor Networks, Cooperative Wireless Networks, Network Optimization, Next Generation Internet (NGI), and Multi-hop Optical Networks. Education: Ph.D., Electrical Engineering, Politecnico di Torino (1992) Laurea, Electrical Engineering, Politecnico di Torino (1987) Key Research Trends: His recent publications focus on 5G networking, optical network automation, elastic optical networks, network reliability, and cross-layer optimization. He explores FPGA acceleration in 5G Low-PHY functions, live migration of containerized network components, and spectral fragmentation mitigation in EONs. Scientific Awards: Best Teaching Award, Electrical Engineering, UTD (2002) Best Thesis Award for Ph.D. Advisee Isabella Cerutti (2002) IEEE ComSoc Distinguished Lecturer Tour (2000) Best Paper Award (1999): 'An Optimal Design Algorithm for Photonic Slot Routing Networks Migrating to Optical Packet Switching' Advising and Grants: He advised Ph.D. student Isabella Cerutti. In 2001, he secured a $300,000 grant from FUNDACAO CPqD for optical network reliability research. He leads the Optical Networking Advanced Research (OpNeAR) Lab at UTD, collaborating on international projects like the Italian government-funded grid computing initiative (2002) and the OMEGA Test-bed for differentiated reliability. Laboratories and Teams: He directs the OpNeAR Lab , which develops tools for optical network emulation and reliability testing. His projects involve partnerships with institutions in Brazil (Unicamp), Sweden (KTH), Italy (Politecnico di Torino, Scuola Superiore Sant'Anna), and CNR/CNIT.

Pradip SharmaView profile

Associate Professor

• Cybersecurity
• Artificial Intelligence
• Blockchain
• +5 more

Dr. Pradip Sharma is an Associate Professor of Cybersecurity & AI at the University of Aberdeen, UK, within the School of Natural and Computing Sciences, Department of Computing Science. He is a globally recognized academic and researcher with expertise in Cybersecurity, Artificial Intelligence, Blockchain, and Edge Computing. His research interests span multiple domains including Cybersecurity, Blockchain, Edge Computing, Software-defined Networking, and IoT Security. Dr. Sharma's work focuses on developing innovative solutions for security challenges in emerging technologies, with particular emphasis on privacy-aware AI systems, secure data sharing frameworks, and intelligent network security mechanisms. His interdisciplinary approach bridges theoretical foundations with practical implementations across healthcare, smart mobility, and consumer electronics domains. Senior Fellowship Advance HE (SFHEA) IEEE Senior Member (SMIEEE) Dr. Sharma actively supervises doctoral researchers and is accepting new PhD students in Computing Science. His funded research portfolio exceeds £1M from sources including EPSRC, Innovate UK, and international agencies. Current projects include 'Secure, Privacy-aware, and Trusted Data Share in Smart Mobility' (EPSRC, £200K), 'ZECURE Data Exchange Platform' (Innovate UK, £236K), and 'Quantum-resistant Cybersecurity' (Royal Embassy of Saudi Arabia, £73K). He also serves as an editor for leading journals and is a regular keynote speaker at international conferences.

Andrew ZhangView profile

Professor

• Wireless Communications
• Sensing Technologies
• Signal Processing
• +3 more

Prof. Andrew Zhang is a Professor at the School of Electrical and Data Engineering, University of Technology Sydney (UTS). He leads the UTS Radio Sensing and Pattern Analysis (RaSPA) Lab and serves as Technical Director of the UTS-TPG Network Sensing Lab. His research focuses on integrated sensing and communications (ISAC), wireless signal processing, and autonomous vehicular networks. He holds a PhD from the Australian National University and has over 15 years of industry experience, including roles at CSIRO and ZTE Corp. Education: B.S. (Xi’an Jiaotong University), M.Sc. (Nanjing University of Posts and Telecommunications), Ph.D. (Australian National University). Research Interests: ISAC, radio sensing, machine learning for communications, and 6G waveform design. Key projects include developing perceptive mobile networks and flood/storm sensing via ISAC. Publications: Over 290 papers, 5 patents, and notable works on ISAC frameworks, joint communication-sensing systems, and mmWave technologies. Recent trends emphasize ISAC, 6G waveforms, and IoT integration with federated learning. Awards: CSIRO Chairman’s Medal, Australian Engineering Innovation Award, and multiple best paper awards. Active in IEEE leadership roles, including Editor-in-Chief of ISAC-Focus. Grants: ~$8M in research funding. Advises on ISAC-ETI initiatives and collaborates with industry partners like TPG Telecom. Labs: RaSPA Lab (radio sensing analytics) and UTS-TPG Lab (ISAC industrial solutions).

Ryo SuzukiView profile

Assistant Professor

• Human-Computer Interaction
• Augmented Reality (AR)
• Virtual Reality (VR)
• +5 more

Ryo Suzuki is an Assistant Professor at the ATLAS Institute within the University of Colorado Boulder's Computer Science department. His research focuses on innovative intersections of Human-Computer Interaction (HCI), Augmented Reality (AR), and robotics. He explores systems that blend AI, haptics, and shape-changing interfaces to create enriched user experiences. Key areas of investigation include embedding interactivity into static educational materials (e.g., textbooks), developing AI-driven AR tools for procedural instruction, and creating shape-changing robotics for tactile feedback. His work often emphasizes practical applications in education, remote collaboration, and creative industries. Recent projects include MapStory (LLM-driven map animation), RealityEffects (3D volumetric video augmentation), and HoloDevice (holographic cross-device collaboration).

Karthik DantuView profile

Associate Professor

• Mobile Sensor Networks
• Robot Networks
• Networked Embedded Systems
• +8 more

Karthik Dantu is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York, within the School of Engineering and Applied Sciences. His research focuses on mobile sensor networks, robot networks, networked embedded systems, mobile computing, wireless networks, and embedded operating systems. He leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab and has received significant funding including an NSF CAREER Award. Dr. Dantu's educational background includes: PhD in Computer Science from University of Southern California (2009) BE in Computer Science from Sri Jayachamarajendra College of Engineering (1999) His research interests center on algorithmic and systems challenges in Edge Computing Systems, with particular focus on enabling seamless vision sensing in cloud-edge environments. Dantu's work bridges mobile systems and robotics, developing novel approaches for UAV software, visual SLAM, and distributed sensing. His research addresses critical challenges in resource-constrained environments, security, and real-time performance for mobile and robotic systems, with emphasis on practical implementations that solve real-world problems in autonomous systems. Dr. Dantu's publication record shows a strong trajectory in mobile systems and robotics research, with increasing focus on edge computing applications for visual sensing. His recent work demonstrates expertise in adapting visual SLAM to edge environments, securing mobile systems through technologies like Rushmore, and developing novel approaches for UAV software reliability and depth sensing. The research spans theoretical algorithms and practical system implementations, with particular strength in bringing academic research to practical applications in robotics and mobile computing. Dr. Dantu has received several scientific honors: NSF CAREER Award on Enabling Seamless Vision Sensing in Cloud-Edge Systems Outstanding service award from the Office of International Services NSF Travel Grant for SenSys 2005 Conference Travel Grant for SIGCOMM 2002 As an advisor, Dr. Dantu has mentored numerous PhD students to completion, with graduates now working at companies like Samsung Research and Zoox Inc., or continuing academic careers as Assistant Professors. His research is supported by substantial grants including a DARPA OFFSET Sprint 4 award ($470k), an NSF CAREER award ($550k), and multiple NSF collaborative grants totaling over $1.5 million. He serves on numerous conference committees including Mobicom, MobiSys, and ICRA, demonstrating leadership in the mobile systems and robotics research communities. Dr. Dantu leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab at UB, which focuses on developing algorithms and systems for mobile sensor networks, robot networks, and embedded sensing applications. The lab's work spans theoretical foundations to practical implementations, with particular expertise in UAV systems, visual SLAM, and edge computing for robotics, maintaining strong collaborations with industry partners and other academic institutions to advance the state of the art in mobile and robotic systems.

Michael WeyrichView profile

Professor

• Industrial Automation
• Digital Twins
• Large Language Models (LLMs)
• +7 more

Prof. Michael Weyrich is a faculty member at the Institute of Industrial Automation and Software Engineering (IAS) within the University of Stuttgart , leading the Cluster of Excellence IntCDC . His academic rank is Professor, and he focuses on Industrial Automation , Digital Twins , and Large Language Models (LLMs) for manufacturing and automotive systems. His research explores integrating LLMs into industrial automation for adaptive control, cloud offloading of vehicle functions, and semantic interoperability via Asset Administration Shells . He investigates modular production architectures , connected vehicle systems , and synthetic data generation for autonomous machinery. Recent publications highlight LLM-driven production planning , dynamic sensor calibration , and machine learning for fault detection in electric vehicle powertrains. His work emphasizes real-time data modeling and flexible microservice orchestration .

• Wireless Communication
• 6G Networks
• 5G Networks
• +6 more

A. Asadi is an Assistant Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science at TU Delft. He leads the Wireless Communication and Sensing (WISE) Lab within the Embedded Systems Group, focusing on the integration of wireless communication and sensing systems for Beyond-5G and 6G networks. His research leverages machine learning to develop practical solutions for next-generation wireless networks, with strong industrial collaborations from companies such as Nokia, NEC, and National Instruments. Research Themes : Wireless Sensing, 6G Networks, Physical Layer Security, Reconfigurable Intelligent Surfaces (RIS), mmWave Communication Key Collaborations : Industry partnerships with Nokia, National Instruments, and NEC Recent research outputs highlight his work on Reconfigurable Intelligent Surfaces (RIS) for 6G systems, including liquid crystal-based designs for fast beam switching and temperature compensation. His publications emphasize practical implementations in mmWave communication, security protocols, and experimental validation. Scientific Awards : Athene Young Investigator Prize (2017) Educational Fellowship (2025) Asadi contributes to the academic community through committee roles at major conferences like IEEE INFOCOM , IEEE ICNP , and ACM CoNEXT , and his work on D2D communication has been cited as an ESI highly cited paper.

Maozhen LiView profile

Professor

• High Performance Computing
• Big Data Analytics
• Artificial Intelligence
• +13 more

Maozhen Li is a Professor in the Department of Electronic and Electrical Engineering at Brunel University of London , within the College of Engineering, Design and Physical Sciences . He serves as the Vice-Dean of the NCUT Transnational Education (TNE) programme, overseeing a joint school with North China University of Technology. He has been at Brunel since 2002, progressing from Lecturer to Professor in 2013. Education: PhD, Institute of Software, Chinese Academy of Sciences (1997) Postdoctoral Research, School of Computer Science and Informatics, Cardiff University (1999–2002) His primary research interests lie in high performance computing, big data analytics, and artificial intelligence, with applications in smart grids, smart manufacturing, and cybersecurity. He focuses on developing interpretable, robust, and lightweight AI models, including work in causal AI, parallel machine learning, and edge computing. His research integrates advanced techniques such as deep learning, reinforcement learning, and blockchain for real-world system optimization. An analysis of his recent publications reveals a strong and consistent research trajectory in AI-driven solutions for environmental monitoring (e.g., PM2.5 prediction), industrial defect detection, IoT security, and intelligent transportation. His work frequently combines deep learning with graph-based modeling and federated or reinforcement learning, emphasizing scalability, efficiency, and robustness in distributed and edge environments. Scientific Awards and Recognition: Fellow of the Institution of Engineering and Technology (IET) Fellow of the British Computer Society (BCS) Shortlisted for the Computing UK BIG DATA EXCELLENCE AWARDS 2018 in the category of Most Innovative Big Data Solution Maozhen Li has successfully supervised 25 PhD students and examined over 30 PhD theses externally. He has secured significant research funding from EPSRC, the European Union (Horizon 2020), Innovate UK, and the Royal Society , with projects including Z-BRE4K, IoRL, and TDX-ASSIST. He serves as an Associate Editor for journals such as the Journal of Cloud Computing and the International Journal of Grid and High Performance Computing . Research Groups and Teams: He is affiliated with the Intelligent Engineering Frameworks (IEF) research group at Brunel, contributing to collaborative efforts in AI, IoT, and smart systems. His leadership in transnational education also fosters international research collaboration between Brunel and Chinese institutions.