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Riccardo Lancellotti is an Associate Professor at the Department of Engineering 'Enzo Ferrari' of the University of Modena and Reggio Emilia. His research focuses on Edge/Fog/Cloud Computing, Cyber Security, and Resource Management in distributed systems. He has extensive contributions in optimizing infrastructure performance, load balancing, and energy efficiency in cloud and fog environments. His work often combines theoretical models with practical simulations, addressing challenges like stale information in edge systems and heterogeneous resource allocation in smart cities. Key research areas include: Fog/Edge computing infrastructure design and optimization Cloud resource provisioning and SLA compliance Security for Industry 4.0 and automotive systems Genetic algorithms for service placement Scalable VM clustering and resource allocation Publications highlight trends in cloud/fog integration, robust game theory for microservices, and distributed load balancing under dynamic conditions. His work emphasizes practical applications, such as pharmaceutical distribution routing and smart city sensor management. No awards are explicitly listed, but his extensive publication record reflects recognition in the field.

• Edge Computing
• Fog Computing
• Cloud Computing
• +7 more

Overview ASSILA Ahlem is a Researcher-Lecturer at CESI, specializing in Human-Machine Interaction (HMI), Augmented Reality (AR), and Virtual Reality (VR). She holds a PhD in Computer Science from Université de Valenciennes (2016) and a postdoctoral position at Institut Image ARTS ET METIERS PARISTECH (2017). Her research focuses on usability evaluation, digital twin technology, and BIM-integrated XR systems. She has supervised multiple engineering and master’s projects, including AR application development for network management. Research Contributions Developed frameworks for integrating subjective/objective usability metrics using ISO standards Proposed maturity models for BIM-based AR/VR systems Explored digital twin applications in manufacturing and construction industries Education & Responsibilities Teaches computer science at all engineering levels (L1-M2) at CESI Reims, including algorithmics, HMI design, and project-based learning. Served as pilot for engineering program cycles (2017–2020). Active in organizing international conferences (e.g., HCI 2020, Flexible Automation 2018) and peer review for journals like IJISE and IEEE VR. Awards & Recognition No specific awards listed, but recognized for contributions to HCI and industry-relevant research. Advising & Grants Supervised over 10 student projects including PFEs and internships. Actively participates in jury panels for engineering thesis defenses and academic promotions across multiple institutions. Labs & Collaborations Member of the CESI Chair for Industry and Services of Tomorrow, focusing on technology integration in construction and manufacturing sectors.

• Human-Machine Interaction (HMI)
• Augmented Reality (AR)
• Virtual Reality (VR)
• +4 more

Xiaowei Yang is a Professor of Computer Science at Duke University, where she holds multiple leadership positions including Co-Director of Graduate Studies for the Master of Science in Economics and Computation Program and Director of Graduate Studies for the MS Program in the Department of Computer Science. She is a prominent researcher in computer networks and distributed systems with numerous publications in top-tier conferences and journals. Dr. Yang received her Ph.D. in Computer Science from Massachusetts Institute of Technology in 2004 and her B.S.E. in Electronic Engineering from Tsinghua University in China in 1996. Prior to joining Duke University, she served as an assistant professor in the Department of Computer Science at the University of California at Irvine. Dr. Yang's research focuses on large-scale computer systems, particularly computer networks and distributed systems. Her work addresses challenges that arise as computer systems scale in size and distribute across geographical locations, with emphasis on scalability, reliability, security, performance, and manageability. Her current research interests include developing practical ML/AI technologies to improve network reliability and security (AIOps), protecting online privacy and security of Internet users, and providing network and system support for latency-sensitive applications. Her research has significant practical impact, with several projects addressing real-world problems in cloud computing, content delivery networks, and broadband infrastructure. Dr. Yang's recent publications demonstrate a consistent focus on practical network systems research with strong empirical validation. Her work spans multiple aspects of networking including cloud infrastructure, content delivery, security protocols, and network measurements. A notable trend in her recent work is the increasing focus on privacy-preserving technologies and the security implications of modern web infrastructure, particularly concerning content delivery networks and third-party services. Among her notable recognitions is the prestigious NSF CAREER award, which supports early-career faculty who exemplify the role of teacher-scholars through outstanding research, excellent education, and the integration of education and research. Dr. Yang has secured significant research funding, including multiple National Science Foundation grants. Current projects include "CNS Core: Small: Optimizing IP Anycast Performance at Scale" (2022-2026) and previously led "CNS Core: Small: Collaborative Research: Improving the Reliability of Cable Broadband Networks with Proactive Network Maintenance" (2019-2023) and "FIA-NP: Collaborative Research: The Next-Phase MobilityFirst Project" (2014-2018). She is actively involved in mentoring students and has taught courses including Introduction to Computer Systems and Advanced Computer Networks. As part of the Duke Systems group, Dr. Yang collaborates with colleagues on various systems research projects. Her work often involves close collaboration with industry partners, particularly cloud service providers and content delivery networks, ensuring her research addresses real-world challenges in large-scale systems.

• Computer Networks
• Distributed Systems
• Network Security
• +3 more

Professor Lynn Meuleners is a Senior Principal Research Fellow at the Western Australian Centre for Road Safety Research (WACRSR) and holds roles as a Senior Honorary Research Fellow in the School of Psychological Science and a Senior Principal Research Fellow in the UWA Law School at The University of Western Australia (UWA). With over 21 years of experience as an epidemiologist in road safety, her work focuses on data linkage, older drivers, driver simulation, road safety policy, and fatigue in heavy vehicle drivers. She has a PhD from Curtin University and an MSc from the University of Manchester. Her extensive collaborations include institutions such as the Department of Health WA, Main Roads WA, WA Police, and the Road Safety Commission. She has secured significant funding, including grants from the NHMRC, ARC, and others, totaling over $2 million. Notable projects include studies on cataract surgery’s impact on falls and drug driving deterrence regimes. Her research interests span road safety interventions, older driver safety, and the application of driving simulators. She has published over 200 peer-reviewed articles and technical reports, contributing to policy changes nationally and internationally. Her work aligns with UN Sustainable Development Goals related to road safety and public health. Current initiatives include the eFOVID study examining visual field disorders and crash risk, as well as projects on cycling infrastructure safety and personalized feedback systems to reduce road crashes among young drivers.

• Road Safety
• Older Drivers
• Driver Simulation
• +4 more

Dr. Cynthia Coles is an Associate Professor in the Department of Civil Engineering at Memorial University of Newfoundland's Faculty of Engineering and Applied Science. She specializes in environmental engineering, water resources, and geo-environmental engineering. Her research focuses on metal interactions with soils/sediments, arsenic distribution/removal, and mining impacts on groundwater. She teaches courses including Water and Wastewater Treatment, Environmental Pollution Mitigation, and Renewable Energy. Education: PhD (Geo-environmental Engineering) and M.Eng. (Water Resources) from McGill University, B.Eng. (Civil Engineering Structures) from McGill University. Industrial experience includes construction supervision in Sierra Leone and work with Conestoga-Rovers and Associates. Research Highlights: Over 15 peer-reviewed publications since 2000, focusing on heavy metal adsorption mechanisms, groundwater remediation techniques, and climate change impacts. Recent work addresses arsenic removal via sand filtration and peat-based sorbents. Teaching: Offers graduate courses in water treatment, soil chemistry, and environmental pollution control. Undergraduate instruction includes hydrology, municipal engineering, and environmental geotechnics. Current Opportunities: Accepting M.Env.Sci. students for research in geo-environmental engineering.

• Environmental Engineering
• Water Resources
• Geo-Environmental Engineering
• +4 more

Tara Javidi holds the Jerzy (George) Lewak Endowed Chair and is a Professor in the Department of Electrical and Computer Engineering and Halicioglu Data Science at the University of California San Diego (UCSD). She leads multiple initiatives, including serving as Founding CTO of KavAI, Co-Director of the Center for Machine Intelligence, Computing and Security, and Co-Principal Investigator (CoPI) of the NSF AI Institute TILOS. Her research focuses on stochastic analysis, design, and control of information systems, emphasizing active learning, decentralized optimization, and wireless networks. Key areas include information acquisition/utilization, stochastic control, and AI-driven communication solutions. Her work bridges theoretical foundations and practical implementations, such as drone systems for information gathering (via detecdrone.ucsd.edu) and optical data center networking. Notable contributions include end-to-end scheduling for all-optical data centers and hybrid wireless-optical architectures. Javidi is an IEEE Fellow and has received significant grants, including leading UCSD’s Schmidt AI in Science Postdoctoral Fellowship program. She actively collaborates with industry and academia, with a focus on next-generation wireless networks and decentralized systems. Education: Ph.D. in Electrical Engineering (implied from title). Affiliations: IEEE Journal of Selected Areas in Information Theory (Editor-in-Chief), CALIT2, CNS, and TILOS. Grants: NSF AI Institute TILOS ($20M over 5 years), Schmidt AI Fellowship program. Her research group emphasizes both theoretical rigor (e.g., sequential hypothesis testing) and practical testing, with applications in service drones, cognitive networks, and federated learning. Recent articles highlight advancements in optical networking, secure communication, and distributed learning protocols. Awards: IEEE Fellow, Jerzy Lewak Chair. Labs/Teams: Center for Machine Intelligence, TILOS Institute, KavAI, and UCSD’s AI in Science initiatives.

• Information Theory
• Active Learning
• Decentralized Learning
• +4 more

Dr. Haydar Aygun serves as Associate Professor in Acoustics and Building Services at the Bioscience and Bioengineering Research Centre, Department of Civil and Building Services Engineering, University of Salford. He holds multiple leadership roles including Course Director for the MSc Environmental and Architectural Acoustics, Diploma in Acoustics and Noise Control, and The Acoustics Apprenticeship programs. With a PhD in Acoustics and Vibration from the University of Hull (2006), his academic foundation includes a MSc in Advanced Materials, Processes and Manufacturing (2002) and a BSc in Mechanical Engineering. Dr. Aygun's research spans multiple critical domains of acoustics: Development and characterization of novel acoustic materials and metamaterials for noise control Duct acoustics and sound propagation through complex media Biomedical applications including bone analysis and respiratory sound detection Vibration control of porous materials using advanced computational methods Environmental noise assessment and building acoustics solutions His publication record shows consistent scholarly output with 46 research items from 2006-2025, demonstrating particular productivity in recent years (7 publications in 2023). His work shows increasing integration of computational methods with experimental validation, expanding applications in medical diagnostics and sustainable building technologies. Dr. Aygun actively contributes to the academic community through multiple service roles: Editorial Board Member for Journal of Applied Acoustics EPSRC Grant Reviewer Reviewer for Journal of Applied Acoustics and Journal of the Acoustical Society of America Deputy leader of Biomedical Acoustics Special Interest Group within UK Acoustics Network As an educator, Dr. Aygun has supervised numerous PhD students and teaches across multiple levels from undergraduate Building Services Engineering to specialized postgraduate Acoustics programs. His consultancy work bridges academic expertise with practical industry applications in noise assessment, building acoustics, and event sound management.

• Acoustic Materials
• Metamaterials
• Biomedical Acoustics
• +7 more

Vadhiraj Shrinivas is a Research Fellow and Doctorate Student at Coventry University's Centre for Future Transport and Cities. His work bridges machine learning, transportation safety, and biomedical engineering. He holds a Postgraduate Certificate in Artificial Intelligence & Machine Learning from the University of Texas at Austin (2020) and a Degree in Electrical and Electronics Engineering from Visvesvaraya Technological University (2013). Research interests include applying machine learning to pedestrian collision forensics, analyzing injury parameters via meta-analyses, developing computational models for brain injury mechanics, and advancing power electronics through SPWM techniques. Notable projects include the PACE-AI forensic calculator and collaborations on concussion biomechanics. Publications span forensic tool development, injury severity analysis, and numerical methods for brain trauma. His earlier work focused on multilevel inverter optimization. Active in international collaborations, he contributes to road safety and biomedical research.

• Machine Learning
• Transportation Safety
• Biomedical Engineering
• +3 more

Roberto Rojas-Cessa is a Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT), affiliated with the School of Applied Engineering and Technology. His research focuses on networking, blockchain applications in smart cities, energy systems, wireless communications, and high-performance switching. He has led multiple National Science Foundation (NSF)-funded projects, including initiatives on controlled delivery power grids and next-generation network quality of service. Notably, his work explores blockchain for energy metering, sustainable environmental measures, and smart grid optimization. He is also a Senior Member of the National Academy of Inventors (2024). His research interests span network protocols, distributed systems, and IoT applications. Recent projects include AMI-Chain (a blockchain-based power metering system) and studies on indirect free-space optical communications for vehicular networks. He has contributed to advancements in medium access control for crowded networks and energy packet switches for digital microgrids. Rojas-Cessa’s work integrates machine learning for network management and flood impact analysis. He has developed tools for time-lapse analysis of urban data and agent-based models to evaluate electric vehicle adoption. His publications emphasize scalability, security, and efficiency in both traditional and emerging technologies. Grants: Collaborative Research on Power Grids (NSF, 2016–2018), NeTS-NR: Quality of Service Networks (NSF, 2004–2008) Awards: Senior Member of the National Academy of Inventors (2024) His lab activities include experimental evaluations of digital microgrids and blockchain implementations for carbon footprint tracking. He actively collaborates on projects addressing emergency communications and resilient energy distribution systems.

• Networking and Communications
• Blockchain Technology
• Smart Grids and Energy Systems
• +5 more

Dr. Hanna Maoh is a Professor in the Department of Civil and Environmental Engineering at the University of Windsor. She holds a BSc from Bethlehem University (1996), MSc from McMaster University (1999), and PhD from McMaster (2005). Her research focuses on integrating transportation and land use models, freight transportation analysis, sustainable transportation strategies, and big data applications in GIS. She leads the Traffic Lab, exploring innovative solutions for cross-border logistics, electrification of fleets, and environmental impact mitigation. Key professional affiliations include the Transportation Association of Canada, Professional Engineers Ontario, and the Transportation Research Board. Her work emphasizes policy-relevant research, such as modeling Canada-US border crossing efficiency, optimizing electric vehicle charging networks, and assessing freight infrastructure resilience. Recent publications highlight advancements in truck stop location optimization using GPS data, fleet electrification demand analysis, and border crossing behavior studies. Her research consistently bridges academic insights with practical applications, informing sustainable urban planning and environmental policy.

• Transportation Engineering
• Sustainable Transportation
• Freight Transportation Analysis
• +4 more

Eric Wustrow is an Associate Professor in the Department of Electrical, Computer & Energy Engineering at the University of Colorado Boulder , affiliated with the College of Engineering and Applied Science . His research focuses on network security, internet censorship, and cryptographic protocols. Contact: ewust@colorado.edu , Phone: 734-330-8702, Office: ECCR 1B13. Academic Rank: Associate Professor Department: Electrical, Computer & Energy Engineering University: University of Colorado Boulder Eric Wustrow's research explores methods to measure and circumvent internet censorship, analyze network vulnerabilities, and enhance privacy in digital communications. His work includes studying the Great Firewall of China, DNS and TLS security, and developing anticensorship tools like ShadowTLS and WATER. He also investigates cryptographic weaknesses in network devices and secure hardware implementations. Recent publications examine the effectiveness of anticensorship tools, the impact of IPv6 on information controls, and vulnerabilities in encrypted protocols. His studies include speculative execution attacks, DNS censorship measurement, and techniques to exploit transient errors in TLS for key compromise. These works highlight evolving network threats and countermeasures. Eric's research has been supported by grants such as the CAREER: Combating Censorship from within the Network (2022) and SaTC: CORE: Medium: Collaborative: Studying the Impact of IPv6 on Information Controls and Censorship Circumvention (2020). These projects focus on developing network-level solutions to censorship and security challenges.

• Network Security
• Internet Censorship
• Cybersecurity
• +8 more

Y. Charlie Hu is the Michael and Katherine Birck Professor of Electrical and Computer Engineering and Professor of Computer Science (by courtesy) at Purdue University, where he leads the PurNET Lab and contributes to the Systems and Networking Group. His research spans Mobile Systems, Distributed Systems, Operating Systems, and Computer Networks , with a focus on energy-efficient AI systems and edge computing. His groundbreaking work on smartphone energy management has been widely adopted by the mobile industry and recognized with multiple test-of-time awards , including from ACM SIGOPS and ACM SIGMOBILE . He has received prestigious honors like the NSF CAREER Award , Honda Initiation Grant , and industry accolades from Google Research and Qualcomm . Notable Funded Projects: NSF's NeTS: Black-box Optimization of White-box Networks (2023-2026) Intel -NSF's SPLICE initiative His research has produced 15+ PhD graduates now in academia (University of Arizona, Virginia Tech) and industry (Google, Apple, Qualcomm). The articles reflect a career-long focus on edge computing , 5G network optimization , and energy-aware systems , with recurring themes in mobile AR/VR , video analytics , and network protocol design . Scientific Awards Honda Initiation Grant NSF CAREER Award Purdue Early Career Research Award Google Research Award Qualcomm Faculty Award ACM SIGOPS EuroSys Best Student Paper Award ACM MobiCom Best Community Paper Award IEEE Fellow ACM Distinguished Scientist Purdue PRF Innovator Hall of Fame

• Mobile Systems
• Distributed Systems
• Operating Systems
• +5 more

Taejoong Chung is an Associate Professor in the Computer Science department at Virginia Tech. He received his PhD in Computer Science and Engineering from Seoul National University in 2015. His research focuses on Internet security protocols including DNS, TLS/HTTPS, routing (BGP/RPKI), and email security, with an emphasis on protocol deployment challenges and internet measurements. His work has earned recognition including an NSF CAREER Award (2024), Outstanding New Assistant Professor award from Virginia Tech's College of Engineering (2024), ACM CCS Best Paper Honorable Mention (2022), IRTF Applied Networking Research Prize (2019), ACM IMC Distinguished Paper Award (2019), and USENIX Security Distinguished Paper Award (2017). Dr. Chung leads research on practical security improvements, developing systems like RoVista for measuring route origin validation and mmTLS for optimizing encrypted traffic inspection. His group actively contributes to internet standards through IETF involvement. He mentors PhD students working on security protocols and maintains collaborations with industry partners including Meta, Verisign, and Cloudflare. Research Areas: Internet routing security (RPKI, BGP) DNS ecosystem (DNSSEC, TTL violations) TLS certificate ecosystem evolution Email security protocols (DMARC, DANE, MTA-STS) Certificate revocation mechanisms Recent Grants: NSF CAREER Award (2024), NSF CRII Award (2019)

• Internet Security
• DNS Security
• TLS/HTTPS Protocols
• +3 more

Riadul Islam serves as an Assistant Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC), maintaining his primary office in room 316 of the Information Technology and Engineering (ITE) Building. His academic appointment focuses on hardware design and verification within the institution's engineering framework. His educational qualifications include: Ph.D. in Computer Engineering from UCSC (2017) M.A.Sc. in Electrical and Computer Engineering from Concordia University, Montreal (2011) B.Sc. in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (2007) Professor Islam's research centers on VLSI CAD tools and low-power digital/mixed-signal IC design , with significant contributions to current-mode clock networks, vehicular security systems, and error-robust circuit architectures. His work increasingly integrates machine learning for design automation while exploring neuromorphic computing applications and secure hardware implementations. This multidisciplinary approach bridges traditional IC design with modern AI-driven optimization techniques. Analysis of his 2023-2025 publications reveals three dominant research thrusts: (1) Machine learning applications in early-stage Design Rule Checking (DRC) prediction and clock network optimization, (2) Graph-based intrusion detection systems for automotive networks (particularly CAN bus security), and (3) Event-based vision systems and neuromorphic computing architectures. These areas demonstrate consistent innovation in merging hardware design with AI/ML methodologies for enhanced system reliability and efficiency. He directs the UMBC VLSI and SoC Research Group , which develops energy-efficient clocking networks, secure vehicular communication protocols, and compute-in-memory architectures. The lab maintains active collaboration with industry partners on hardware security and neuromorphic computing initiatives while supporting graduate student research in cutting-edge IC design methodologies.

• VLSI CAD
• Low-power IC Design
• Mixed-signal IC Design
• +5 more

Kun An is a Professor at the Department of Traffic Information and Control Engineering within the College of Transportation Engineering at Tongji University. She has previously held academic positions at Monash University (Senior Lecturer, 2018–2019; Lecturer, 2016–2018) and conducted postdoctoral research at the University of Illinois at Urbana-Champaign (2015–2016) and The Hong Kong University of Science and Technology (2014–2015). Her academic journey includes a PhD in Civil Engineering from HKUST (2014) and a Bachelor's degree from Tongji University (2009). PhD: Civil Engineering, The Hong Kong University of Science and Technology (2014) Bachelor's: Transportation Engineering, Tongji University (2009) Dr. An specializes in intelligent transportation systems, focusing on optimizing complex traffic networks, characterizing traveler behavior in stochastic environments, and advancing electric vehicle sharing infrastructure. Her research spans urban transit planning, carsharing logistics, battery electric bus deployment, and real-time traffic signal optimization, with applications to mitigate rail disruptions and enhance multimodal connectivity. Her publications emphasize solving transport challenges through stochastic programming, game theory, and behavioral analysis. Key themes include autonomous vehicle integration, demand uncertainty modeling, and sustainable mobility solutions. Awards include the Hong Kong PhD Fellowship and multiple best paper recognitions. Hong Kong PhD Fellowship (2010–2014) TRBADB30 Best Paper Nomination (2014) Best Paper at 18th Hong Kong Transportation Annual Meeting (Second Author, 2013)

• Intelligent Transportation Systems
• Traffic Network Optimization
• Stochastic Demand Modeling
• +3 more