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Michael Berry is a Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, part of the Tickle College of Engineering. He holds a PhD in Computer Science from the University of Illinois at Urbana-Champaign, an MS in Applied Mathematics from North Carolina State University, and a BS in Mathematics from the University of Georgia. His research focuses on data science, machine learning, text mining, nonnegative matrix factorization, parallel computing, and their applications in biomedical and environmental domains. Notable contributions include work on tensor decomposition for big data analysis, algorithms for text mining, and computational tools like PolyLens and CodeAssessor. Berry's publications emphasize interdisciplinary applications, such as using nonnegative tensor factorization for biomedical literature analysis and developing GPU-accelerated methods for traffic flow analysis. His work spans conferences like the International Conference on Soft Computing in Data Science (SCDS) and journals in computational science. He has contributed to software tools like FutureLens for text visualization and SHEPPACK for interpolation algorithms. His research also addresses environmental challenges via parallel ecosystem modeling and spatial control problems. No scientific awards or grants are explicitly mentioned in the provided text.

• Data Science
• Machine Learning
• Text Mining
• +4 more

Niloufar Shirani is an Assistant Research Professor in the Department of Civil and Environmental Engineering at the University of Connecticut's College of Engineering. Her research focuses on intelligent transportation systems, traffic safety, and sustainable transportation, with expertise in crash modeling, connected/automated vehicles, and transportation-public health intersections. Dr. Shirani earned her Ph.D. from the University of Alabama in 2020. Her educational background emphasizes transportation engineering methodologies and statistical analysis applied to real-world infrastructure challenges. Her primary research areas include Intelligent Transportation Systems (ITS), Driving Simulator Studies for connected and automated vehicles, Highway Traffic Safety, Crash Modeling and Analysis, Transportation and Public Health, and Sustainable Transportation. She employs advanced data-driven techniques like mixed logit modeling, unsupervised classification, and spatial analysis to investigate driver behavior, infrastructure safety, and policy impacts. Analysis of her recent publications reveals a dominant focus on traffic safety analytics, particularly distracted driving, automated vehicle interactions, and infrastructure-related crash risks. Her work frequently leverages Connecticut and Alabama case studies, demonstrating strong state transportation department collaborations. She also explores critical intersections between transportation systems and public health outcomes, including accessibility services and environmental sustainability. Dr. Shirani actively contributes to advancing behavioral safety tools for the Connecticut Department of Transportation and utilizes driving simulator facilities to evaluate human factors in emerging vehicle technologies. Her research directly informs transportation policy and infrastructure design through evidence-based safety performance functions and risk assessment frameworks.

• Intelligent Transportation Systems
• Connected and Automated Vehicles
• Highway Traffic Safety
• +3 more

Brian Ricks is an Assistant Professor of Instruction in the Computer Science Department at the University of Texas at Dallas (UTD). His academic journey includes a PhD, MS, and BS from UTD, specializing in wireless networking, network security, and Bayesian networks. He was advised by Bhavani Thuraisingham, Sriraam Natarajan, and Patrick Tague during his doctoral studies. Previously, he contributed to the MEWS research group at Carnegie Mellon University: Silicon Valley (CMU-SV), focusing on network simulation and security solutions. Education: PhD in Computer Science, University of Texas at Dallas MS in Computer Science, University of Texas at Dallas BS in Computer Science, University of Texas at Dallas His research interests span network security, Bayesian networks, and cybersecurity. He has pioneered work on network anomaly detection, DDoS mitigation, and probabilistic fault diagnosis in hybrid systems. His publications reflect a focus on practical solutions for real-world network challenges, including data generation, concurrency analysis, and attack isolation. Research Trends: Brian’s work emphasizes integrating probabilistic methods with network security, such as leveraging Bayesian networks for fault diagnosis and developing cost-effective network data generation techniques. His recent publications highlight advancements in detecting underlying anomalies during DDoS attacks and simulating realistic network scenarios. Awards: Best Paper Award at IEEE Intelligence and Security Informatics (ISI), 2018 Best Paper Award at IEEE Intl Conference on Information Reuse and Integration for Data Science (IRI), 2018 Grants & Advising: While no specific grants are listed, his research contributions suggest active engagement in funded projects. He advises students through his teaching and mentorship roles. Labs & Teams: 曾参与MEWS research group at CMU-SV, focusing on network simulation and security. His collaborations span academia and industry, reflecting a commitment to bridging theoretical research with practical applications.

• Network Security
• Wireless Networking
• Bayesian Networks
• +3 more

Weixian Liao is an Assistant Professor in the Department of Computer and Information Sciences at Towson University. His research focuses on big data analytics, cybersecurity, and networking in cyber-physical systems (CPS) and IoT. Dr. Liao holds a Ph.D. in Computer Engineering from Case Western Reserve University (2018), an M.S. in Electrical and Computer Engineering from Mississippi State University (2015), and a B.S. in Information Engineering from Xidian University (2012). His expertise spans secure edge intelligence, federated learning, adversarial machine learning, and IoT system resilience. Recent work includes surveys on AI model marketplaces, blockchain-empowered federated learning, and cybersecurity frameworks for smart energy systems. He has contributed to over 30 peer-reviewed publications in top journals/conferences such as IEEE Transactions and ACML. Research trends highlight his focus on interdisciplinary solutions blending machine learning with cybersecurity in critical infrastructure systems. His work emphasizes practical applications like disaster damage assessment via IoT search engines and resilient CPS design. Current projects explore edge computing security, federated learning incentives, and adversarial attack detection in distributed systems. No scientific awards or grants are explicitly listed in the provided materials. Dr. Liao’s lab focuses on advancing secure AI frameworks for IoT and CPS through innovative algorithm design and system architectures.

• Big Data Analytics
• Cybersecurity
• Networking
• +3 more

Bryan Dawson is a University Professor of Mathematics at Union University, located in Jackson, Tennessee. He holds a Ph.D. from the University of North Texas and both M.S. and B.S. degrees from Pittsburg State University. His work bridges advanced mathematical theory with innovative educational practices, particularly in calculus pedagogy and nonstandard analysis. Dawson has been honored as Researcher of the Year (2023) and is listed in multiple Who's Who directories. He is also an inventor, holding four U.S. patents related to muscle training and motion sculpting technologies. Education: Ph.D., University of North Texas; M.S. & B.S., Pittsburg State University His research interests focus on revitalizing calculus through infinitesimal methods, re-examining historical mathematical proofs (e.g., Euler's work), and exploring the intersections of mathematics with theology and education. He frequently presents at conferences such as the Joint Mathematics Meetings and the Association of Christians in the Mathematical Sciences, advocating for clearer mathematical explanations and faith integration. Key contributions include textbook development and workshops on teaching calculus using infinitesimals, as well as foundational research in hyperreal numbers and series convergence tests. His articles span topics like limit unification, paradox resolution, and pedagogical strategies. Scientific Awards: Researcher of the Year (2023), U.S. Patents #9,981,173 (2018), #9,149,705 (2015), #8,827,843 (2014), #8,398,501 (2013) Collaborations and advising involve mentoring student researchers, though specific advisee names are not listed. His professional activities include serving on academic committees, organizing workshops, and contributing to interdisciplinary scholarship symposia at Union.

• Calculus
• Nonstandard Analysis
• Infinitesimal Mathematics
• +3 more

Jan L Botha is a Professor in the Department of Civil & Environmental Engineering at San José State University (SJSU), affiliated with the College of Engineering. He holds a Ph.D. from the University of California, Berkeley (1980). His research focuses on traffic engineering, transportation safety, intelligent transportation systems (ITS), and automated vehicle operations, with additional expertise in transportation economics and air pollution mitigation. Current projects include evaluations of bus and truck automation concepts. Professional activities span traffic safety analysis and policy development. Key research contributions include studies on cold-weather traffic flow dynamics and societal impacts of digital infrastructure. His work bridges engineering principles with broader societal implications, particularly in urban mobility contexts.

• Traffic Engineering
• Transportation Safety
• Intelligent Transportation Systems (ITS)
• +3 more

Tao Wang is an Assistant Professor in the Department of Computer Science and Engineering at the University of North Texas, within the College of Computing and Informatics. He co-directs the Intelligent Security and Privacy (ISnP) Lab and holds a Ph.D. from the University of South Florida (2019) and a B.S. from Jilin University, China. Education: Ph.D., University of South Florida, 2019 B.S., Jilin University, China Dr. Wang's research spans Network Security , Web Security , 5G Security , Cyber-physical System Security and IoT Security , Wireless Networking , and Machine Learning for Cybersecurity including Trustworthy and Adversarial Machine Learning. His work focuses on designing defenses for emerging wireless technologies and web applications against sophisticated adversaries. His recent publications (2019-2023) reveal a strong emphasis on practical security solutions for IoT, 5G, and wireless systems, often integrating machine learning techniques. Key themes include data integrity in hardware enclaves, JavaScript caching vulnerabilities, MU-MIMO user selection, and adversarial network inference. Scientific Awards: Best Paper Award at IEEE GlobalSIP (2019) NSF Engineering Research Initiation (ERI) award (2022) Dr. Wang has successfully secured competitive grants from the NSF (Sole PI for ERI award), DoD Office of Naval Research (Sole PI for WeCARE project), U.S. Department of Energy, U.S. Army Research Laboratory, and Microsoft AFMR program. He actively mentors students, with at least one advisee (Shengping) acknowledged in publications, and recruits PhD, MS, and undergraduate researchers for his lab. He leads the Intelligent Security and Privacy (ISnP) Lab, which focuses on cutting-edge security research for next-generation networks and systems.

• Network Security
• Web Security
• 5G Security
• +5 more

Tommaso Giovannelli is an Assistant Professor in the Industrial and Systems Engineering program within the Department of Mechanical and Materials Engineering at the University of Cincinnati. Previously, he was a postdoctoral researcher and adjunct faculty member at Lehigh University's Department of Industrial and Systems Engineering. Education B.S. in Engineering Management, Sapienza University of Rome (2015) M.S. in Engineering Management, Sapienza University of Rome (2017) Ph.D. in Operations Research, Sapienza University of Rome (2021) Research Interests Giovannelli's research focuses on nonlinear optimization with applications in healthcare, transportation, and machine learning. Primary methodological interests include: Stochastic bilevel and multi-objective optimization Simulation-based optimization techniques Derivative-free and black-box optimization methods Machine learning optimization frameworks His applied research targets healthcare management optimization, transportation system efficiency, and fairness in AI systems. Publications Recent publications demonstrate strong focus on bilevel optimization techniques, healthcare operations (especially emergency department management), transportation logistics, and sports analytics. Work frequently combines simulation with optimization and addresses real-world social impact challenges. Awards Doctoral Award at ORAHS 2019 for simulation-based optimization research in emergency department management Grants and Advising Secured $500,000 from the Air Force Office of Scientific Research for optimization research. Advises undergraduate and graduate students on research projects in optimization and machine learning, with several co-authored publications in sports analytics and transportation. Organized major optimization conferences including MOPTA (2023-2025) and ICCOPT 2022. Labs and Teams Member of Lehigh University's Optimization and Machine Learning (OptML) Research Group. Current research team focuses on stochastic optimization methods and applications in social good domains.

• Nonlinear Optimization
• Stochastic Optimization
• Bilevel Optimization
• +6 more

Orlando Hernandez is an Associate Professor in the Department of Electrical and Computer Engineering at The College of New Jersey. He holds a Ph.D. in Electrical Engineering from Southern Methodist University (2002), an M.S.E.E. (1993) and B.S.E.E. (1991) from the University of South Florida. Prior to his academic career, he held industry positions at Texas Instruments and Maxim Integrated Products from 1993-2003, serving in design management roles for imaging systems, ASIC development, and microcontroller technologies. His research focuses on high-performance VLSI architectures for computer vision applications, including color image segmentation, digital signal processing, embedded systems, and mixed-signal design. Key research areas include hardware acceleration for image compression algorithms, real-time traffic monitoring systems, autonomous robotics, and advanced encryption implementations. His work consistently bridges theoretical algorithms with practical hardware implementations. Professional affiliations include Senior Membership in the Institute of Electrical and Electronics Engineers (IEEE). He has secured multiple research grants including a $93,320 National Science Foundation award for image processing instrumentation and several industry-sponsored equipment grants from Texas Instruments and Xilinx.

• VLSI Architectures
• Computer Vision
• Image Processing
• +4 more

Dr. Younghee Park is an Associate Professor in the Department of Computer Engineering at San José State University, part of the College of Engineering. She joined SJSU in 2013 as an Assistant Professor, advancing to her current rank in 2019. Her research focuses on network and system security, including malware detection, insider threats, botnets, smart grid security, and blockchain applications. She holds a Ph.D. in Computer Science from North Carolina State University (2010) and postdoctoral experience at the University of Illinois at Urbana-Champaign and Columbia University. Dr. Park has received prestigious awards such as the Kordestani Endowed Chair (2016-2017) and the Faculty Award for Excellence in Scholarship (2018). She founded the Silicon Valley Cybersecurity Institute (SVCSI), a non-profit dedicated to advancing cybersecurity. Her work integrates machine learning, blockchain, and SDN/NFV to address modern security challenges in IoT, mobile cloud computing, and critical infrastructure. Recent research emphasizes real-time intrusion detection systems, generative AI for malware analysis, and blockchain-based security mechanisms. She has led projects funded by the National Science Foundation (NSF) and industry partners, contributing to both academic publications and practical cybersecurity solutions.

• Network Security
• System Security
• Malware Detection
• +7 more

Dr. Niranjani H. Patel is a Professor in the Department of Industrial & Systems Engineering at San José State University (SJSU), where she also coordinates the MS Engineering Management program. She has held academic roles including Associate Professor at SJSU, Chair of Industrial & Manufacturing Engineering at the University of Wisconsin-Milwaukee, and visiting positions at the University of Central Florida. Her research focuses on operations research, supply chain optimization, transportation systems, and statistical modeling. Education: Ph.D. Industrial and Systems Engineering, Georgia Institute of Technology (1988) M.S. Operations Research, Georgia Institute of Technology M.S. Systems Engineering, University of Illinois, Chicago M.Sc. and B.Sc. Statistics, Maharaja Sayajirao University of Baroda, India Dr. Patel’s research interests span optimization techniques, stochastic processes, and industrial engineering applications. Notable contributions include work on factorial experiment design, supply chain integration, and hazardous materials routing. She has published extensively in journals like Computers & Industrial Engineering and International Journal of Industrial & Systems Engineering . Her awards include the Newnan Teaching Excellence Award (2009), NSF-funded grants for engineering entrepreneurship curriculum development, and multiple research fellowships. She has advised numerous Ph.D. and M.S. students, contributing to over 30 dissertations and theses. Grants & Service: Developed Lean Six Sigma programs within SJSU’s curriculum Directed the Operations Research Division of the Institute of Industrial Engineers (2000–2002) Recipient of over $100K in NSF and institutional grants for educational and research initiatives

• Operations Research
• Supply Chain Management
• Transportation Systems
• +3 more

Dr. Xiao Su is Associate Dean for Graduate Studies and Research at the Charles W. Davidson College of Engineering, San José State University, and a faculty member in the Computer Engineering Department. She joined SJSU in Fall 2002 after working at Inktomi Corporation. Dr. Su holds a Ph.D. from the University of Illinois, Urbana-Champaign (2001) and teaches courses in networking and security. Her research spans computer networking, multimedia communications, network security, and cloud computing. She has secured over $2.5M in research funding from NSF, NASA, Intel, and HP. Major grants include a $400K NSF CAREER Award (2006-2012) for multimedia streaming research and a $1.5M NASA grant for airport traffic optimization. Publications show strong focus on cloud-based media distribution, peer-to-peer networks, and security systems. Recent work emphasizes cloud storage optimization, mobile computing applications, and secure video transmission. Her 50+ publications demonstrate consistent innovation in distributed systems design and multimedia networking. Applied Materials Faculty Award for Excellence in Teaching (2012) College of Engineering Faculty Award for Excellence in Scholarship (2010) National Science Foundation CAREER Award (2006) As principal investigator, she has led 8+ major grants establishing research infrastructure and curriculum enhancements. She serves on NetApp's Academic Alliance advisory board and maintains active industry collaborations in Silicon Valley. A senior member of IEEE and ACM, Dr. Su has chaired technical committees for IEEE ICME and other international conferences.

• Computer Networking
• Multimedia Communications
• Network Security
• +3 more

Kevin Fang is an Associate Professor and Director of the Center for Sustainable Communities (CSC) in the Department of Geography, Environment, and Planning at Sonoma State University. His research focuses on sustainable transportation modes, urban mobility patterns, and land use planning. He explores how urban environments can be designed to support micromobility solutions like scooters, skateboards, and Segway-type devices, emphasizing sustainability and equity. Education: PhD Transportation Technology and Policy, University of California, Davis (2016) Graduate Certificate in Atmospheric Aerosols and Health, UC Davis (2011) M. City and Regional Planning & MS Engineering (Transportation Planning), Cal Poly (2009) BA Integrative Biology, UC Berkeley (2006) Research Interests: Urban sustainability and transportation alternatives Micromobility systems (e.g., electric scooters, skateboards) Land use patterns and their impact on travel behavior Environmental impact analysis of urban policies His recent work analyzes the safety, usage patterns, and policy implications of emerging transportation modes. He has contributed to studies on road diets, VMT reduction strategies, and the co-benefits of sustainable transport policies. Fang’s articles often bridge technical analysis with policy recommendations for urban planners and policymakers. As Director of the CSC, he leads initiatives promoting community-driven sustainability strategies. His advising and grants focus on fostering student research in urban mobility and environmental planning.

• Transportation
• Urban Planning
• Sustainable Transportation
• +3 more

Todd Walter is a Research Professor of Aeronautics and Astronautics at Stanford University, serving as Director of the Global Positioning System (GPS) Laboratory. His work focuses on high-integrity satellite navigation systems and international standards coordination. He holds a Ph.D. in Applied Physics (Stanford, 1994), M.S. in Applied Physics (Stanford, 1990), and B.S. in Physics (Rensselaer Polytechnic Institute, 1987). His research emphasizes GNSS integrity, RFI detection, spoofing mitigation, and advanced RAIM algorithms. The GPS Lab at Stanford is a key institution in his work. Research Interests: Walter’s expertise spans satellite navigation systems, GNSS security, and real-world interference detection. He develops cutting-edge techniques for spoofing detection using low-cost receivers, integrates ADS-B data for jamming localization, and explores cryptographic methods for signal authentication. His work bridges theoretical advancements (e.g., Gaussian bounding, error modeling) with practical applications in aviation and ground-based monitoring systems. Grants & Labs: Leads the GPS Lab, which focuses on advanced navigation technologies. His projects include ground-based integrity monitors for PPP services and cryptographic protocols for TESLA-enabled systems. Collaborates with international standards bodies to enhance GNSS security and reliability.

• Satellite Navigation Systems
• GNSS Integrity
• RFI Detection
• +3 more

Yixin Sun is an Anita Jones Career Enhancement Assistant Professor in the Department of Computer Science and an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Virginia's School of Engineering and Applied Science. Their research focuses on network security and privacy, including routing security, anonymity systems, and network attacks and defenses. Sun holds a B.A. from the University of Virginia (2013) and a Ph.D. from Princeton University (2019). Research interests span critical areas such as TLS and DNS security, IoT device vulnerabilities, connected vehicle systems, and privacy-preserving protocols like those in the Tor network. Their work addresses real-world challenges, such as securing internet infrastructure against routing attacks and enhancing anonymity in dynamic network environments. Recent publications explore topics like RPKI-based Tor relay selection, Mutual TLS certificate configurations, and Bluetooth traffic interception from health devices. Despite no explicitly listed scientific awards, Sun’s contributions to network security have advanced methodologies for detecting malicious DNS activities, securing vehicular networks, and improving threat prioritization systems. Their dual appointments reflect expertise bridging computer science and electrical engineering, emphasizing interdisciplinary approaches to cybersecurity.

• Network Security
• Privacy
• Routing Security
• +8 more