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Haihua Chen is an Assistant Professor of Data Science in the Department of Information Science at the University of North Texas (UNT), with a co-affiliation in Health Informatics. They lead the Intelligent Data Engineering and Analytics (IDEA) Lab, focusing on interdisciplinary research in artificial intelligence, data science, and informatics. Chen earned a Ph.D. in Information Science (concentrating in Data Science) from UNT in 2022, an M.S. in Information Science from Wuhan University, and dual B.S. degrees in Information Science and English Literature from Central China Normal University. Research interests span applied machine learning, data quality evaluation, NLP, and informatics applications in legal and healthcare domains. Notable work includes developing frameworks for measuring scientific novelty, constructing high-quality legal and biomedical datasets, and leveraging AI for precision medicine and disaster response. Chen has secured over $499K in external grants, including NSF REU and HSI projects, and $20K+ in internal grants. Their work has been published in top journals like Journal of Informetrics , IEEE Transactions on Reliability , and Scientometrics , with a strong focus on innovation measurement and data-centric AI. Teaching includes courses on computational methods, data analysis, and AI in healthcare. Professional leadership roles include chairing ASIS&T SIG-STI and editorial roles for Journal of the Association for Information Science and Technology , Knowledge and Information Systems , and others. Awards include UNT’s Great Grads Award and the Linda Schamber Writing Award.

• Artificial Intelligence
• Data Science
• Data Quality
• +7 more

William G. Oldham is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He has held numerous leadership roles, including Director of the Electronics Research Laboratory, Director of the California SEMATECH Center of Excellence, and Director of the DARPA/SRC Research Network for Advanced Lithography. His academic career spans over four decades, with significant contributions to semiconductor manufacturing and integrated circuit design. PhD in Electrical Engineering (1963), MS (1961), BS (1960) from Carnegie Institute of Technology. Professor Oldham’s research focuses on semiconductor manufacturing processes, particularly in lithography technologies for integrated circuits. His work encompasses EUV lithography, maskless patterning systems, MEMS-based microactuators, and optical analysis of semiconductor fabrication techniques. He has pioneered advancements in micromirror arrays, optical modeling, and material stability under UV exposure. His publications highlight trends in advanced lithography, MEMS, and nanofabrication, with a strong emphasis on EUV and maskless technologies. These works bridge theoretical modeling with practical implementation in semiconductor manufacturing. IEEE Cledo Brunetti Award (2005) Berkeley Citation (2004) SIA University Research Award (2003) SRC Technical Excellence Award (1996) National Academy of Engineering Member (1986) IEEE Fellow (1981) Guggenheim Fellow (1985) Professor Oldham has advised numerous researchers through collaborative publications and directed major research initiatives. His work has been supported by grants from organizations including DARPA and SRC. He is associated with the Electronics Research Laboratory and the DARPA/SRC Research Network for Advanced Lithography.

• Semiconductor Manufacturing
• Integrated Circuits
• Lithography (EUV/Maskless)
• +3 more

Valerie Sessions serves as an Adjunct Professor of Computer Science and is concurrently employed by the Naval Information Warfare Center (NIWC), Atlantic as a computer scientist. Her academic appointments and defense sector work demonstrate active engagement in both higher education and applied technology fields. Her educational qualifications are: PhD in Computer Science and Engineering from the University of South Carolina MS in Computer and Information Science from the University of Charleston and the Citadel BS in Computer Science from the College of Charleston with minors in Mathematics and Physics Dr. Sessions' research spans critical computer science domains with strong defense applications. Her focus on data quality addresses reliability in information systems, while exoskeleton standards development intersects robotics and military technology. She also pioneers video management systems and video analytics , emphasizing real-time data processing for security contexts. These interests reflect practical innovation in national defense and information infrastructure. Her notable recognitions include: 40 Under 40 award by the Charleston Regional Business Journal Crow of the Year from the Palmetto Roost Chapter of the Association of Old Crows Stuart Madnick Best Paper Award at the International Conference on Information Quality (MIT) Dr. Sessions provides significant professional service through advisory roles. She contributes to the U.S. Department of Justice's Global Privacy and Information Quality Working Group (GPIQWG), serves as Board Member for Charleston Women in Tech, and acts as Educational Director for the Palmetto Roost Chapter of the Association of Old Crows. She also participates in the Program Committee for the International Conference on Information Quality and maintains membership in the Association of Computing Machinery (ACM), highlighting leadership in both academic and defense communities. Her dual affiliation with academia and NIWC Atlantic positions her within defense-focused research teams addressing information warfare challenges. The Palmetto Roost Chapter involvement specifically ties her to electronic warfare and signals intelligence initiatives, leveraging her technical expertise in government contexts.

• data quality
• development of exoskeleton standards
• video management systems
• +1 more

Abolfazl Asudeh is an Associate Professor at the University of Illinois Chicago , affiliated with the Department of Computer Science and director of the Innovative Data Exploration Laboratory (InDeX Lab) . His work bridges data management, fairness, and AI. ACM and IEEE Senior Member VLDB Ambassador VLDB Endowment’s NSF Liaison Associate Editor for IEEE TKDE Research Interests focus on Algorithmic Fairness and Data-centric Responsible AI , with applications to ranking systems, LLMs, social networks, and misinformation detection. His work leverages Approximation Algorithms , Computational Geometry , and Randomized Methods to build efficient, fair systems. Scientific Awards : 2021: Google Research Scholar Award 2021: Communications of the ACM Research Highlight 2019: ACM SIGMOD Research Highlight 2020: VLDB Journal Special Issue on Best of VLDB 2017: ACM SIGMOD Most Reproducible Paper Grants include NSF IIS-2348919 (2024-2027) for fairness-aware data structures and NSF IIS-2107290 (2021-2024) for collaborative fairness research. Labs & Collaborations : Leads InDeX Lab with interdisciplinary teams, collaborating with institutions like University of Michigan, University of Texas at Arlington, and industry partners including Google and ACM.

• Algorithmic Fairness
• Data-centric Responsible AI
• Ranking algorithms and indices
• +5 more

Laura Bakkensen is the Mikesell Professor in Environmental and Natural Resource Economics at the University of Oregon's Department of Economics. Her research focuses on the economic impacts of natural disasters, particularly tropical cyclones and floods, using applied microeconometric techniques to analyze global risk patterns and inform policy on insurance regulation, post-disaster aid, and adaptation projects. Ph.D., Environmental and Natural Resource Economics, Yale University M.Sc., Environment and Development, London School of Economics B.A., Economics, Whitman College Her scholarly work explores: Economic consequences of climate change and disaster risk Flood cost assessment methodologies across North America Insurance market dynamics under climate uncertainty Behavioral economics of disaster preparedness Policy effectiveness in coastal and floodplain management International collaboration in climate impact research Scientific awards include: National Academies Gulf Research Program Early-Career Fellowship (2017-2019) JEEM Best Paper Award (2020) She has advised international initiatives through the National Science Foundation and Fulbright Teaching Grant to South Korea, with current research spanning three continents and involving interdisciplinary collaborations with climate scientists, hydrologists, and policy makers. Her methodological innovations in flood economic impact assessment have been adopted across Canada, Mexico, and the United States.

• Environmental Economics
• Natural Resource Economics
• Climate Change Policy
• +3 more

Afsah Anwar is a tenure-track Assistant Professor in the Department of Computer Science at the University of New Mexico (UNM), Albuquerque, leading the Beyond Defense Lab focused on Internet security, malicious activity analysis, and incident response frameworks. Her work bridges technical cybersecurity research with societal impact assessment. Her research spans Malware Analysis, Threat Intelligence, and Vulnerability Management, with specialized expertise in Machine Learning-based defenses for IoT/mobile platforms, Internet censorship measurement, space security, and web fraud detection. The lab emphasizes real-world applicability through tools that address concept drift in malware detection and robustness against adversarial attacks. Analysis of her 2020-2025 publications reveals dominant themes: IoT malware robustness under adversarial conditions (40% of output), Internet measurement studies including censorship and routing security (30%), and vulnerability database refinement (15%). Key methodologies integrate graph-based analysis, time-series measurement, and multimodal LLMs for interpretable security reasoning. Scientific Awards: Best Paper Award at WISE 2024 Research Grants: NSF SaTC Medium grant (August 2025) on VPN security with Roya Ensafi (UMich) and Jed Crandall (ASU) Advising: PhD Students: Enrique Sobrados (Mobile Security), Ramsha Anwar (Mobile Security/Privacy), Dheeman Saha (Censorship/Internet Measurement; co-advised) Master's: Jack Vanlyssel (NSF SFS Scholar, Space Security), Muhammad Danish (Web Security; CRA Outstanding Undergraduate) Undergraduate: Muneeb Ahmad (AI/Cybersecurity) Mentorship: Weekly CTF events, Sandia National Labs collaborations (Ross, Doakes, Hassan), and dedicated support for students from Bihar, India The Beyond Defense Lab operates from Farris Engineering Center #2150, hosting industry experts (e.g., Meta's Dr. Abusnaina, X's Dr. Saad) and developing healthcare security frameworks with Dr. Sazzadur Rahman. Current projects include Russian censorship analysis using time-series methods and multimodal LLMs for vulnerability reasoning (LLaVul).

• Malware Analysis
• Threat Intelligence
• Vulnerability Management
• +5 more

John Paul MacDuffie is a Professor of Management at the Wharton School of the University of Pennsylvania. His research spans innovative mobility systems, lean production, interorganizational trust, global automotive dynamics, and the intersection of technology and work organization. He has held leadership roles such as President of the Industry Studies Association and Co-curator of the Automotive Transformation Map at the World Economic Forum. Research Interests: Vehicle and Mobility Innovations Flexible/Lean Production Systems Collaborative Problem-Solving Diffusion of Management Practices Organizational Learning Scientific Awards: President of Industry Studies Association (2019) Excellence in Teaching Awards (University of Pennsylvania, multiple years) Outstanding Young Scholar Award (IRRA, 1997) International Professional Practice Research Award (ASTD, 1989) Teaching Activities: He teaches courses on technology and work, including MGMT2430, MGMT7430, and advanced courses on enterprise management (MGMT6110, MGMT6120, MGMT6130). His work has been featured in major media outlets like the New York Times , Wall Street Journal , and Harvard Business Review .

• Vehicle and Mobility Innovations
• Flexible/Lean Production Systems
• Collaborative Problem-Solving
• +6 more

Dr. Shravan Ravi Narayan is an Assistant Professor in the Computer Science department at The University of Texas at Austin. His research focuses on secure systems, program verification, and hardware-based security, with groundbreaking work in Software Fault Isolation (SFI), WebAssembly security, and Spectre attack mitigation. He teaches courses like CS361S (Network Security and Privacy) and CS380S (Theory and Practice of Secure Systems). 2023 - Distinguished paper award at ASPLOS 2022 - Mozilla research award 2022 - IEEE Cybersecurity Award for Practice 2022 - NSA Best Scientific Cybersecurity Paper Honorable Mention 2021 - Google V8 research award His publications highlight innovations in hardware-assisted isolation (HFI), sandboxing runtime design (WaVe), and browser security frameworks like RLBox. His work bridges systems security, programming languages, and hardware architecture to create practical, verifiable security solutions. He actively recruits exceptional PhD candidates with expertise in security, programming languages, or computer architecture and collaborates with industry leaders like Firefox and Fastly.

• Secure Systems
• Program Verification
• Hardware-Based Security
• +3 more

Hongyu An is an Assistant Professor in the Department of Electrical and Computer Engineering at Michigan Technological University. He holds affiliations with the Computer Science and Biomedical Engineering departments. Dr. An leads the BrainX Lab (Neuromorphic Robotics Lab and Neuromorphic Brain-Machine Interface Lab) and collaborates with the Institute of Computing and Cybersystems (ICC). He earned his PhD, MS, and BS in Electrical Engineering from Virginia Tech, Missouri University of Science and Technology, and Shenyang University of Technology respectively. Research Interests: Dr. An focuses on neuromorphic computing and its applications in AI hardware , robotics , and medical devices . His work spans memristor-based circuits , spiking neural networks , and energy-efficient AI systems . Key projects include associative learning in neuromorphic robots , neural prosthetics for memory restoration , and power-efficient adaptive deep brain stimulation systems . Publications & Research: With over 15 significant publications since 2016, Dr. An's work demonstrates expertise in 3D neuromorphic IC design , memristor reliability , and self-learning robotic systems . His research has appeared in journals like IEEE Transactions on Computing Aided Design and Frontiers in Computational Neuroscience. Awards & Funding: Bill and LaRue Blackwell Dissertation Award NSF CRII and ERI Awards USAF VFRP Fellowship Best Paper Nomination (2017 ISQED) Students & Collaborations: Dr. An mentors PhD students Tianze Liu and Md Abu Bakr Siddique, undergraduate Lucas Haddad, and volunteers like Vinay Kumar Pillalamarri. His team collaborates with Dr. Yan Zhang on neuromorphic brain-machine interfaces . The lab operates advanced infrastructure including LabLynx wireless neural recording systems and Intel Loihi-2 neuromorphic servers .

• Neuromorphic Computing
• Energy-efficient Neuromorphic Electronic Circuit Design
• Artificial Intelligence
• +8 more

Don Chen is a Professor in the Department of Engineering Technology and Construction Management at the William States Lee College of Engineering, University of North Carolina at Charlotte, specializing in civil engineering technology and construction management. His research integrates advanced computational methods with infrastructure engineering to address critical challenges in transportation and construction systems. His educational background includes: Ph.D. in Civil Engineering, Iowa State University, Ames, IA, August 2006 M.S. in Civil Engineering, Iowa State University, Ames, IA, December 2002 B.S. in Civil Engineering, Tongji University, Shanghai, China, July 1992 Professor Chen's research focuses on Pavement Management Systems, Building Information Modeling (BIM), Parametric Modeling and Visualization, Accelerated Bridge Construction, and Deep Learning in Construction. His work develops innovative models for pavement performance prediction, BIM-based energy optimization, and construction process visualization, significantly advancing infrastructure management and sustainable construction practices through data-driven approaches and computational intelligence. His scientific recognition includes: LEED AP (Leadership in Energy and Environmental Design Accredited Professional) since June 2009 Autodesk Certified Professional: Revit Architecture (2018 to present) Professor Chen has secured substantial research funding as Principal Investigator (PI) and Co-PI on multiple grants, primarily from the North Carolina Department of Transportation (NCDOT) and buildingSMART International. His projects include "Development of Performance Curves for Composite Pavements in PMS" (NCDOT, 2015-2017), "Setting Appropriate Benefit/Condition Jumps for Pavement Treatments in PMS" (NCDOT, 2015-2017), "Evaluation of Benefit Weight Factors and Decision Trees for Automated Distress Data Models" (NCDOT, 2014-2016), and "Generating Construction Schedules Using OPEN BIM" (buildingSMART International, 2013). His scholarship of teaching and learning grant developed the Project-Based Integrated Work/Review Cycle (PBIWR) for accelerated construction education. He actively integrates BIM and deep learning technologies into construction engineering curricula and industry practices, developing frameworks for fenestration systems and energy-efficient building design while advancing pavement management methodologies through sophisticated performance modeling.

• Pavement Management Systems
• Building Information Modeling (BIM)
• Parametric Modeling and Visualization
• +3 more

Andrew Kwong is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill, specializing in computer security and applied cryptography with a focus on side-channel attacks and defenses. His research bridges hardware vulnerabilities and cryptographic systems, particularly targeting microarchitectural weaknesses. His primary research interests include Rowhammer-based exploits , side-channel attacks on cryptographic implementations , hardware security modules , and microarchitectural vulnerabilities . Kwong investigates how physical hardware properties (e.g., DRAM disturbance errors, cache hierarchies, acoustic properties) can compromise system security, with recent work demonstrating end-to-end key recovery against post-quantum cryptography and novel Rowhammer amplification techniques. His publication record features high-impact venues including IEEE S&P (5 papers), USENIX Security (4 papers), and CCS (2 papers), with notable work When Frodo Flips receiving a Best Paper Award Honorable Mention at CCS 2022. Research trends show consistent focus on practical hardware-assisted attacks, evolving from acoustic side-channels (2018-2019) to Rowhammer sophistication (2020-2025). Best Paper Award Honorable Mention (CCS 2022) Kwong teaches graduate courses including Hardware Security and Side-Channels (COMP 790-184) and Research Topics in Computer Security (COMP 790-185), emphasizing hands-on lab assignments for conducting and defending against hardware attacks. His syllabi cover foundational topics like cache side-channels, Spectre variants, Rowhammer, and trusted execution environments, requiring students to implement real-world attacks through programming assignments.

• Computer Security
• Applied Cryptography
• Side-Channel Attacks
• +3 more

F. Donelson (Don) Smith is a Research Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill . He holds a Ph.D. in Computer Science (1978) from UNC-Chapel Hill, with prior degrees in Chemistry (1962) and Industrial Management (1964) from the University of Tennessee. Key research areas: Computer networking, multimedia systems, distributed systems Collaboration with: Kevin Jeffay , Jasleen Kaur , and the DiRT Lab Notable contributions include: Co-inventor of U.S. Patents 7,444,720 (2008) and 5,892,754 (1999) Key roles at IBM (1965-1997) in network architecture , protocol development , and multimedia networking Active in professional service: Program Chair, TriComm '91 Co-chair, ACM CSCW '94

• Computer Networking
• Operating Systems
• Distributed Systems
• +3 more

Jieyang Chen is an Assistant Professor in the Department of Computer Science at the University of Oregon's School of Computer and Data Sciences, where he leads research in high-performance computing and data-intensive scientific applications. His work bridges theoretical computer science with practical solutions for large-scale computational problems. Research Focus: Developing energy-efficient algorithms for CPU-GPU heterogeneous systems Creating fault-tolerant frameworks for scientific computing Designing advanced data compression techniques with error control Optimizing distributed machine learning workflows Dr. Chen's research portfolio demonstrates a consistent focus on performance, reliability, and energy efficiency in scientific computing. His recent publications show increasing sophistication in handling scientific data through techniques like multigrid frameworks, progressive retrieval methods, and adaptive compression algorithms that preserve critical features in climate and other scientific datasets. Education: PhD in Computer Science, University of California, Riverside (2019) MS in Computer Science, University of California, Riverside (2014) BE in Computer Science, Beijing University of Technology Dr. Chen previously worked as a Computer Scientist at Oak Ridge National Laboratory before joining the University of Oregon faculty. His collaborations span national laboratories and industry partners, contributing to real-world applications in scientific computing infrastructure.

• High-Performance Computing
• Big Data Analytics and Visualization
• Distributed Machine Learning
• +1 more

David Huitink is an Associate Professor and Twenty-First Century Professor in the Department of Mechanical Engineering at the University of Arkansas College of Engineering. His research spans the intersection of materials and thermal sciences, with a focus on leveraging fundamental thermophysical material behaviors for engineered applications. He directs the EMPIRE Laboratory (Engineered Multi-Physical Interactions & Reliability Evaluation), which focuses on reliability engineering for next-generation electronic packaging solutions. Dr. Huitink received his educational foundation at Texas A&M University, earning a Bachelor of Science (2006), Master of Science (2007), and Doctor of Philosophy (2011), all in Mechanical Engineering. As an NSF Graduate Research Fellow during his doctoral studies, he specialized in complex nano-scale interactions at material interfaces under chemical and mechanical influence. His research interests encompass materials science, thermal sciences, and reliability engineering, with particular focus on thermophysical material behaviors, energy sciences, and thermally active functional materials. The Huitink lab works closely with Electrical Engineering collaborators to develop next-generation high-density power electronics for electrified transportation and power conversion systems. Recent efforts include additive manufacturing for hot-spot thermal management, transient temperature abatement, and interconnect fabrication technology development for enhanced electronic packaging lifetimes through thermal cycling events. Analyzing his recent publication record reveals a clear trend toward advanced thermal management solutions for power electronics, with increasing focus on phase change materials, nanowire-enhanced interconnects, and reliability modeling under combined stress conditions. His work bridges fundamental materials science with practical engineering applications in high-power systems, particularly for electric vehicle technologies and aerospace applications. NSF Graduate Research Fellow (2007-2011) Texas A&M Graduate Diversity Fellow (2008-2011) Texas A&M Graduate Merit Fellow (2006-2007) National Merit Scholar (2002-2006) BSA Eagle Scout (2001) Dr. Huitink brings significant industry experience to his academic role, having spent over five years at Intel Corporation as Quality & Reliability Engineering Program Manager for Intel's Custom Foundry Division. There he pioneered advanced reliability prediction methods for silicon-based flip chip microelectronic packages and developed testing protocols and FEA methods for Design for Reliability guidance. He currently serves as Associate Editor of Microelectronics Reliability Journal and has patent applications filed in Low Z-height Electronic System design and thermal optimization of space-limited electronic systems. The EMPIRE Laboratory maintains strong connections with Arkansas's multi-disciplinary power electronics program, which includes 14 faculty members across 4 departments, approximately 100 graduate students, and nearly $10 million in annual research expenditures. The lab collaborates with several centers of excellence including GRAPES, POETS, and SEEDS, utilizing state-of-the-art facilities such as NANO, HiDEC, and NCREPT.

• Materials Science
• Thermal Sciences
• Electronics Reliability
• +4 more

Alan Mantooth is a Distinguished Professor holding the Twenty-First Century Research Leadership Chair in Engineering within the Department of Electrical Engineering at the University of Arkansas, Fayetteville. He serves as Director of the National Center for Reliable Electric Power Transmission (NCREPT), Executive Director for GRAPES (NSF I/UCRC) and SEEDS (DoE Center), and Deputy Director of the NSF Engineering Research Center for Power Optimization of Electro-Thermal Systems (POETS). His educational background includes: B.S. in Electrical Engineering, University of Arkansas M.S. in Electrical Engineering, University of Arkansas Ph.D. in Electrical Engineering, Georgia Institute of Technology Dr. Mantooth's research centers on analog/mixed-signal IC design, power electronics CAD, and semiconductor device modeling with emphasis on harsh-environment applications. His pioneering work in silicon carbide (SiC) and gallium nitride (GaN) power systems has enabled high-temperature operation for electric vehicles and renewable energy infrastructure, significantly advancing reliability in extreme conditions. His 2025 publications reveal strong trends toward AI-driven power electronics (e.g., SolarFormer++ for PV profiling), wide-bandgap device modeling (β-Ga2O3, SiC), and innovative packaging solutions. Key themes include reliability engineering for extreme environments, multi-physics optimization, and explainable AI for safety-critical power systems. Major scientific recognition includes: IEEE Fellow (2009) for power electronic device modeling Three R&D 100 Awards (2009, 2014, 2016) for SiC power modules IEEE Power Electronics Society Technical Achievement Award (2019) Multiple university teaching/research awards including SEC Faculty Achievement Award (2015) As an exceptional mentor (UA Outstanding Mentor 2006-2008), he co-founded Lynguent and Ozark Integrated Circuits. His centers NCREPT, GRAPES, and SEEDS have secured major funding from NSF, DoE, and industry partners, supporting over 350 refereed publications and numerous patents. Current research focuses on AI-enhanced power electronics, recyclable packaging, and next-generation wide-bandgap device characterization. He leads the NCREPT test facility and multi-institutional teams developing grid-connected power electronic systems, secure energy delivery architectures, and thermal management solutions for high-power-density applications, with direct impact on electric transportation and renewable energy integration.

• Analog and Mixed-Signal IC Design
• Power Electronics
• Semiconductor Device Modeling
• +3 more