Jun Wang is Assistant Professor and Director of the Mississippi Transportation Research Center in the Department of Civil and Environmental Engineering at Mississippi State University. He holds a Ph.D. in Civil Engineering from McMaster University, with research interests spanning smart construction, sustainable infrastructure, human-robot collaboration, and construction safety. Awarded the prestigious NSF CAREER grant ($557,391) for VR and AI research in construction robotics, he leads projects sponsored by NSF, DOT, CDC, and industry partners. Key research areas include: Virtual Reality and AI for safety training Human-in-the-loop cyber-physical systems Sustainable infrastructure development Construction automation technologies His recent publications explore drone systems for marine debris management, VR safety training, AI-powered PPE detection, and digital twin frameworks, with work appearing in leading engineering and computing venues.
Joydeep Mukherjee is an Assistant Professor in the Department of Computer Science and Software Engineering at California Polytechnic State University (Cal Poly), San Luis Obispo, USA. He also holds an Adjunct Assistant Professor role at the University of Calgary's Department of Electrical & Software Engineering, where he collaborates on research and student supervision. His research focuses on software performance management in cloud computing and IoT systems, with a particular emphasis on detecting and mitigating performance interference in cloud-native applications. Education: Ph.D. and M.Sc. in Computer Science from the University of Calgary (supervised by Dr. Diwakar Krishnamurthy) Bachelor's in Computer Science and Engineering from NIT Durgapur, India Research Interests: Dr. Mukherjee's work addresses challenges in cloud and IoT systems, including performance anomaly detection, resource contention management, and machine learning-driven optimization. His Ph.D. introduced a novel model-based runtime performance management technique that avoids reliance on hardware counters, enabling cloud subscribers to autonomously manage application performance. He has also contributed to frameworks for IoT security, FaaS scalability, and DevOps automation. Key Research Contributions: His publications explore predictive auto-scaling, interference modeling, and anomaly detection using spectrograms and CNNs. He co-developed PRIMA and RAD systems for subscriber-driven performance mitigation in cloud environments. Awards: No specific awards mentioned in the provided text. Lab and Collaborations: Active in the CERAS Lab at York University (during his postdoc) and collaborates with the University of Calgary on research programs. His work bridges academic and industrial challenges in cloud computing and IoT through interdisciplinary approaches.
Pierre-Hugues Beauchemin is a Professor of Physics & Astronomy at Tufts University, affiliated with the School of Arts and Sciences. His research focuses on experimental high-energy physics, particularly within the ATLAS experiment at CERN’s Large Hadron Collider (LHC). He leads efforts in precision measurements of the Standard Model, searches for dark matter via missing energy signatures, and optimization of the ATLAS trigger system, with a focus on the Missing Energy trigger. Education: PhD in High Energy Physics, McGill University (2005) MSc in High Energy Physics, Université de Montréal (2000) BSc in Mathematics and Physics, Université de Montréal (1999) Research Interests: Experimental High Energy Physics, dark matter detection, quantum chromodynamics (QCD), Standard Model precision studies, and epistemological aspects of particle physics experiments. His work combines data analysis at the LHC with software development for detector operations. Grants & Funding: Recipient of U.S. Department of Energy grants for High Energy Physics research at Tufts (2018–2021 and ongoing). Professional Roles: Coordinator of the ATLAS ETmiss Trigger Group (2014–2016), Monte Carlo Production and Simulation Trigger Coordinator (2016), and contributor to the Standard Model Group at CERN. Active in workshops such as the Corfu2017 conference on particle physics. Labs/Teams: Integral member of the ATLAS Collaboration, focusing on detector operations and data analysis for new physics searches.
Patrick Florance is the Director of Research Technology at Tufts University, where he leads Tufts Technology Services’ support for High-Performance Computing, research storage, scientific instrumentation, and data science. He is concurrently an affiliate of the Department of Urban & Environmental Policy & Planning in the School of Arts and Sciences and a senior instructor at the Fletcher School of Law and Diplomacy. Education Bachelor of Arts, University of Oregon, Eugene, United States Master of Arts, Geography – Geographic Information Science, City University of New York – Hunter College, New York, United States Research & Scholarly Interests Florance’s scholarship and service converge on the design, deployment, and governance of open-source geospatial infrastructures. His work encompasses: Global and humanitarian mapping, crisis mapping, and geospatial support for disaster response Development of the Open Geoportal (OGP) Federation — a Sloan-funded collaborative platform for sharing geospatial data across universities 3D GIS, remote sensing, UAV/drone workflows, and spatial data infrastructures for urban modeling Digital humanities, natural language processing, and data-mining approaches to historical and textual geodata Geospatial pedagogy, open-data advocacy, and capacity-building in the developing world Publications & Intellectual Trajectory Across more than two decades, Florance has authored or co-authored scholarly articles, software reviews, and special journal issues that advance both technical architectures and sociotechnical practices for geospatial information curation. His writings trace a trajectory from foundational concerns of GIS collection development in academic libraries to contemporary challenges of real-time, open, and ethical crisis mapping. Scientific Awards & Grants Alfred P. Sloan Foundation – Open Geoportal Cloud (OGP) Federation (US$ grant, 2013) University Service & Leadership Patrick chairs or serves on multiple university committees driving data-intensive research strategy: Data Analytics Steering Committee, School of Arts & Sciences Digital Humanities Steering Committee, Tufts University Data-Intensive Scholarship Center (DISC) Advisory Committee on Infrastructure and Services (ACIS) GIS Steering Committee Research Data Services Committee Labs, Teams & Infrastructure He directs the Tufts Data Lab , a campus hub for GIS, statistics, visualization, and machine-learning services, and oversees the Open Geoportal Project , a multi-institutional consortium providing federated discovery and access to geospatial data sets. His team supports thousands of researchers university-wide with high-performance compute clusters, research storage arrays, and discipline-specific scientific instrumentation.
Dr. Bingzhe Li is an Assistant Professor in Computer Science at UT Dallas' Erik Jonsson School of Engineering. His research at the Lab for Intelligent Storage and Computing (Lab4ISC) focuses on DNA storage systems, machine learning infrastructure, and energy-efficient computing architectures. Awarded the NSF CAREER Award (2025) and recognized for Best Paper nominations at leading conferences. Research spans DNA storage capacity optimization, reinforcement learning for hybrid SSDs, Kubernetes storage optimization, and stochastic computing architectures. Recent publications demonstrate innovations in out-of-core graph processing and blockchain storage systems. Leads multiple NSF/NASA-funded projects on DNA storage and convertible SSDs. Teaches Digital Logic and Computer Architecture courses. Supervises 8 PhD students and 3 master's candidates in storage systems and low-power computing research.
Professor Moi Hoon Yap is a Professor of Image and Vision Computing and Lead of Human-Centred Computing at The Manchester Metropolitan University. Her research focuses on computer vision, deep learning, and medical image analysis, particularly in early cancer detection and diabetic foot ulcer tools. She leads projects funded by The Royal Society, EU, EPSRC, Innovate UK, and industry partners. She is an Associate Editor of the Journal of Computers and Programs in Biomedicine and has developed datasets and grand challenges for reproducible research, such as the DFU-2021 challenge. Her work includes facial analysis, gesture interpretation, and human behavior quantification. Key Projects: FAST Healthcare NetworksPlus Award (2020-2021), Royal Society PhD Studentship (2018-2022), FootSnap Cloud Infrastructure (2019-2021). Awards: Royal Society Industry Fellowship, Marie Skłodowska-Curie Innovative Training Network Grant. Research Interests: Medical imaging, facial/gesture analysis, human behavior analysis, dataset creation, and sustainable software development. Professor Yap supervises PhD students and teaches Data Analytics, Deep Learning, and related courses. She is actively involved in international collaborations to advance biomedical data sharing and federated learning mechanisms.
Prof Alan Patching is a Professor and Semester Teaching Fellow at Bond University's Faculty of Society & Design, affiliated with the Centre for Comparative Construction Research. Contact: apatchin@bond.edu.au. His research focuses on psychological stress in construction management, mindfulness-based interventions in maternal health, interoceptive awareness in PTSD treatment, collaborative design methodologies, and the societal impact of esports. Research interests include integrating psychological studies with construction industry challenges, leveraging technologies like BIM and Lean processes in education, and exploring esports' potential in major sports events. He has presented on topics such as stress management in construction and hypnosis in therapy. No scientific awards are explicitly listed. Advising and grants: Supervised a doctoral thesis on stress attitudes in construction (2019). Active in interdisciplinary research collaborations, particularly with the Centre for Comparative Construction Research.
Dr. Isaac Kofi Nti is an Assistant Professor in the School of Information Technology at the University of Cincinnati, with over 16 years of interdisciplinary research experience in applied machine learning, health informatics, cybersecurity, and data governance. His work emphasizes responsible AI deployment in high-impact domains including healthcare, finance, and education. He concurrently holds affiliations with Ghanaian institutions (University of Energy and Natural Resources and Sunyani Technical University) and serves as a Visiting Assistant Professor at Cincinnati until 2024. Education PhD in Computer Science, University of Energy and Natural Resources, Ghana (2021) MSc in Information Technology, Kwame Nkrumah University of Science and Technology, Ghana (2016) BSc Computer Science, Catholic University of Ghana (2011) Higher National Diploma in Electrical & Electronic Engineering, Sunyani Technical University, Ghana (2007) Research Focus Dr. Nti develops lightweight, explainable AI systems for cybersecurity, healthcare diagnostics, agricultural optimization, and educational technology. His research integrates secure data analytics, ethical AI frameworks, and cloud-based learning infrastructures. Current projects explore generative AI in education, predictive modeling for disease outbreaks, and blockchain applications for health data verification. Publication Trends His 60+ publications (2022-2024) demonstrate strong emphasis on ensemble learning methods, healthcare AI applications, and cybersecurity innovations. Recent works frequently utilize hybrid models (LSTM/XGBoost/StackNet) for fraud detection, disease prediction, and renewable energy forecasting. Awards & Grants Provost Office Strategic Collaborative Faculty Team Award (2024-2025): $19,200 for AI integration in higher education Faculty Development Grant (2023-2024): $10,038 for emerging technology training Faculty Incentive Awards for Research (CECH, UC 2022-2024) Teaching & Service Teaches graduate/undergraduate courses in machine learning, cybersecurity, and data technologies. Leads multiple university committees including PhD Admissions Review and Applied Research teams. Professional memberships include ACM, IEEE, and AAAI.
Pere Millán Marco is an Associate Professor in the Department of Computer Engineering and Mathematics (DEIM) at Universitat Rovira i Virgili (URV), Tarragona, Spain. He serves as coordinator for Non-permanent lecturers. His research focuses on computer communications, mobile/sensor networks, and IoT, with emphasis on quality prediction and performance optimization in wireless environments. Education: M.Sc. in Computer Engineering (Polytechnic University of Catalonia, 1992); PhD in Computer Engineering (URV, 2018). Research Interests : Specializes in mobile and sensor network architectures, underwater acoustic networks, real-time communication protocols, and low-cost hardware solutions for educational and environmental applications. His work integrates time series analysis, predictive modeling, and social behavior patterns to enhance network efficiency. Publications Trends : Recent work emphasizes IoT applications in environmental monitoring (e.g., deep aquifer pumping systems), optimization of underwater acoustic networks, and low-cost multicomputer systems for teaching. Consistently explores predictive techniques for network topology and quality-of-service improvements in ad hoc and community networks. Awards & Recognition : Holds a granted US patent related to location-based information systems. Advising & Infrastructure : Involved in DEIM's teaching laboratory development. Active in organizing international conferences like UCAmI and VISIGRAPP. Member of the CloudLab research group, advancing cloud and distributed computing solutions.
Micah Beck is an Associate Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, within the Tickle College of Engineering. His research focuses on foundational challenges in computer networking, internet architecture, and system design principles like minimal sufficiency. He holds a PhD in Computer Science from Cornell University (1992), an MS from Stanford (1980), and a BA from the University of Wisconsin (1979). Education: PhD in Computer Science, Cornell University, 1992 MS in Computer Science, Stanford University, 1980 BA in Mathematics & Computer Science, University of Wisconsin, 1979 Research Interests: Beck critiques traditional internet architecture paradigms, exploring flaws in assumptions like end-to-end arguments and TCP reliability. He advocates for minimal sufficiency principles to enhance deployment scalability. Recent work addresses broadband accessibility, digital monopolies, and exposed buffer architectures for stateful networking. His writing often bridges theoretical rigor with practical system design critiques. Recent Article Themes: His 2025 article Hit the Goalie analyzes formal proof misapplications in engineering systems, while 2024's End-to-End Arguments re-evaluates foundational networking principles. He co-authored Breaking Up Digital Monopolies (2023) proposing regulatory frameworks for data governance. Awards & Grants: No explicit awards listed, but his work has influenced networking discourse through venues like ACM and IEEE. Active in initiatives like Cybercosm and Exposed Buffer Architecture development. Teaching & Advising: Teaches operating systems (COSC 361), computer networks (ECE 453/553), and cloud/edge computing (COSC 494/594). Projects include xv6 kernel modifications and network protocol analysis. No formal advisee roster provided. Labs/Teams: Collaborates on projects like the Wildfire Data Logistics Network and Cybercosm ecosystem. Engages with industry through presentations at conferences like IEEE MASS and ACM workshops.
Markos Anastasopoulos is Associate Professor at the National and Kapodistrian University of Athens, specializing in optical/wireless networks and mobile computing. His research focuses on 5G/6G network convergence, intent-based management, and AI-driven optimization for telecommunications. Recent publications address THz-optical integration, federated learning in transport networks, and semantic-aware radio systems. Applied work includes intelligent asset management for railways and techno-economic analyses of network deployments. Recognized with best dissertation and best paper awards, his research bridges theoretical networking with industrial applications in transportation and cloud infrastructure.
Dong Chen is an Associate Professor in the Department of Computer Science at the Colorado School of Mines. His research focuses on building data-driven experimental systems in Cyber-Physical Systems (CPS), IoT, Embedded AI, and Embodied AI, with applications in smart devices, homes, cities, and renewable energy systems. He leads the Next Generation Cyber-Physical Systems Laboratory (CPSLab), emphasizing open-source systems and datasets. Dr. Chen holds PhDs in Electrical and Computer Engineering (2018, University of Massachusetts Amherst) and Computer Science (2014, Northeastern University). His work addresses security, privacy, sustainability, and efficiency in smart environments. Notable contributions include SolarFinder, SolarTrader, PrivacyGuard, and VoiceAttack, which tackle challenges in IoT privacy, energy trading, and adversarial attacks. He received the NSF CAREER Award (2023) and is a member of Sigma Xi, ACM, AAAI, and IEEE. His research spans system design, AI applications, and cross-cutting domains like solar energy modeling and edge computing. Current projects include AgileDART (edge stream processing) and SolarDetector (satellite-based PV array identification). Advising and collaborations: Dr. Chen seeks PhD and undergraduate students with strong CS/EE backgrounds. His lab focuses on CPS/IoT security, energy systems, and AI-driven solutions. He has published extensively on topics ranging from smart grid optimization to adversarial machine learning.
Nihat Altiparmak is an Associate Professor in the Department of Computer Science and Engineering at the University of Louisville. He holds a B.S. in Computer Engineering from Bilkent University (2007) and a Ph.D. in Computer Science from the University of Texas at San Antonio (2013). His research focuses on data storage systems, parallel/distributed systems, high-performance computing, and cloud computing. He directs the Computer Systems Laboratory at the University of Louisville and has received NSF awards for his work on storage optimization and big data infrastructure. Education: B.S., Computer Engineering, Bilkent University, 2007 M.S., Computer Science, University of Texas at San Antonio, 2012 Ph.D., Computer Science, University of Texas at San Antonio, 2013 Research interests emphasize adaptive parallel storage systems and efficient data retrieval techniques. His work has been published in top-tier journals like IEEE Transactions on Computers and ACM Transactions on Storage. Notable contributions include frameworks for optimizing I/O performance in heterogeneous storage environments. Awards include NSF CRII (2017) and MRI (2018) grants for advancing storage technologies.
Dr. Andrew Yang is an Associate Professor of Computer Science and Computer Information Systems at the University of Houston-Clear Lake's College of Science and Engineering. His research focuses on computer security, wireless and mobile computing, networking, performance measurement, and cybersecurity education. His publications demonstrate a consistent focus on cybersecurity challenges, educational frameworks, and emerging technologies. Recent work explores AI ethics, IoT security, blockchain applications, and cybersecurity workforce development, reflecting a pattern of addressing contemporary technological vulnerabilities through both technical solutions and pedagogical approaches.
Professor Ian Ferguson is a faculty member in the Department of Earth Sciences at the University of Manitoba, affiliated with the Clayton H. Riddell Faculty of Environment, Earth, and Resources. He holds a Ph.D. in Geophysics and B.Sc. (Hons) in Geology/Geophysics from the Australian National University. His research focuses on electromagnetic methods to study Earth's crust and upper mantle, including tectonic history, groundwater systems, environmental geophysics, archaeological investigations, and carbon sequestration monitoring. Notable projects include magnetotelluric surveys in Canada's Cordillera and Superior Craton, as well as geophysical studies at the Aquistore CO2 sequestration site. Dr. Ferguson teaches advanced courses such as GEOL 3810 - Applied Geophysics and GEOL 7820 - Environmental Geophysics , emphasizing practical skills in geophysical data analysis and field methodology. His work integrates cutting-edge techniques like deep learning algorithms for geophysical inversion and multidisciplinary approaches in Arctic archaeology. His publications span over 40 years, addressing diverse topics from continental-scale tectonics to near-surface environmental applications. Collaborations include international projects like the SNORCLE initiative and domestic studies on Canadian geohazards and resource exploration.
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