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Kewei ShaView profile

Associate Professor

• Data Analytics
• Edge Computing
• Security and Privacy
• +3 more

Dr. Kewei Sha is an Associate Professor at the University of North Texas (UNT) in the College of Information. Previously, he held positions as Associate Professor and Department Chair at Oklahoma City University (OCU) and the University of Houston-Clear Lake (UHCL). He earned a Ph.D. and M.S. from Wayne State University and a B.S. from East China University of Science and Technology. His research focuses on Data Analytics, Edge Computing, Security and Privacy, Blockchain, and IoT, with over $5M secured in research grants from NSF, NASA, and other institutions. He has published over 70 peer-reviewed papers and serves as an Associate Editor for IEEE IoT Journal, Smart Health, and Computing. Dr. Sha has received awards including the UHCL President’s Outstanding Research Award and IEEE Outstanding Leadership Award, and holds senior membership in ACM and IEEE. He chairs conferences like IEEE MOST 2024 and ACM/IEEE SEC 2023. His recent work includes securing NSF funding for edge-based multi-robot systems and NSF Noyce Scholarships for STEM teacher training. Key projects involve EdgeBrain for edge video analytics and ElasticEdge for live video processing. He has pioneered frameworks for data governance, secure cloud storage, and disaster rescue UAV systems. Dr. Sha also develops educational tools like AR therapy systems for autistic children and network forensics labs for teaching institutions.

• Machine Learning
• Applied Artificial Intelligence
• Wildlife Conservation
• +9 more

Carl Chalmers is a Senior Lecturer in Machine Learning and Applied Artificial Intelligence at the School of Computer Science and Mathematics, Liverpool John Moores University, since October 2018. He holds a PhD in Computer Science (2014-2017) and a BSc (Hons) Computer Science (2010-2014) from the same institution.

• Distributed Computing
• Internet Computing
• Cloud Computing
• +9 more

George Pallis is a Professor in the Department of Computer Science at the University of Cyprus, where he also serves as Associate Director of the Laboratory of Internet Computing. He is a programme director for the Master in Data Science and leads major international research initiatives funded by the European Commission, national agencies, and industry partners such as Google. His academic foundation includes a BSc and PhD in Informatics from Aristotle University of Thessaloniki, Greece. PhD, Department of Informatics, Aristotle University of Thessaloniki, Greece, 2006 BSc, Department of Informatics, Aristotle University of Thessaloniki, Greece, 2001 Dr. Pallis’s research focuses on Distributed and Internet Computing , with specialized interests in Big Data Analytics, Cloud/Edge/Fog Computing, Content Delivery Networks, and Online Social Networks . His work bridges theoretical innovation and practical deployment, particularly in scalable and energy-efficient computing infrastructures. He has contributed to international standards through the German Institute for Standardization (DIN) and has developed frameworks for cloud elasticity, fog emulation, and misinformation detection. His 15 most recent publications reflect a strong trend in edge and fog computing, AI-driven analytics, privacy-preserving data processing, and misinformation detection . These works span high-impact venues such as IEEE IC2E, IEEE/ACM SEC, IEEE CloudCom, and IEEE BigData, with increasing integration of machine learning and human-in-the-loop systems. Dr. Pallis has received multiple scientific awards, including: Best Paper Award, IEEE CloudCom 2024 Best Paper Award (2nd place), IEEE/ACM UCC 2023 Best Paper Award, IEEE IoTDi 2022 Best Student Paper, IEEE ISCC 2022 Best Paper, IEEE BigData 2016 Best Paper, ICSOC 2014 Best Demo Award, ACM/IEEE SEC 2020 World’s Top 2% Scientists (Stanford) Golden Core Member, IEEE Computer Society He has supervised several PhD students in areas such as fog computing emulation, big data in entrepreneurship, and polarization detection. His research is supported by over 5.5 million euros in grants from the European Commission (e.g., RAINBOW, UNICORN, ICARUS), the Research Promotion Foundation in Cyprus, and industry. He has served as General Chair of IEEE/ACM SEC 2024 and IEEE IC2E 2024, and as Editor-in-Chief of IEEE Internet Computing (2019–2023), now holding the Emeritus title. He is currently Associate Editor for the Computing Journal (Springer). Dr. Pallis leads the Laboratory of Internet Computing, a hub for research in cloud, edge, and social computing. The lab develops tools like Fogify for emulation, RAINBOW analytics, and Check-It for fake news detection, fostering collaboration across academia and industry.

• Waste and Circular Economy
• Plastic Recycling
• Tracer-Based Sorting
• +7 more

Christoph Olscher is a Research Associate at the Institute for Waste and Circular Economy, Department of Landscape, Water and Infrastructure, University of Natural Resources and Life Sciences Vienna (BOKU). He holds an M.Sc. in Technical Environmental Management and Ecotoxicology from FH Technikum Vienna and a B.Sc. in Biology with a focus on Ecology. His academic and research career includes roles as a Young Researcher and Young Lecturer at FH Technikum Vienna (2019–2022) and ongoing research engagement at BOKU since 2021. His research focuses on waste and circular economy , particularly plastic recycling technologies , tracer-based sorting , and the safety and sustainability of advanced materials . He investigates the application of marker materials such as rare earth oxides to improve the sorting efficiency of plastic wastes. His work also encompasses the Safe and Sustainable by Design (SSbD) framework, especially in the development of biobased, recyclable composites for automotive and aerospace applications, and the environmental safety assessment of nanomaterials like nanoscale zinc oxide. The recent publications and conference contributions of Christoph Olscher reflect a strong trend toward sustainable materials engineering , environmental safety , and innovative recycling technologies . His work bridges polymer science, environmental technology, and regulatory frameworks, aiming to enhance circularity in industrial material flows. Key subfields include tracer-based sorting, spectroscopic waste characterization, chemical recycling of epoxy composites, and risk assessment of nanomaterials. His scientific contributions have been presented at major international events such as SETAC Europe, NanoTox, and the Sardinia Symposium on Waste Management. While no formal scientific awards are listed, his active participation in EU- and FFG-funded research projects underscores his role in advancing sustainable material solutions. Christoph Olscher is involved in knowledge transfer through lectures and stakeholder workshops on the safety and sustainability of nanomaterials and plastic waste management. He has not supervised any theses to date. He is part of research teams working on projects like REPOXYBLE and SSbD implementation for advanced materials, contributing to both fundamental and applied research in circular economy strategies.

Ahmet SoyluView profile

Professor

• Ontology-driven information systems
• Semantic Web
• Knowledge representation
• +4 more

Ahmet Soylu is currently Dean of the School of Doctoral Studies and Professor of Computer Science at Kristiania University of Applied Sciences in Oslo, Norway. He also holds an Adjunct Professor position at the University of Oslo (UiO) . Previous roles: Full Professor at OsloMet – Oslo Metropolitan University (Innovation, Digital Transformation, Sustainability group), Norwegian University of Science and Technology (NTNU) Researcher background: Senior Scientist at SINTEF Digital, Senior Engineer at DNV, Postdoctoral Fellow at UiO, Visiting Researcher at University of Oxford PhD in Computer Science (2012) from University of Leuven, Belgium His research focuses on ontology-driven information systems with a human-computer interaction perspective, particularly for industrial data integration and Big Data using Semantic Web and Linked Data technologies. Key topics include: Visual query systems for non-technical users End-user development frameworks Digital transformation in enterprise environments Knowledge representation for data access Recent publications include work on semantic analytics in industrial contexts like Siemens and Statoil, with a particular emphasis on streaming data and static data integration . He has contributed to the development of the OptiqueVQS system for visual query formulation. As a project leader, he has coordinated major EU-funded initiatives such as: TheyBuyForYou (Horizon 2020) Optique (EU FP7) iCamp , ROLE , LEGIS LEFIS , TREE (FP6/FP7) He serves on editorial boards for: Journal of Web Semantics (JoWS) Transactions on Graph Data and Knowledge (TGDK) Professional activities include organizing: Declarative AI series (RuleML+RR) Reasoning Web Summer School DecisionCAMP conferences

Scott ShenkerView profile

Professor

• Networking
• Software-Defined Networks
• Datacenter Infrastructure
• +4 more

Scott Shenker is a Professor at the University of California, Berkeley, and a Research Director at the International Computer Science Institute (ICSI). He previously served as Chief Scientist at ICSI (2012-2021) and held roles at Xerox PARC, University of Southern California, and Cornell University. PhD in Physics, University of Chicago (1983) ScB in Physics, Brown University (1978) His research spans Internet architecture, software-defined networks, datacenter infrastructure, and game theory. He has contributed to distributed systems, privacy mechanisms, and network protocols, with a focus on scalable and resilient designs. Recent work includes advancements in memory management for distributed systems, cloud resource optimization, and SDN frameworks. His 15 most recent publications highlight innovations in datacenter networking, packet scheduling, and storage efficiency. IEEE Computer Society Women of ENIAC Computer Pioneer Award (2023) Fiat Lux Faculty Award (2022) IETI Distinguished Fellow (2020) National Academy of Sciences Member (2019) Paris Kanellakis Theory and Practice Award (2017) ACM SIGCOMM Test of Time Paper Awards (2017, 2011, 2006) IEEE Internet Award (2006) ACM and IEEE Fellowships National Academy of Engineering Member (2012) Shenker has advised numerous PhD and Master’s students, including A. Ermolinskiy, M. Perry, Y. Harchol, and T. Das. His research teams at UC Berkeley and ICSI explore next-generation networking solutions, including open-source frameworks like Spark and Mesos.

Patrick VelteView profile

Professor

• Financial Accounting
• External Audit
• Corporate Governance
• +11 more

Prof. Dr. Patrick Velte holds the Professorship for Business Administration with specializations in Accounting, Auditing & Corporate Governance at Leuphana University of Lüneburg. He is affiliated with both the Institute for Management, Accounting & Finance and the Centre for Sustainability Management within the Faculty of Sustainability. His research focuses on three interconnected domains: Business Administration : Financial reporting quality, audit effectiveness, corporate governance mechanisms, and earnings management Sustainability Science : ESG reporting frameworks, sustainability assurance, integrated reporting, board diversity, and climate-related disclosures Legal Studies : Accounting law, corporate law, and tax law implications of sustainability transitions Analysis of his 15 most recent publications reveals dominant research streams in sustainability reporting regulation (especially EU Taxonomy and CSRD/ESRS implementation), corporate governance reforms, and the intersection of audit quality with ESG verification. His work consistently examines European evidence through empirical-quantitative methods, with strong policy implications for the EU Green Deal framework. Professor Velte has received significant recognition including: ScholarGPS Highly Ranked Scholar (2020-2024) with #1 global ranking in Accounting M&T Impact Award 2024 for research contributions Ranked among top business economics researchers in DACH region by WirtschaftsWoche He leads multiple research projects including doctoral studies on supply chain transparency and capital markets, supported by programs like the Deloitte-Stiftung Stipendienprogramm. His work informs regulatory bodies and professional practice through ongoing knowledge transfer activities.

• Food Science
• Dioxin
• Tandem Mass Spectrometry
• +5 more

Dr. Stefan van Leeuwen is a senior researcher at Wageningen Food Safety Research , part of Wageningen University & Research. He specializes in the identification and mitigation of chemical contaminants in food systems. Research focuses on dioxins, PCBs, PFAS, and processing contaminants like MCPD esters and glycidyl esters. Active in analytical method development using LC-MS/MS and tandem mass spectrometry for food safety assessments. Recent work explores PFAS regulation, circular economy food systems, and contaminant detection in waste streams. PhD Supervision : Co-promotor for projects on PFAS accumulation in fish and chlorinated paraffin uptake in agricultural products. Key Collaborations : Engaged in international research initiatives with teams from The Netherlands, UK, and beyond.

Abid MehmoodView profile

Associate Professor

• Machine Learning
• Deep Learning
• Computer Vision
• +4 more

Dr. Abid Mehmood serves as an Associate Professor at The Beacom College of Computer & Cyber Sciences, Dakota State University, leveraging over 20 years of combined academic and industry expertise to advance artificial intelligence applications in critical domains including healthcare, precision agriculture, and surveillance systems. His educational foundation includes: Ph.D. in Computer Science from Universiti Teknologi Malaysia (2014) M.Sc. in Computer Science from Quaid-i-Azam University (2001) B.Sc. in Computer Science from University of Peshawar (1998) Dr. Mehmood's research centers on applied machine learning and deep learning , with pioneering work in computer vision for medical diagnostics (skin lesion classification, glaucoma detection), precision agriculture solutions (automated fruit disease identification, crop yield estimation), and surveillance technologies (real-time anomaly detection in video streams). His predictive analytics expertise extends to healthcare sentiment analysis, financial forecasting, and driver behavior monitoring, consistently translating theoretical AI advances into practical implementations across diverse sectors. Analysis of his 15 most recent publications (2021-2024) reveals a pronounced interdisciplinary focus, with 60% dedicated to healthcare applications (medical imaging diagnostics), 27% to agricultural technology, and 13% to surveillance/security systems. This trajectory demonstrates strategic alignment with societal needs while maintaining technical rigor in computer vision and deep learning architectures. No scientific awards were documented in the provided materials. Dr. Mehmood has secured substantial research funding through 14 competitively awarded grants (2021-2024) totaling SAR 400,000+ from Saudi Arabian institutions, including King Faisal University and the Ministry of Education. His grant portfolio demonstrates exceptional breadth: Healthcare Innovation : Driver depression monitoring systems, skin lesion classification frameworks, glaucoma diagnostics, and obesity/fatty liver correlation studies Agricultural Technology : Automated fruit disease identification and crop yield estimation using AI-driven remote sensing Security Systems : Lightweight anomaly detection frameworks for video surveillance Cross-Domain Applications : Stock price prediction models, vaccine sentiment analysis, and aspect-oriented programming solutions

• Machine Learning
• Deep Learning
• Data Mining
• +3 more

Markus Goldstein is a Professor of Computer Science and Data Science at Ulm University of Applied Sciences (THU), where he also serves as Head of the Institute of Computer Science. His office is located in room Q229 at Albert-Einstein-Allee 53-55 in Ulm, Germany, and he can be reached at +49 731 96537-418 or Markus.Goldstein@thu.de. Professor Goldstein's primary research focuses on machine learning, deep learning, data mining, anomaly detection, and data science with noSQL databases. His work bridges theoretical foundations with practical applications, particularly in unsupervised anomaly detection methods and their implementation across various domains including security systems and big data analytics. His research program demonstrates consistent contributions to developing efficient algorithms for outlier detection and evaluation frameworks for comparing different approaches. His publication record shows a clear research trajectory focused on unsupervised anomaly detection, with recent emphasis on explainability in outlier detection systems (2023), comparative evaluations of algorithms (2016, 2015), and practical applications in security contexts (2013-2014). His work spans both theoretical contributions (such as FastLOF algorithm development in 2012) and applied research (including document authentication and DDoS mitigation). As an educator, Professor Goldstein teaches Programming in Java (I and II), Introduction to Computer Science, Databases, Machine Learning, Data Warehousing NoSQL and Big Data, and Advanced Machine Learning at the Master's level. He maintains regular office hours on Wednesdays at 2:00 PM with registration via email, and actively encourages student engagement through final papers and projects in his research areas.

• Adversarial knowledge discovery
• Data analytics
• Cybersecurity
• +12 more

David Skillicorn is a Professor at the School of Computing, Queen's University and an Adjunct Professor in the Mathematics and Computer Science department at the Royal Military College . His research focuses on adversarial knowledge discovery with applications in terrorism, cybersecurity, crime, fraud, and financial report analysis. He leads the Adversarial Analytics research group and contributes to social network analysis and human behavior modeling . Research Interests: Adversarial data analytics Cybersecurity and fraud detection Social network analysis with typed edges Deception detection in textual data Privacy-preserving systems design High-dimensional data modeling Recent Publications: Focus on security informatics, counterterrorism analytics, and adversarial prediction frameworks. Key themes include novel document ranking systems, robust clustering methods, and semantic sensor development for anomaly detection. Scientific Contributions: 2009 IEEE Technical Achievement Award for adversarial analytics Best Paper at IEEE WSE2011 for service-oriented web analysis Author of foundational texts on high-dimensional datasets and adversarial knowledge discovery Teaching Activities: Coordinates courses like CISC251 (Introduction to Analytics), CISC447/CISC866 (Cybersecurity), and specialized grad courses in cybersecurity and policing. Develops pedagogical resources for effective learning techniques and hypermedia-based education . Academic Genealogy: Ph.D. under Ralph Stanton (University of Manitoba, 1981), with lineage connections to Erdős (Erdős number 3), Gauss, and other mathematical luminaries.

Stuart SimpsonView profile

Adjunct Professor

• Water and Sediment Quality Assessment
• Environmental Analytical Chemistry
• Sediment Ecotoxicology
• +7 more

Dr. Stuart Simpson serves as a Senior Principal Research Scientist in CSIRO Environment and leads the Healthy Communities & Ecosystems group within the Industry Environments program. He also holds an Adjunct Professor position at the University of New South Wales since 2019. His work focuses on developing threat surveillance and risk forecasting systems to protect Australian communities from environmental shocks and manage waste streams. Dr. Simpson's research interests center on water and sediment quality assessment, with particular expertise in the quantification of chemical contaminants, their speciation, bioavailability, and ecotoxicological effects. His work spans environmental analytical chemistry, sediment ecotoxicology, and the development of frameworks for assessing environmental impacts. He has made significant contributions to Australia's sediment quality guidelines and pioneered wastewater surveillance systems for pathogen detection. His recent publications demonstrate a strong focus on environmental surveillance systems, particularly using wastewater to monitor pathogens like SARS-CoV-2, antimicrobial resistance genes, and other contaminants. His work bridges environmental science, public health, and risk assessment, with applications in both freshwater and marine ecosystems. 2006 Land and Water Australia Eureka Prize for Water Research 2006 CSIRO Medal for Research Achievement 2015 CSIRO Newton Turner Award 2020 CSIRO Land and Water, Science Excellence Award for 'Wastewater testing for early community detection of COVID-19 Team' 2021 Finalist - Sir Ian McLennan Impact Medal for 'COVID sewage EcoSurveillance' 2022 Finalist - Sir Ian McLennan Impact Medal for 'SARS-CoV-2 wastewater surveillance' Dr. Simpson leads three major research teams: EcoSurveillance Systems, Green Resource Recovery, and Waste Beneficiation & Storage. His work has significant implications for environmental protection, public health surveillance, and sustainable resource management. He has contributed to numerous national guidance documents including Australia's Sediment Quality Guidelines and National Assessment Guidelines for Dredging.

Ivo V. StoepkerView profile

Researcher

• Statistics
• Computer Science
• Anomaly Detection
• +5 more

Ivo V. Stoepker is a University Researcher at the Department of Statistics within the Mathematics and Computer Science school at Eindhoven University of Technology (TU/e). His work focuses on anomaly detection, blockchain analytics, and statistical methods in disease surveillance. Email: i.v.stoepker@tue.nl Research Interests: Statistics and probability theory Anomaly detection in high-dimensional data Bitcoin transaction analysis and blockchain modeling Monte Carlo methods and permutation-based testing Epidemiological surveillance systems Recent Publications: 2025 work on sparse anomaly detection frameworks, 2024 contributions to Bitcoin transaction efficiency and multi-stream anomaly detection, and interdisciplinary research in AI-supported disease outbreak detection.

Sebastian FischmeisterView profile

Professor

• Embedded Systems
• Distributed Systems
• Formal Methods
• +8 more

Sebastian Fischmeister is a Professor and NSERC/Magna Industrial Research Chair in Automotive Software for Connected and Automated Vehicles at the Department of Electrical and Computer Engineering, University of Waterloo. His research focuses on systems at the intersection of software technology, distributed systems, and formal methods, with applications in automotive systems, avionics, and medical devices. He has pioneered frameworks for scalable location-based pervasive computing and verifiable real-time communication schedules, contributing to the ASTM F29.21 standard. Education: Dipl.-Ing. in Computer Science (Vienna University of Technology, 2000), Ph.D. in Computer Science (University of Salzburg, 2002) Research Themes: Real-time embedded systems, runtime monitoring, security analysis, data analytics for validation, and performance evaluation. Scientific Awards: APART Stipend (2005) Ontario Early Researcher Award (2014) Multiple best paper and tool awards He is an ACM Distinguished Speaker and actively participates in organizing conferences such as ESCAR, RTSS, DATE, and ICPE. His work includes significant contributions to anomaly detection, cybersecurity in automotive networks, and runtime verification techniques under unreliable conditions.

Venkat ArunView profile

Assistant Professor

• Networked systems
• Formal methods
• Internet congestion control
• +4 more

Venkat Arun is an Assistant Professor in the Department of Computer Science at the University of Texas at Austin, College of Natural Sciences. His research focuses on making networked systems robust and performant through the application of formal methods. Previously, he completed his PhD at MIT and undergraduate studies at IIT Guwahati. He co-leads the UT Networked Systems Lab (UTNS) and has developed algorithms deployed at Meta. His research interests center around networked systems and formal methods, with a focus on developing conceptual, mathematical, and automated tools to design provably performant networked systems. Arun's work spans internet congestion control, video streaming, privacy-preserving computation, wireless networks, and mobile systems. A common theme across his research is using theoretical ideas to gain insights into real-world systems that would be difficult to discover otherwise. His recent publications demonstrate a strong focus on performance verification and synthesis for networked systems, with significant contributions to congestion control algorithms. His work bridges theoretical foundations with practical implementations, as evidenced by the deployment of his algorithms at Meta. The research spans formal verification techniques, network protocol design, and performance analysis across various networked applications. Scientific Awards: MIT EECS G. M. Sprowls PhD Thesis Award in Computer Science (2024) ACM SIGCOMM Doctoral Dissertation Award Runner-Up (2024) Marconi Society Young Scholar Award (2023) ACM SIGCOMM best student paper award (2022) ACM SIGCOMM best paper award (2017) MIT Jacobs Presidential Fellowship (2017) President of India Gold Medal - IIT Guwahati (2017) KVPY Government of India Scholarship (2013) Venkat Arun currently advises three PhD students: Haoyu Li (co-advised with Aditya Akella), Tony (Jia) Pan (co-advised with Isil Dillig), and Saarth Deshpande (co-advised with Neeraja Yadwadkar). His research group is funded by NSF grants including "Nets: Medium: An End-To-End Framework For Network" (2024) and "FMitF: Performance Verification for Networked Systems" (2024), as well as a generous gift from Mibura (2024). The group is managed by Destiny Turner. He leads several major research projects including Performance Verification and Synthesis, "Solving" Congestion Control, and Metasurfaces with Thousands of Antennas. Arun teaches CS 395T: Performance Analysis of Networked Systems and CS 356: Computer Networks at UT Austin.