جست‌وجوی استاد و پژوهشگر

Jiayang Sunمشاهده پروفایل

استاد

• Simultaneous Inference
• Multiple Testing
• Data Mining
• +۷ مورد دیگر

Dr. Jiayang Sun is a Professor, Bernard Dunn Eminent Scholar, and Chair of the Department of Statistics at George Mason University’s College of Engineering and Computing. She holds a PhD in Statistics from Stanford University and previously served as Professor and Director of the Center for Statistical Research, Computing, and Collaboration (SR2c) at Case Western Reserve University. Her leadership extended to a role as the inaugural ASA/ACM/AMS/IMS/MAA/SIAM Science & Technology Policy Fellow at the USDA ARS from 2019-2020. Dr. Sun’s research focuses on statistical methodologies including simultaneous inference, multiple testing, biased sampling, and machine learning applications in healthcare, biomedicine, and interdisciplinary domains. Her work bridges theoretical statistics with practical challenges in fields like neuroimaging, wound care, and precision medicine. Key contributions include developing predictive tools for pressure injury management and advancing methods for analyzing large-scale biomedical datasets. Education: PhD in Statistics, Stanford University Professional Recognition: Elected Fellow, American Statistical Association (ASA) Elected Fellow, Institute of Mathematical Statistics (IMS) President, Caucus for Women in Statistics (CWS) Key Projects: Development of SCIPUD+, a clinical decision support system for pressure injury care Leadership in PV module degradation analytics through statistical pathway modeling Advancement of subsampling algorithms for feature selection in high-dimensional data Her interdisciplinary collaborations span oncology, environmental science, neuroscience, and energy systems, supported by grants from NSF, NIH, DOE, and others. Dr. Sun advocates for statistical rigor in translating big data into actionable insights for clinical and policy applications.

• Artificial Intelligence
• Healthcare Informatics
• Data Science
• +۵ مورد دیگر

Wajahat Ali Khan is an Associate Professor in Artificial Intelligence at the University of Derby's College of Science and Engineering. His research focuses on AI-driven solutions for healthcare informatics, cybersecurity, and data integration. He leads interdisciplinary projects involving knowledge graphs, semantic web technologies, and clinical decision support systems. Research interests include applying machine learning to healthcare challenges such as disease subtyping, health data interoperability, and personalized medicine. He also explores cybersecurity in network systems and SDN environments. Key contributions include platforms like the Ubiquitous Health Profile (UHPr) for health data interoperability and the Intelligent Medical Platform for dialogue-based healthcare services. His publications span topics from anti-DDoS models to sentiment analysis for depression detection. Collaborations with institutions like Sungkyunkwan University (South Korea) highlight global impact. Khan’s work emphasizes bridging semantic gaps in healthcare systems through adaptive mediation frameworks and data-driven knowledge acquisition methods.

Vijay Mehrotraمشاهده پروفایل

استاد

• Business Analytics
• Customer Success Management
• Call Center Operations
• +۴ مورد دیگر

Dr. Vijay Mehrotra is a Professor of Business Analytics at the University of San Francisco's School of Management. He leads the MBA Customer Success Management program, the first of its kind globally, and directs the MBA Business Analytics curriculum. His prior decade in Silicon Valley included roles as an analytics consultant, entrepreneur, and executive. He contributes regularly to Analytics magazine through his column 'Analyze This!' and advises tech startups. Education: PhD in Management Science & Engineering from Stanford University (1992), MS in Operations Research (1989), and BA in Mathematics, Economics, and Statistics from St. Olaf College (1986). Appointments: Director of Customer Success Management Initiatives; Academic Director of the MBA for Executives Program. His research focuses on customer success management , digital transformation , and service operations . He explores topics like B2B relationships, call center optimization, and data-driven decision frameworks. Recent articles highlight trends in AI-driven business strategies and B2B customer health metrics. His awards include the 2024 Outstanding Graduate Teaching Award and recognition as a Global Top 100 Customer Success Thought Leader (2023). He has advised over 20 startups and contributed to corporate consulting projects on technology adoption.

Vladimir Grupcevمشاهده پروفایل

دانشیار

• Computer Science
• Mathematics
• Data Analysis
• +۱ مورد دیگر

Vladimir Grupcev is Associate Professor of Instruction in Mathematics & Statistics at USF's College of Arts and Sciences. Holding a PhD in Computer Science from USF, his research bridges mathematics, algorithms, and big data analysis. He develops computational methods for molecular simulation and spatial data processing. He teaches courses across multiple institutions including Intermediate Algebra, Business Calculus, and Analysis of Algorithms. His technical expertise spans programming languages (C/C++), mathematical software (Maple/Mathematica), and educational platforms (MyMathLab, Blackboard).

• Digital Health
• Artificial Intelligence
• Generative AI (GenAI)
• +۸ مورد دیگر

Associate Professor Georg Grossmann is affiliated with the School of IT and Mathematical Sciences at the University of South Australia (UniSA), within the Advanced Computing Research Centre. He holds roles as the Research Degree Coordinator for Maths & Stats and Systems Engineering at UniSA STEM, and co-directs the Digital Health Innovation and Clinical Informatics (DHICI) Lab. His research focuses on Digital Health, Artificial Intelligence (AI), Industry 4.0, and interoperability solutions for complex systems. He is also a member of the AI & Software Engineering Lab in the Industrial AI Research Centre, addressing challenges in data integration and business process modeling. Research Interests: Georg's work spans process and data interoperability, AI-driven systems, generative AI (GenAI), and digital transformation. He explores applications in healthcare (e.g., clinical decision support systems), industrial IoT (IIoT), and cultural heritage management. His methodologies include multi-level modeling, knowledge graphs, and semantic frameworks to enhance system interoperability and decision-making. Labs & Collaborations: He leads the DHICI Lab and collaborates with institutions like MIMOSA, Practera, and BAE Systems. His projects include frameworks for predictive maintenance in Industry 4.0, adaptive clinical decision systems, and NLP-based artifact management in museums. He has secured grants from the South Australian Premier’s Research and Industry Fund and the Australian Government’s Department of Industry. Teaching & Supervision: As a Research Degree Supervisor, he guides students in areas like enterprise modeling, software engineering, and AI applications. He also contributes to courses on Business Process Management and Software & Data Modeling.

Saptarshi Debroyمشاهده پروفایل

دانشیار

• Computer Networking
• Network Security
• Big Data Networking
• +۹ مورد دیگر

Saptarshi Debroy is an Associate Professor of Computer Science at Hunter College and a member of the Doctoral Faculties at The Graduate Center, CUNY. He leads the Distributed Systems and Security (DiSSect) Lab and co-leads the CoSSMO Lab, focusing on resilient distributed systems, edge computing, and cyber security. His research addresses challenges in disaster response systems, federated cloud workflows, and moving target defense mechanisms. He holds a PhD in Computer Engineering from the University of Central Florida and has held roles including Post-Doctoral Fellow at the University of Missouri. Education: PhD (Computer Engineering, UCF, 2014), MTech (Distributed & Mobile Computing, Jadavpur University, 2008), BTech (Information Technology, West Bengal University of Technology, 2006) Research Interests His work spans distributed systems, edge/AI-driven networks, cyber security, and resource optimization in disaster scenarios. Key areas include fog computing frameworks for real-time video processing (EFFECT), secure federated workflows (ADON), and MTD-based cloud defense strategies. He emphasizes practical applications like disaster response and healthcare data security. Grants & Awards Recipient of NSF CAREER Award (2020), NSF grants totaling over $1.1M, and Google Research Award. Notable projects include a trusted framework for health incident response (NSF), volunteer edge-cloud resource allocation (NSF), and DDoS mitigation strategies (NSF). Teaching & Service Teaches graduate courses on distributed systems, cloud computing, and networks at CUNY. Serves on NSF review panels and as chair for IEEE/ACM conferences. Leads initiatives like the Cyber Security Summer School for Women to promote diversity in tech. Labs & Collaborations Directs the DiSSect Lab, which develops edge-native systems for disaster response and secure AI. Collaborates with FDNY, perfSONAR, and NSF-funded testbeds like PAWR. Partnerships include projects with bioinformatics and high-performance computing communities (CyVerse, XSEDE).

Polyvios Pratikakisمشاهده پروفایل

دانشیار

• Parallel Programming
• Distributed Systems
• Programming Languages
• +۲ مورد دیگر

Polyvios Pratikakis is Associate Professor in the Computer Science Department at University of Crete and Visiting Researcher at FORTH-ICS. Research develops tools for parallel/distributed software execution, focusing on programming languages, runtimes, and static analysis for modern hardware. Current projects include EuroEXA (programming models for exascale applications) and ETAK (earthquake simulation deployment in cloud environments). Past projects include ASAP (big data workflows), Myrmics/BDDT/PARTEE (task-parallel runtimes), and GreenVM (JVM for non-cache-coherent architectures). Additional research examines software fault tolerance and static analysis for parallel programs. Teaching includes undergraduate/graduate courses on Parallel Programming, Type Systems, Multicore Programming, and Computer Science fundamentals. Supervises multiple MSc/PhD students in compiler design, runtime systems, and social network analytics. Service includes program committees (EuroPar, CF), HiPEAC organization, and faculty committees at University of Crete.

Farokh Bastaniمشاهده پروفایل

استاد

• AI-Based Automated Software Synthesis
• Embedded Real-Time Systems
• Formal Methods and Program Transformation
• +۴ مورد دیگر

Farokh Bastani is the Excellence in Education Chair and Professor of Computer Science at the University of Texas at Dallas (UT Dallas). He serves as Director of the UT Dallas National Science Foundation Net-Centric Software & Systems Industry/University Cooperative Research Center. His academic journey includes roles at the University of Houston (1980–1997) and visiting positions at Michigan State University and the University of California, Berkeley. Bastani holds a Ph.D. in Computer Science from UC Berkeley (1980), an M.S. from the same institution (1978), and a B.Tech. in Electrical Engineering from the Indian Institute of Technology, Bombay (1977). His research focuses on AI-driven software synthesis, embedded real-time systems, formal methods, high-assurance decentralized systems, and tele-collaborative systems. He has led projects on fault-tolerant distributed systems, software reliability, and security assurance. His work emphasizes modular parallel programming and telecommunication system design. Bastani’s publications span topics like P2P data grids, robotic swarm systems, and real-time anomaly detection. He has received multiple IEEE awards, including the Meritorious Service Certificate (2001) and Golden Core Award (1996). He holds editorial roles in journals like the IEEE Transactions on Knowledge and Data Engineering and Wiley’s Encyclopedia of Computer Science. He has directed significant grants, including the $207,250 High-Assurance NCCS project (DoD, 2007–2008) and NSF-funded initiatives. His lab, the Embedded Software Center, develops resilient systems for hostile environments. Collaborations with industry partners like Boeing and Lockheed Martin underscore his applied research impact.

• Cybersecurity
• Machine Learning
• Data Analytics
• +۷ مورد دیگر

Dr Zhiyuan (Thomas) Tan is an Associate Professor in the School of Computing, Engineering and the Built Environment at Edinburgh Napier University (ENU). His research focuses on Cybersecurity, Machine Learning, and Network Security with applications in IoT, Edge Computing, and Intelligent Transportation Systems . He has supervised 11 PhD students over 10 years, with 6 completing their studies successfully. Education: BEng (2005) from Northeastern University (China), MEng (2008) from Beijing University of Technology, PhD (2014) from University of Technology Sydney. Research Interests include: Cybersecurity and Machine Learning for Malware Detection Adversarial Machine Learning in Network Security Trust Evaluation in Vehicular Networks Secure Data Architectures for Critical Systems Touch-based Biometric Authentication Hardware Security and Federated Learning Recent Research Trends involve: Advancements in Federated Learning and Machine Unlearning Privacy-preserving IoT and Edge Computing Adversarial Techniques in Malware Analysis Trust Models for Cyber-physical Systems Scientific Awards National Research Award 2017 (Oman) Three Best Paper Awards Kaspersky Lab Finalist Award Stanford Top 2% Scientist (2021-2023) Honourable Mention in SICSA Supervisor of the Year 2019 Grants from organizations including Royal Society (£12,000) , Scottish Informatics Alliance , CSIRO , and ENU Development Trust (£29,703) . He actively recruits self-motivated PhD students for research in Adversarial Machine Learning , Virtualization Security , and Machine Learning Security .

Jin Wangمشاهده پروفایل

استاد

• Climate Change
• Biogas Valorization
• Methane Capture
• +۳ مورد دیگر

Jin Wang is the Walt and Virginia Woltosz Professor of Chemical Engineering at Auburn University’s College of Engineering. His research focuses on biogas valorization, methane capture from air, smart manufacturing, and big data analytics. He leads projects funded by the Department of Energy and USDA, including waste-to-value conversion systems and algae-based protein production for aquafeed. Wang has pioneered methanotroph-cyanobacteria coculture platforms for biofuel production and wastewater treatment. His work integrates systems engineering principles with data science, advancing both computational modeling and industrial applications. Education: Ph.D. Chemical Engineering from University of Texas and Tsinghua University, B.S. Chemical Engineering from Tsinghua University. Research highlights include a $2.5M DOE grant for converting carbon emissions into aquafeed, and an Alabama grant for bioplastic production from agricultural waste. He co-authored studies on microbial metabolic interactions and developed novel statistical process monitoring tools for smart manufacturing. Recognition includes Auburn’s highest research award (2022) and distinction as Auburn’s first Senior Member of the National Academy of Inventors. His lab explores cutting-edge technologies at the intersection of environmental sustainability and advanced manufacturing.

• Software Engineering
• IT Security
• Cloud Systems Engineering
• +۳ مورد دیگر

Diomidis Spinellis is a Professor at the Department of Management Science and Technology, Athens University of Economics and Business. He is a leading researcher in software engineering, IT security, and cloud systems engineering, with over 300 publications and 10,000 citations. He has authored award-winning books including Code Reading , Code Quality: The Open Source Perspective , and Effective Debugging: 66 Specific Ways to Debug Software and Systems (2016). As a Senior Member of ACM and IEEE, he served as Editor-in-Chief of IEEE Software (2015–2018) and contributed to open-source tools like CScout, UMLGraph, and dgsh. Award-winning author in software engineering Developer of critical open-source tools Editorial leadership in IEEE Software Contributor to macOS and BSD Unix His research spans code quality, software evolution, security, and developer productivity. Articles highlight Unix modernization, AI-assisted coding, dependency analysis, and incident management. He has served on the IEEE Computer Society Board of Governors and holds degrees from Imperial College London (MEng, PhD). Scientific contributions include open-source datasets (e.g., VulinOSS, Alexandria3k) and innovative tools for software analysis. His work bridges academic research and industrial practice, with case studies on Eclipse, Android APIs, and ING’s incident management.

Guiling Wangمشاهده پروفایل

استاد

• Machine Learning
• Blockchain Technology
• Deep Learning
• +۹ مورد دیگر

Dr. Guiling Wang is a Distinguished Professor of Computer Science and Associate Dean of Research and External Relations at New Jersey Institute of Technology (NJIT). She holds a Ph.D. in Computer Science and Engineering from The Pennsylvania State University (2006) and a B.S. in Software Engineering from Nankai University, China (2002). Her research focuses on machine learning, blockchain technology, deep learning, and intelligent transportation systems. Dr. Wang’s work spans interdisciplinary areas such as: Machine Learning and Reinforcement Learning Blockchain-based systems and decentralized applications Intelligent traffic signal control and autonomous systems Data privacy and cybersecurity Generative adversarial networks (GANs) and vision-language models Her recent research emphasizes practical solutions for: Optimizing traffic management through multi-agent reinforcement learning Developing robust watermarking techniques for digital security Applying LLMs for financial decision-making and portfolio management Designing blockchain frameworks for vehicular networks and edge computing Notable contributions include: Proposing novel architectures like MCFN for high-performance watermarking Advancing RAGIC for risk-aware stock interval construction Developing PairUpLight for multi-intersection traffic coordination Pioneering blockchain-based systems iBCTrans and VDKMS for vehicular networks Dr. Wang’s research is supported by grants from federal agencies and industry collaborators, with applications in smart cities, financial technology, and healthcare systems.

Vassil Vassilevمشاهده پروفایل

استاد

• Artificial Intelligence
• Cyber Security
• Machine Learning
• +۶ مورد دیگر

Prof. Vassil Vassilev is a Professor of AI and Intelligent Systems and Head of the Cyber Security Research Centre at London Metropolitan University. His work spans artificial intelligence, cyber security, and data integration with a focus on applications in urban systems, malware analysis, and cyber-physical systems. He leads initiatives in secure transaction risk assessment (CyDRA) and smart city technologies. Research interests include reinforcement learning for cyber incident response, AI policy validation frameworks, and adaptive security systems. He explores hybrid AI models, IoT-based environmental monitoring, and semantic frameworks for vulnerability detection. His work bridges theoretical AI advancements with practical implementations in cyber defense, urban data spaces, and financial security. Grants and funding support his projects on cyber security analytics, threat intelligence, and low-cost data platforms. He collaborates on initiatives like the first urban data space in Bulgaria and innovative authentication techniques using audio steganography. His leadership at the Cyber Security Research Centre drives applied research in both academic and enterprise contexts.

Nicholas Nagleمشاهده پروفایل

استاد

• Spatial Statistics
• Spatial Data Science
• Demography
• +۴ مورد دیگر

Nicholas Nagle is a Professor and Program Director of the NSF Human Networks and Data Science Program at the University of Tennessee's Department of Geography. He specializes in spatial statistics, spatial data science, and demography. His research focuses on improving population survey methodologies, particularly with the U.S. Census Bureau and USDA, and integrates multi-source data like surveys and imagery. Currently on leave until August 2026, he advises on the redesign of the 2020 Decennial Census through the National Academy of Sciences. His work spans climate change demography, forest inventory estimation, and health disparities analysis. Education: Ph.D., University of California, Santa Barbara. Teaching focuses on quantitative methods and population geography. Research interests emphasize spatial data fusion, uncertainty visualization, and policy applications. Recent projects include UrbanPop (spatial microsimulation), RegRake (forest data mapping), and near-real-time pandemic monitoring. His interdisciplinary approach bridges demography, environmental science, and public health. Grants include NSF-funded work on Human Networks and Data Science. Collaborations involve federal agencies and international development projects in Mali and Florida.

Abu Barkat Ullahمشاهده پروفایل

پژوهشگر

• Cyber Security
• Data Analytics
• Decision Analytics
• +۳ مورد دیگر

Dr Abu Barkat Ullah is affiliated with the University of Canberra, where he conducts research in cybersecurity and related fields. He holds a PhD in Computer Science from the University of New South Wales (UNSW) Australia (2009). Previously, he served as Head of the Department of Cyber Security and Games at Canberra Institute of Technology (CIT), where he established the Threat Simulation Operations Centre (TSOC) for cyber training, which won the 2019 ACT Industry Collaboration Award. His research focuses on cybersecurity threats, data analytics, decision analytics, and evolutionary optimization. Notable contributions include studies on ransomware’s impact on national security, phishing strategies leveraging persuasion principles, and cybersecurity challenges in global mining infrastructure. He has led projects funded by organizations like AustCyber and Fifth Domain, emphasizing industry collaboration. Awarded the CIT Board Award for Leadership and Business Growth, Dr Ullah also contributes to academic governance through roles in CIT’s Academic Council and Corporate Resources Committee. His work bridges technical cybersecurity solutions with human-centric factors, emphasizing interdisciplinary approaches to address evolving threats.