جستجوی استاد راهنمای دانشگاهی

• Wireless Communications
• Network Security
• Quality of Experience (QoE)
• +۷ مورد دیگر

Tasos Dagiuklas is a Professor in the Department of Computer Science and Technology within the School of Engineering and Technology at the University of Bedfordshire. With over 168 publications spanning from 1995 to 2025, he has established himself as a leading researcher in telecommunications and network systems. His extensive publication record demonstrates continuous scholarly contribution across multiple decades in the field. Professor Dagiuklas' research focuses on wireless communications, edge computing, 5G/6G networks, quality of experience (QoE), and federated learning . His work bridges theoretical networking concepts with practical applications, particularly in multimedia delivery and security. He has developed significant expertise in video streaming optimization, network security mechanisms, and resource management in emerging network architectures. His research consistently addresses the evolving challenges of modern communication systems, with recent work increasingly focusing on AI integration in networking. Analysis of his recent publications (2023-2025) reveals a strong trend toward edge computing, federated learning, and security applications in next-generation networks. His work demonstrates a strategic shift from traditional networking concerns to more complex systems involving AI integration, energy efficiency, and heterogeneous environments. The publications show consistent collaboration with researchers across multiple institutions, with particularly strong partnerships with Muddesar Iqbal, Ilias Politis, and Stavros Kotsopoulos. Professor Dagiuklas has made substantial contributions to the academic community through his extensive publication record in high-impact venues including IEEE journals and conferences. His work has evolved from foundational networking research to cutting-edge investigations of AI-enhanced communication systems, reflecting the broader trajectory of the field itself. His research demonstrates both technical depth in specific networking challenges and breadth across multiple application domains.

• Cybersecurity
• Blockchain
• Machine Learning
• +۱۲ مورد دیگر

Edgar Weippl is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice Dean and Head of the Research Group Security and Privacy. His work spans cybersecurity, blockchain, and machine learning, with teaching roles in information security and software security courses. Current Positions: Vice Dean (Faculty of Computer Science), Head (Security and Privacy Research Group), Deputy Head (Neuroinformatics & Knowledge Engineering Groups) Research Interests: Cybersecurity, blockchain, IoT security, code obfuscation, privacy technologies, reinforcement learning, and socio-technical systems security Selected Publications: Focus on blockchain privacy, VoWiFi security, code obfuscation, and reinforcement learning applications

Zhiyu Quanمشاهده پروفایل

استادیار

• Actuarial Science
• Data Science
• Computational Statistics
• +۳ مورد دیگر

Zhiyu (Frank) Quan is an Assistant Professor at the University of Illinois at Urbana-Champaign (UIUC), holding positions in the Department of Mathematics, Department of Statistics, and National Center for Supercomputing Applications (NCSA). He is also an affiliate faculty member at Discovery Partners Institute as InsurTech Lead and serves as an ORMI Faculty Fellow in Finance. His research focuses on data science applications in actuarial science, including tree-based models, natural language processing, and deep learning for insurance risk modeling, predictive analytics, and InsurTech innovation. Education: Ph.D. in Actuarial Science (University of Connecticut, 2019), MS in Applied Statistics (Michigan State University, 2014), and BS in Mathematics and Applied Mathematics (Xiamen University, 2012). Research interests include computational statistics, insurance analytics, and leveraging machine learning for actuarial challenges such as claim prediction, rate-making, and cyber risk modeling. He leads the Illinois Risk Lab, bridging academic research with industry needs, and has pioneered hybrid tree-based models to address imbalanced data in insurance. Notable achievements include the Arnold O. Beckman Research Award and Society of Actuaries Research Institute recognition. He advises two doctoral students and teaches advanced predictive analytics courses, emphasizing practical applications in actuarial science and data ethics. Key collaborations involve InsurTech companies and NCSA, focusing on NLP-driven academic paper repositories (CyLit) and federated learning for privacy-preserving insurance data sharing. His work addresses real-world challenges in cyber insurance and automated machine learning systems.

Arnab Nandiمشاهده پروفایل

استاد

• Database Systems
• Human-Computer Interaction
• Human-in-the-Loop Data Analytics
• +۵ مورد دیگر

Arnab Nandi is a Professor of Computer Science and Engineering at The Ohio State University, with a courtesy appointment in Biomedical Informatics. He holds leadership roles including Steering Committee Member for the Human-in-the-Loop Data Analytics (HILDA) Workshop and has served as Workshops co-chair for SIGMOD 2025-26 and Demonstrations co-chair for SIGMOD 2024. His research focuses on bridging human interaction and data infrastructure, spanning database systems, human-in-the-loop data analytics, and next-generation query interfaces. Nandi's work emphasizes interactive data exploration through projects like DICE (Distributed Interactive Cube Exploration), GestureDB (Querying Beyond Keyboards), and Omni (Multimodal Data Exploration). His recent research explores integrating LLMs into database education, augmented reality interfaces for data analytics, and multimodal approaches to video querying. Nandi has received numerous honors including the NSF CAREER Award, Google Faculty Research Award, IEEE TCDE Early Career Award, and the University's Alumni Award for Distinguished Teaching. He was also named to Columbus Business First's '40 under 40' and became an ACM Distinguished Member in 2024. As an educator, he teaches courses including CSE 3241 (Introduction to Database Systems), CSE 5242 (Advanced Database Systems), and CSE 5251 (Introduction to Software Startups). His educational innovations include DBTutor, which integrates LLMs into database systems education. At Ohio State, Nandi co-founded the OHI/O Program, which fosters tech culture through hackathons, and The STEAM Factory, an interdisciplinary research collaboration network. Prior to academia, he was founder and CEO of Mobikit, a connected vehicles data analytics startup acquired by Azuga Inc. (a Bridgestone company). His research has been supported by the NSF and industry partnerships, with applications spanning precision agriculture (CropFusion), clinical data pipelines (ICARUS), and interactive visualization systems (Perceptvis).

Timothy Menziesمشاهده پروفایل

استاد

• Artificial Intelligence
• Software Engineering
• Data Science
• +۵ مورد دیگر

Timothy Menzies is a full Professor in the Department of Computer Science at North Carolina State University's College of Engineering. He serves as the director of the Irrational Research lab (mad scientists r'us) and holds editorial positions as editor-in-chief of the Automated Software Engineering journal and associate editor for IEEE Transactions on Software Engineering. With over 300 publications and more than 24,000 citations, Menzies is a globally recognized leader in software engineering research. Menzies' research focuses on developing computer systems that make optimal decisions with minimal data, specializing in artificial intelligence, intelligent agents, data sciences, analytics, and software engineering. His pioneering work in data-driven, explainable, and minimal AI for software systems has redefined defect prediction, effort estimation, and multi-objective optimization. He is particularly known for his contributions to empirical software engineering, emphasizing transparency and reproducibility. As the co-creator of the PROMISE repository, he helped establish modern empirical software engineering by demonstrating that small, interpretable AI models can outperform larger, more complex ones. Menzies' recent publications reveal several key trends in his research: a growing emphasis on ethical considerations in AI deployment, particularly in sensitive domains like legal systems; continued innovation in software analytics with a focus on hyperparameter optimization tailored specifically for software engineering tasks; exploration of causal relationships in software analytics; and development of techniques that work effectively with limited data, including landscape analysis, surrogate learning, and active learning approaches. Mining Software Repositories Foundational Contribution Award (2017) Carol Miller Graduate Lecturer Award (2016) IBM Faculty Award (2016, 2017) ACM Fellow (2025) ASE Fellow (2024) IEEE Fellow Professor Menzies has advised 24 Ph.D. students throughout his career, with recent completions including Andre Motta (April 2025) and Xueqi Yang (October 2024). His research has secured over $19 million in funding from prestigious agencies including NSF, DARPA, and NASA, as well as industry partners like Meta, Microsoft, and IBM. Current grants focus on improving machine learning model efficiency, adapting empirical software engineering methods to computational science, vulnerability detection, and software analytics at scale using transfer learning across 10,000+ GitHub projects. Menzies has developed innovative approaches to help developers navigate the challenges of AI implementation while maintaining ethical standards and practical effectiveness. As director of the Irrational Research lab, Menzies leads a team focused on creating AI tools that are not only intelligent but also fair, transparent, and trustworthy. The lab's work emphasizes practical applications of AI in software engineering while addressing the human factors involved in developer-AI collaboration. Current projects include developing methods for better fuzzing with L3harris, improving vulnerability detection through smart pruning techniques, and creating AI platforms for workforce empowerment through credential gap diagnostics.

Andreas Rauberمشاهده پروفایل

دانشیار

• Digital Preservation
• Machine Learning
• Data Citation
• +۳ مورد دیگر

Ao.Univ.Prof. Dipl.-Ing. Dr.techn. Andreas Rauber is an Associate Professor at TU Wien's Research Department E-Commerce. His work focuses on digital preservation, machine learning, and reproducible research. He leads projects like EOSC-Life (FAIR principles in life sciences) and PLANETS (long-term data access). Key affiliations include the Network Lab and TU Wien's Institute for Software Technology. His research emphasizes data citation frameworks, secure data infrastructure (OSSDIP), and ethical AI practices. He has advised over 20 PhD/Master’s students in areas like adversarial ML and privacy-preserving systems. Notable contributions include DBRepo (semantic databases) and the DBRepo infrastructure for relational data. He collaborates internationally on initiatives like EOSC support offices and cultural heritage projects linking ethnomusicology datasets.

Sarah Brattمشاهده پروفایل

استادیار

• Scholarly Communication
• Research Data Management
• Science of Science
• +۶ مورد دیگر

Sarah Bratt is an Assistant Professor at the University of Arizona College of Information Science (InfoSci), focusing on Digital Curation & Preservation. Her research explores scholarly communication, research data management, and the science of science, aiming to advance long-term data sustainability and actionable science policy. BS in Philosophy from Ithaca College MS in Library and Information Science with a Data Science certificate from Syracuse University Her work addresses practices, metrics, and infrastructures for data-intensive science, including international collaborations and AI applications in libraries. Recent projects analyze GenBank metadata, dataset co-authorship, and software use in computational biology. She has presented at ASIS&T, 4S, ICSSI, and NetSci conferences. Masters’ prize in Library & Information Science at Syracuse University 2022 Better Scientific Software (BSSw) Fellow honorable mention Bratt collaborates with institutions like UIUC, University of Tennessee, and Metadata Lab @Syracuse University. She co-supervises students with Dr. Cristian Román-Palacios and leads the Metadata Analytics Lab at UA.

John S. Kaddisمشاهده پروفایل

دانشیار

• Type 1 Diabetes
• Systems Biology
• Bioinformatics
• +۵ مورد دیگر

John S. Kaddis, Ph.D. is an Associate Professor in the Department of Diabetes & Cancer Discovery Science within the Arthur Riggs Diabetes & Metabolism Research Institute at City of Hope. With over 15 years of experience at City of Hope, Dr. Kaddis has developed scientific resources for team-based research initiatives focused on type 1 diabetes, creating data systems, analysis tools, and websites used by researchers worldwide. Dr. Kaddis earned his B.S. (Honors) in Biochemistry from California State University Los Angeles, where he completed undergraduate research supported by two National Science Foundation fellowships. He later earned his Ph.D. in Systems Biology and Disease from the University of Southern California. His academic journey includes positions as Assistant Professor since 2015 and Associate Professor since 2022 at City of Hope. Dr. Kaddis's research primarily focuses on the complex mechanisms of type 1 diabetes through systems biology and bioinformatics approaches. His work centers on understanding islet cell biology, beta cell dysfunction, and the immunological aspects of type 1 diabetes. His research has evolved from developing collaborative data resources to conducting cutting-edge investigations into genetic factors in diabetes pathogenesis. He has pioneered the creation of bioinformatics platforms that enable global collaboration in diabetes research. The trends in Dr. Kaddis's publications reveal a progression from foundational work on biobanking and data management toward increasingly sophisticated investigations of genetic and immunological mechanisms in type 1 diabetes. His recent work emphasizes translational applications, including potential therapeutic strategies and predictive models that span diverse ancestral backgrounds. His research bridges basic science with clinical applications through the Human Islet Research Network. Member, American Association for the Advancement of Science (2011-Present) Professional Member, American Diabetes Association (2010-Present) Member, Society of Clinical Research Associates (2003-2012) Lifetime Member, Tri-Beta Honor Society (2000-Present) Dr. Kaddis serves as principal investigator and co-investigator on multiple NIH and JDRF-funded projects, including the Human Islet Research Network Bioinformatics Center and the JDRF nPOD DataShare initiative. His work has established critical infrastructure for collaborative diabetes research, enabling researchers worldwide to access and analyze complex datasets. His laboratory has developed specialized data management systems that facilitate the sharing of islet cell research data across international boundaries while maintaining appropriate security and privacy protections. Dr. Kaddis's athletic pursuits in marathons and triathlons mirror his research approach—requiring stamina and perseverance to achieve long-term goals in diabetes research.

Prashant Shenoyمشاهده پروفایل

استاد

• Distributed Systems
• Networking
• Cloud Computing
• +۷ مورد دیگر

Prashant Shenoy is a Distinguished Professor and Associate Dean in the College of Information and Computer Sciences at the University of Massachusetts Amherst. He has been on the faculty since 1998 and heads the Laboratory for Advanced Systems Software while directing the Center for Smart and Connected Society. His research focuses on systems issues for distributed systems ranging from large server clusters to networks of small sensors. Shenoy received his PhD in Computer Science from the University of Texas at Austin in 1998, following an MS from the same institution in 1994. He earned his BTech in Computer Science and Engineering from the Indian Institute of Technology, Bombay in 1993. His academic progression at UMass Amherst has been from Assistant Professor (1998-2004) to Associate Professor (2004-2009) to Professor (2009-2020) to Distinguished Professor (2020-present). His primary research interests include distributed systems, networking, cloud and edge computing, mobile computing and Internet of Things, and energy and sustainability. Over the past decade, his work has increasingly focused on computational decarbonization, as evidenced by his recent $12 million NSF Expedition award in this area. His research group maintains several important resources including the UMass Trace Repository, UMass CS Weather Station, BenchLab, and Smart* Dataset. Shenoy's publications reflect a progression from foundational distributed systems work to increasingly sustainability-focused research. His recent work centers on carbon-aware computing, energy optimization, and computational decarbonization across various computing domains including cloud, edge, and IoT systems. ACM Fellow (2019) AAAS Fellow (2018) IEEE Fellow (2013) ACM Sigmetrics Test of Time Award (2016) NSF Career Award recipient Conti Research Fellowship recipient Lilly Foundation Teaching Fellow As an educator, Shenoy has consistently taught Distributed and Operating Systems (Compsci 677) and has mentored numerous PhD students who have received awards and gone on to successful careers. He serves as the founding Chair of the ACM Special Interest Group on Energy (SIGEnergy) and has organized numerous conferences including serving as PC chairs for the ACM Symposium on Edge Computing in 2025. His research has secured significant funding, including a recent $12 million NSF Expedition in Computational Decarbonization awarded in May 2024. Shenoy leads the Laboratory for Advanced Systems Software at UMass Amherst and directs the Center for Smart and Connected Society. He serves on editorial boards of several journals including ACM Transactions on IOT (TIOT), ACM Modeling and Performance Evaluation of Computing Systems (TOMPECS), and ACM Transactions on the Web (TWEB).

Cristiana SAPPAمشاهده پروفایل

استاد

• Intellectual Property Law
• Cultural Heritage Law
• Data Protection
• +۴ مورد دیگر

Professor Cristiana SAPPA is a Full Professor at IÉSEG School of Management, specializing in Intellectual Property Law and Open Data policies. She holds PhDs in Private Law from Università degli Studi di Pavia, Italy, and Université Paris Sud, France. As Head of the Innovation and Entrepreneurship Track, she focuses on legal frameworks governing cultural heritage, digital single market regulations, and data protection. Her research bridges intellectual property with emerging technologies like augmented reality and the Internet of Things. Key publications address copyright challenges in cultural digitization and legal strategies for public sector information reuse. She has received the 2018 Best Thesis Award at the International Summer School of Cyber Law. Teaching includes intellectual property law and business law courses, emphasizing legal tools for innovation. Education: PhD in Private Law, Università degli Studi di Pavia, Italy (2009) PhD in Private Law, Université Paris Sud, France (2009) Professional Experience: 2012–2014: Professor, ESCP Europe, Paris 2010–2012: Post-doc researcher, University degli Studi, Torino Key Research Areas: Cultural Heritage Law DSM Directive Compliance Open Data Governance Trademark Strategies in Fashion Awards: Best Thesis, International Summer School of Cyber Law (2018)

• Digital Archiving
• Conventional Archiving
• Digital Preservation
• +۳ مورد دیگر

Christian Keitel is an Honorary Professor for Archival Science and Digital Archiving at the University of Applied Sciences Potsdam. He works at the Landesarchiv Baden-Württemberg, where he has served since 2000, currently as Deputy Head of Department 2 (Specialized Programs and Educational Work). His research focuses on conceptual principles of conventional and digital archiving, DIMAG systems, certification of digital archives, authenticity of digital records, and cooperative learning processes in digital archiving. University of Applied Sciences Potsdam – Honorary Professor (2015–) Landesarchiv Baden-Württemberg – Deputy Head of Department (2011–), Senior Archivist (2000–) Keitel’s scholarly work emphasizes digital preservation, metadata standards, and long-term archive certification. His publications address challenges in trustworthiness of digital repositories, significant properties of electronic records, and collaborative digital archiving frameworks. He co-authored DIN standards 31644 and 31645 for trustworthy digital archives. Recent articles highlight his contributions to digital ingest workflows, metadata extraction, and municipal archive solutions. His work explores intersections between traditional archival principles and modern digital challenges, including authenticity verification, system development, and cross-institutional cooperation.

• Research Data Management
• Data Governance
• Data Sharing Practices
• +۳ مورد دیگر

Chris Wiley serves as the Physical Sciences and Engineering Research and Data Services Librarian and Associate Professor at the University of Illinois at Urbana-Champaign. Based at the Grainger Engineering Library, he focuses on data management, research practices, and digital accessibility across scientific disciplines. Research Interests: Specializing in data governance and stewardship across engineering and physical sciences Advancing FAIR data principles and open repository systems Developing accessible data visualization tools Researching data privacy frameworks for scientific contexts Exploring cloud storage limitations for academic institutions Creating educational resources for data management transitions Contact: Email: cawiley@illinois.edu Phone: 217-300-5801 Location: Grainger Engineering Library, 1301 W. Springfield Ave., Urbana, IL 61801

• Research Data Management
• Semantic Web Technologies
• Machine Learning
• +۳ مورد دیگر

Tomasz Miksa is a researcher affiliated with TU Wien's Department of Research Data Management, focusing on machine-actionable data management plans (maDMPs), semantic web technologies, and data reproducibility. He collaborates extensively on projects involving automated assessment of data management workflows, FAIR data implementation, and privacy-preserving analysis platforms. Primary affiliation: TU Wien Department: Research Data Management Key projects: WellFort, FAIR Data Austria, openEO API His research integrates semantic technologies with data governance to enhance reproducibility in scientific workflows, particularly in domains like environmental monitoring and legal informatics. Recent publications emphasize ontological frameworks (DCSO), API harmonization, and auditable machine learning systems. Notable collaborative works include: Reproducibility standards for soil moisture data Knowledge graph applications in cyber-physical energy systems Dynamic data citation mechanisms He supervises students in theses related to maDMP integration, data citation frameworks, and institutional research data planning architectures.

Domhnall Carlinمشاهده پروفایل

پژوهشگر ارشد

• Cybersecurity
• Malware Analysis
• IoT Security
• +۴ مورد دیگر

Domhnall Carlin is an EPSRC Research Software Engineering Fellow (2020) at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science. His fellowship focuses on establishing Research Software Engineering (RSE) as a career pathway within academia while developing software-based security mitigations for IoT devices through interdisciplinary collaboration with University College London. Dr. Carlin completed his PhD in 2018 with the thesis "Dynamic analyses of malware," supervised by Prof. Sakir Sezer and Dr. Philip O'Kane. His doctoral research pioneered dynamic opcode analysis techniques for malware detection, forming the foundation for his current work in cybersecurity. His research spans Cybersecurity with dual specializations in Malware Analysis (focusing on dynamic opcode/system call analysis and AI-driven detection) and IoT Security (addressing threats in connected devices and tech-abuse scenarios). He simultaneously advances Research Software Engineering through policy development, repository analysis, and promoting software sustainability in academic research. Recent publications (2023-2025) reveal three converging trends: 1) Machine learning applications for IoT malware detection using lightweight runtime analysis, 2) Development of benchmark datasets for vulnerability research, and 3) Systematic studies of research software ecosystems across global academic repositories. His work bridges theoretical cybersecurity with practical software engineering solutions. Key scientific recognition includes: EPSRC Research Software Engineer Fellowships 2020 (awarded 2021) Best Paper Award (2025 IEEE Computing and Communication Workshop) Joint Best Paper Award (2018) Emily Sarah Montgomery Travel Scholarship (2017) Postgraduate School Scholarship (2017) Dr. Carlin actively mentors PhD candidates Adrianne Thompson (investigating IoT tech-abuse in intimate partner violence) and Carl Fitzpatrick (developing IoT threat mitigations). His primary research funding comes from the EPSRC Fellowship, which supports both his IoT security research and institutional RSE capacity-building. He maintains active collaborations with University College London on vulnerable population security projects and contributes to ACM and ReSA policy initiatives. Through his EPSRC Fellowship, Dr. Carlin is establishing Queen's first dedicated Research Software Engineering group, creating infrastructure to support software-intensive research across disciplines. His team develops open tools for malware analysis (including dynamic opcode tracing frameworks) and collaborates with cybersecurity researchers on real-world IoT threat mitigation, particularly focusing on protections for vulnerable societal groups.

Kalikinkar Mandalمشاهده پروفایل

دانشیار

• Cryptography
• Cybersecurity
• Privacy
• +۷ مورد دیگر

Dr. Kalikinkar Mandal is an Associate Professor in the Faculty of Computer Science at the University of New Brunswick (UNB), Fredericton, Canada. He holds the prestigious NB Power Cybersecurity Research Chair for smart grid security and privacy, a position supported by $500,000 in funding from NB Power for a five-year term. Dr. Mandal is also a member of the Canadian Institute for Cybersecurity (CIC), an ACM member, and a member of the International Association for Cryptologic Research (IACR). Education: PhD in Electrical and Computer Engineering from the University of Waterloo (2013) MTech in Computer Science from the Indian Statistical Institute, Kolkata (2009) Additional Master's degree in Mathematics Dr. Mandal's research broadly focuses on cryptography, cybersecurity, and privacy, with specific expertise in lightweight cryptography, privacy-preserving computation, security and privacy in smart grids and Internet of Things (IoT), trusted computing, and high-speed cryptography. His work addresses critical challenges in securing emerging technologies, particularly in energy infrastructure where cybersecurity threats can have severe consequences for essential services. His research bridges theoretical cryptography with practical applications in real-world systems. Analysis of Dr. Mandal's recent publications reveals a consistent focus on cryptographic techniques for resource-constrained environments, particularly for smart grid and IoT applications. His work spans theoretical foundations of cryptographic primitives, practical implementations of lightweight ciphers, and innovative privacy-preserving protocols for emerging technologies. A notable trend in his research is the development of efficient cryptographic solutions that balance security requirements with performance constraints in critical infrastructure systems. Scientific Awards: NB Power Cybersecurity Research Chair ($500,000 funding) Contributor to multiple cryptographic algorithms (ACE, SPIX, SpoC, WAGE) that reached Round 2 of NIST Lightweight Cryptography standardization Dr. Mandal actively mentors graduate students in cybersecurity research, currently supervising three students working on cryptographic protocols for cyber-physical systems, cybersecurity in advanced metering infrastructure, and privacy for electric vehicles. His NB Power Cybersecurity Research Chair supports research that provides training opportunities for both graduate and undergraduate students, preparing them as future cybersecurity leaders. Through direct applied research, knowledge dissemination, and student training, his work addresses critical challenges in power and security infrastructure. Dr. Mandal is actively involved in several research initiatives related to lightweight cryptography. He is part of the development teams for ACE, SPIX, SpoC, and WAGE - all of which were Round 2 candidates in the NIST Lightweight Cryptography standardization project. His GitHub repository (comsec-lwc) contains reference and optimized implementations of these cryptographic algorithms. He also contributes to the Canadian Institute for Cybersecurity at UNB, focusing on practical applications of cryptographic techniques in critical infrastructure security.