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Danijela TešendićView profile

Associate Professor

• Machine Learning
• Computer Vision
• Environmental Monitoring
• +2 more

Danijela Tešendić serves as an Associate Professor in the Department of Mathematics and Informatics at the Faculty of Sciences, University of Novi Sad. Her office is located in the Information Technologies and Systems office (DMI&DF), second floor, room 50, with contact details including telephone (485)-2873 and email tesendic@dmi.uns.ac.rs. She maintains a professional presence through her website at http://www.is.pmf.uns.ac.rs/daca/. Her research demonstrates dual expertise in environmental monitoring systems and library information technology. Recent work (2022-2025) focuses on machine learning applications for airborne pollen classification using CNN architectures and domain adaptation techniques, contributing to standardization frameworks in environmental science. Earlier contributions (2013-2019) established foundational work in library management systems, particularly through the BISIS software platform, business intelligence integration, and mobile accessibility solutions for visually impaired patrons. Analysis of her publication trajectory reveals a strategic shift toward interdisciplinary environmental informatics while maintaining connections to information systems. Her pollen monitoring research bridges computer vision with ecological applications, emphasizing real-time processing and cross-device compatibility. Concurrently, her library science work pioneered cloud-based service models and inclusive design principles, showcasing adaptable technical frameworks across distinct domains. Scientific Awards No awards or honors were documented in the provided materials. Advising and Grants Student mentorship details are absent from the source text. No research grants or funding sources are explicitly referenced.

Mira MeziniView profile

Professor

• Software development paradigms and tools
• Programming systems for reliable distributed software
• Automated software analysis
• +3 more

Mira Mezini is a Professor of Computer Science at the Technical University of Darmstadt, Germany, leading the Software Technology Lab. She serves on steering committees, program committees, and editorial boards of top-tier conferences and journals. Her affiliations include the National Research Center for Applied Cybersecurity ATHENE and co-directorship of hessian.AI, the Hessian Center for Artificial Intelligence. Her research focuses on programming systems for reliable distributed software and AI, automated software analysis, and foundational code models. She has developed large-scale module concepts for adaptability, extensible programming languages, and intelligent software development environments that leverage web-based resources to generate programming rules and patterns. Specializes in software engineering Expert in programming language design Contribution to cybersecurity and AI Her recent work emphasizes static analysis, distributed systems, and programming language design, with trends in API misuse detection, decentralized applications, and secure local-first programming. The focus spans from foundational type systems to practical tools enhancing software quality and developer productivity. Scientific Awards Two-time IBM Eclipse Innovation Award recipient (2005, 2006) Google Research Award (2017) Horst Görtz IT Security Award (2014) ERC Advanced Grant (2012) ACM Fellow Dahl-Nygaard Prize (2025) She has held leadership roles including Dean of Computer Science at TU Darmstadt (2013-2014) and Vice President positions (2014-2019). Her service extends to international juries, funding panels, and editorial boards. Labs & Teams Leads the Software Technology Lab at TU Darmstadt, driving research in programming paradigms and tools. Co-directs hessian.AI and contributes to the Excellence Cluster 'Reasonable Artificial Intelligence.'

Wen-Chin ChenView profile

Professor

• Design and Analysis of Algorithms
• Multimedia Systems
• Quantum Algorithms
• +7 more

Wen-Chin Chen is a Professor at National Taiwan University in the Department of Computer Science and Information Engineering. With a PhD in Computer Science from Brown University (1984), his expertise spans algorithms , multimedia systems , and quantum computing . Previously at GTE Laboratories (1984–1987), he has taught foundational courses such as Algorithms , Mathematical Analysis of Algorithms , and Quantum Algorithms . Education: BS in Mathematics, National Taiwan University (1976) PhD in Computer Science, Brown University (1984) His research integrates design and analysis of algorithms with applications in multimedia synchronization and quantum computing . Publications reflect deep engagement with data structures , combinatorics , and real-time system design , including work on audio-video synchronization models , heap-ordered trees , and genetic algorithm optimization . Recent projects involve quantum algorithms (e.g., Shor's, Grover's) and linear algebra for geometric and matrix operations, indicating ongoing contributions to theoretical computer science and applied mathematics .

Anne-Marie KermarrecView profile

Professor

• Large-scale distributed systems
• Epidemic algorithms
• Peer-to-peer networks
• +4 more

Anne-Marie Kermarrec is a Professor at the École Polytechnique Fédérale de Lausanne (EPFL) since 2020, specializing in large-scale distributed systems, epidemic algorithms, and system support for machine learning. She previously served as CEO of Mediego (2015–2020), a startup providing content personalization services, and held a Research Director role at Inria, France (2004–2015). Her academic affiliations include the School of Computer and Communication Sciences (IC), specifically the Institute of Communication Systems (IINFCOM) and the Scalable and Adaptive Distributed Systems Lab (SACS). She also holds leadership roles in education and governance at EPFL, including Vice-President for Doctoral Education and Continuing Education. Her research focuses on distributed systems, federated learning, privacy-preserving technologies, and scalable machine learning architectures. Notable achievements include an ERC Grant (2008), ERC Proof of Concept Grant (2013), ACM Fellowship (2016), and election to the European Academy (2013). She advises multiple PhD students and has authored influential papers on decentralized learning systems, graph watermarking, and federated learning optimizations. Professional roles include membership in the Global Ethics and Partnerships Committee (GEP) and leadership in the Commission Doctorale (CDOCT). Her work bridges theoretical computer science with practical applications, emphasizing ethical AI and system interoperability.

Godmar BackView profile

Associate Professor

• Computer Systems
• Operating Systems
• Programming Languages
• +5 more

Godmar Back is an Associate Professor in the Department of Computer Science at Virginia Tech's College of Engineering. He holds a Ph.D. in Computer Science from the University of Utah (2002) and specializes in systems research, programming languages, and performance analysis. His work focuses on foundational aspects of operating systems, distributed systems, and cloud computing, with notable contributions to memory management, concurrency, and cybersecurity education. His research explores how hardware and software interact to optimize system performance, including studies on SPEC benchmarking, garbage collection, and undefined behavior in programming languages. He has developed frameworks like CloudBrowser 2.0 for cloud-based applications and the VT-ASOS system for many-core platforms. Back is also active in pedagogy, integrating DevOps practices into undergraduate research and incorporating cybersecurity modules into core curricula through spiral theory-based methods. Key projects include the Pintos instructional operating system kernel, the VirtuOS virtualized OS, and ReplayCache for predictive computations. His work frequently bridges theoretical systems research with practical applications, emphasizing reproducibility and real-world impact. His educational initiatives aim to broaden participation in systems research through high-impact practices and collaborative development environments.

Martin GaedkeView profile

Professor

• Web Engineering
• Knowledge Engineering
• Artificial Intelligence (AI)
• +4 more

Prof. Dr.-Ing. Martin Gaedke is a Full Professor and Dean of the Department of Computer Science at Technische Universität Chemnitz (TU Chemnitz). He leads the research group Distributed and Self-organizing Systems (VSR) and holds roles such as President of the International Society of Web Engineering (ISWE), founder of the International AIQT Foundation, and member of the German Foundation for University Admissions' IT-advisory board. His expertise spans Web Engineering, AI-driven systems, and decentralized technologies. Education: Martin Gaedke earned a Master's degree (1997) and doctoral degree (2000) in Computer Science/Engineering from the University of Karlsruhe (now Karlsruhe Institute of Technology). Research Focus: Gaedke's work advances collaborative systems in hyper-connected societies, emphasizing Web Engineering, knowledge engineering, and AI-supported hypermedia systems. Key areas include chatbot design patterns, decentralized web trust, smart IoT systems, and end-user development tools. His contributions include pioneering work in Web Engineering since the 1990s, notably co-authoring the first Web Engineering paper at WWW6 (1997). Recent Trends in Publications: Recent research highlights dynamic code migration, GenAI-driven UIs, and ethical AI in chatbots. He emphasizes trust in decentralized systems (e.g., Solid-based social networks) and practical applications like autonomous smart home agents (WS3H). Awards: Ranked 39th globally in Knowledge Engineering (2020), honored with the AI 2000 Most Influential Scholars Honorable Mention and listed in the AI 2000 Annual List. His work is cited over 1,800 times in key areas like Web Engineering and IoT. Advising & Outreach: Gaedke has mentored numerous researchers and entrepreneurs through roles as a Certified High Performance Coach and business advisor. His lab, VSR, develops open-source tools like the Web-Based Network Simulator (WNSWE) for education and industry. Labs/Teams: The Distributed and Self-organizing Systems (VSR) group at TU Chemnitz focuses on innovative projects such as the Trusting Decentralized Web Data framework and the GenAI-Driven Multimodal UI Architecture .

Yifan ZhangView profile

Associate Professor

• Mobile Computing
• Operating Systems
• Embedded Systems
• +4 more

Yifan Zhang is an Associate Professor in the Computer Science Department at Binghamton University (SUNY). He joined the School of Computing in 2014 after completing his Ph.D. in Computer Science at the College of William and Mary and a B.S. in Computer Science from Beihang University. Prior to academia, he worked as a system software engineer in industry. Education Bachelor of Science in Computer Science, Beihang University Doctor of Philosophy in Computer Science, College of William and Mary Research Focus Zhang's work centers on mobile computing systems, operating systems, embedded systems, and wireless networks. He explores emerging paradigms like edge/cloud computing, mobile/IoT applications, and distributed machine learning systems. His research emphasizes system design for energy efficiency, resource optimization, and security in mobile and distributed environments. Notable Achievements Recipient of Best Paper Runner-up at ACM/IEEE Symposium on Edge Computing (SEC 2024) Supervised students in projects such as Meunik, EdgeCourier, and StoArranger Academic Contributions Zhang has authored over 20 publications in top-tier conferences/journals including ACM MobiSys, IEEE INFOCOM, and IEEE Transactions on Networking. His work addresses challenges in energy-efficient systems, secure mobile communication, and distributed computing architectures.

Bruce LesterView profile

Professor

• Parallel Computing
• Programming Languages
• Multi-Core Processors
• +3 more

Dr. Bruce Lester is a Professor of Computer Science at Maharishi University of Management (MUM), where he founded the Computer Science Department and served as its Chair for eight years. He holds PhD, MS, and BS degrees from the Massachusetts Institute of Technology (MIT). His research focuses on Parallel Computing and Programming Languages for Multi-Core Processors, with a strong emphasis on compiler optimization and concurrency control. Education: Bachelor of Science, Massachusetts Institute of Technology Master of Science, Massachusetts Institute of Technology Doctor of Philosophy (PhD), Massachusetts Institute of Technology Research Interests: Dr. Lester’s work spans Parallel Computing, Programming Languages, and Multi-Core Processor Optimization. He has developed techniques for lock-free parallel data structures, operator fusion in data-parallel libraries, and compile-time detection of control flow errors in parallel programs. His contributions to the field include foundational research on concurrency debugging and the design of educational tools like Multi-Pascal for teaching parallel programming. Publications Trends: His publications emphasize practical applications of parallel computing, including high-performance algorithms, compiler techniques, and concurrency error detection. Recent work focuses on lock-free systems and data-parallel library optimizations. Awards & Honors: Best Paper Award at the 2011 International Conference of Parallel and Distributed Computing (World Congress on Engineering) Advising & Grants: No formal advisee names are listed in the provided data. His professional experience includes 13 years of teaching and six years as a Senior Software Engineer at Primus Telecommunications, where he developed client/server systems and internet platforms. Labs & Teams: While specific lab affiliations are not detailed, his role as founder of MUM’s Computer Science Department suggests leadership in departmental research initiatives.

Rolf KampView profile

Professor

• Networking
• Computer Science
• Software Engineering
• +4 more

Rolf Kamp is a Professor at Monmouth University's Department of Computer Science and Software Engineering. He serves as the IEEE/ACM Club Advisor and Manager of the CSSE Tutor Center, contributing to student mentorship and academic support. Education: M.S. in Computer Science from New Jersey Institute of Technology Kamp's research interests center on Networking and its intersections with software development. His scholarly work explores Java programming, data structures, and client-server computing, with a focus on real-time web applications and distributed systems. Kamp's publications span foundational topics in software engineering, including Java collections, Swing-based applet design, and COBRA-driven networking solutions. These works reflect his expertise in data management , user interface development , and network-centric architectures . In his academic roles, Kamp oversees the CSSE Tutor Center, facilitates student engagement through club advising, and teaches core courses in computer networks, algorithms, and programming ethics. His patents in network-based service systems highlight his practical contributions to software engineering.

• Digital Preservation
• Web Technologies
• Graph Theory
• +3 more

Charles Cartledge is an Adjunct Instructional Faculty at Old Dominion University's Continuing Education division. He holds a Ph.D. in Computer Science from Old Dominion University (2014). His research focuses on digital preservation strategies, web technologies, and graph theory applications in data archiving. Cartledge has contributed to frameworks for self-preservation of digital objects and analysis of network resilience in graph structures. His work bridges theoretical computer science with practical implementations in distributed systems and high-performance computing environments. No formal advising roles or grants are listed in the provided text.

• Computer Science
• Geographic Information Systems (GIS)
• 3D Terrain Visualization
• +3 more

Dejan D. Rancic is a Professor at the Faculty of Electronics , University of Niš, Department of Electrical Engineering and Computer Science. His academic career spans over two decades, with promotions to Assistant Professor in 2005 and Full Professor in 2015. He earned his PhD (2004), Master's (1997), and BSc (1993) degrees from the same department. Current projects: 3 National, 1 International Reviewer for WSEAS journal series Rančić’s research focuses on Geographic Information Systems (GIS), 3D terrain visualization, and algorithm optimization for large-scale spatial data processing. His work bridges computer science with geospatial engineering, emphasizing parallelism and web-based frameworks. His publications highlight trends in GIS integration (mobile/web), terrain rendering algorithms, and advanced signal processing for meteorological applications. Key subfields include raster map creation, adaptive rendering, and spatial coherency techniques. Contact: Email: dejan.rancic@elfak.ni.ac.rs Address: Aleksandra Medvedeva 4, 18104 Niš Tel: +381 (18) 529-105

Abello Monedero, JamesView profile

Professor

• Graph Mining
• Relational Learning
• Visualization of Massive Data Sets
• +10 more

James Abello Monedero is a Professor in the Computer Science Department at Rutgers University , specializing in algorithms, graph mining, and visualization of massive datasets. He earned a Ph.D. in Computer Science from the University of California, San Diego, and held postdoctoral and academic positions at UC Santa Barbara, Texas A&M University, and Bell Labs. Ph.D. in Computer Science, UC San Diego M.S. in Computer Science, UC Santa Barbara His research interests span external memory algorithms , graph mining , relational learning , and visual analytics for massive datasets. He has pioneered techniques for dynamic weighted multi-digraph analysis, large-scale network visualization, and interdisciplinary applications in epidemiology and cultural analytics. James’s publications focus on scalable graph algorithms, visual metaphors for data exploration, and network decomposition. His work includes foundational contributions to graph sketches , quasi-clique detection , and 3D graph navigation , with applications to telecommunications, web graphs, and homeland security. Scientific awards include the ESA Test of Time Award (2017) , Best Teaching Award at Rutgers (2015) , and Fellow of the Institute of Combinatorics (1993) . He has advised numerous Ph.D. and M.S. students, and his research has been funded by NSF , DHS , and LLNL . James leads the Universal Information Graphs Project at DyDAn (DHS Center) and has developed software systems like MGV and Ask-GraphView for interactive graph analysis. He is an active organizer of conferences and workshops in data mining and visualization.

• E-Commerce Systems
• Database Management
• Information Technology
• +6 more

Prof. Dr. Ilija Hristoski is a faculty member at the Faculty of Economics in Prilep, affiliated with the Department of Business Informatics at Saint Clement of Ohrid University – Bitola. He holds the rank of Professor and has been actively involved in research and teaching since 2006. His academic journey includes a PhD in Technical Sciences (2013) and a Master's in Electrical Engineering (2001). He has led research projects, such as analyzing the impact of the COVID-19 pandemic on small businesses and studying inflation drivers in North Macedonia. Education: PhD in Technical Sciences (2013), Technical Faculty, Saint Clement of Ohrid University, Bitola MSc in Electrical Engineering (2001), Electrotechnical Faculty, Skopje Engineer in Informatics (1992), Military Technical Faculty, Zagreb/Belgrade Research Interests: Ilija's work focuses on e-commerce systems, database management, performance analysis of ICT systems, and macroeconomic determinants. Notable contributions include modeling e-commerce client-server interactions, analyzing road traffic flow using databases, and evaluating business-oriented performance metrics. His research bridges technical and economic domains, addressing issues like competitiveness in the Western Balkans and the impact of ICTs on economic growth. Professional Roles: He has served as Head of the Business Informatics Department (2016–2018), Director of the Scientific Research Center (2014–2016), and a member of the University Self-Evaluation Committee. He has also been a visiting scholar at Linnaeus University (Sweden), University of Udine (Italy), and University of Wolverhampton (UK). Grants & Projects: He led projects on Macedonian tobacco production analysis (2011) and the impact of the pandemic on small businesses (2020). His work often involves interdisciplinary collaboration, combining IT systems with economic and social sciences. Labs/Teams: His research group focuses on database systems, e-commerce frameworks, and performance modeling, contributing to both academic publications and practical solutions for industry challenges.

• Communications
• Networking
• Signal & Image Processing
• +5 more

Mung Chiang is the Roscoe H. George Distinguished Professor of Electrical and Computer Engineering and President of Purdue University . He holds a PhD from Stanford University (2003) in Electrical Engineering, following earlier degrees from the same institution. His research focuses on optimizing networks and systems, including federated learning, edge computing, and 6G technologies. He leads projects on fog networking, smart data pricing, and social learning networks. Key research areas include network optimization , edge AI inference , and cooperative federated learning . Recent work addresses challenges in dynamic client management, hybrid terrestrial-satellite networks, and energy-efficient D2D systems. His publications emphasize practical solutions for heterogeneous environments and wireless network dynamics. Dr. Chiang has contributed to systems like Coded Edge Computing and Model Predictive Control (MPC) frameworks. He explores the interplay between connectivity and machine learning, with applications in autonomous vehicles and IoT. His work spans theoretical advancements and real-world implementations, including protocols for wireless system discovery and control. Current research trends include 6G innovations, resilient cyberphysical systems, and adaptive learning frameworks for dynamic networks.

Adam D. GroceView profile

Professor

• Cryptography
• Theoretical Computer Science
• Database Privacy
• +3 more

Adam D. Groce is a Professor of Computer Science at Reed College , specializing in cryptography, differential privacy, and rational cryptography. He obtained his PhD in Computer Science from the University of Maryland in 2014 under the supervision of Jonathan Katz, after completing bachelor’s degrees in mathematics and political science at MIT . Research Interests Database privacy and differential privacy, with a focus on practical hypothesis testing under privacy constraints. Rational cryptography, exploring the intersection of cryptography and game theory by modeling adversaries as rational actors. General theoretical computer science, especially secure multi-party computation, zero-knowledge proofs, and oblivious RAM. Scientific Awards & Recognition No specific awards listed in the provided text. Teaching & Mentorship Regularly teaches core undergraduate courses: Introduction to Computing (CSCI 121), Algorithms and Data Structures (MATH/CSCI 382), Computability and Complexity (MATH/CSCI 387), and Cryptography (MATH/CSCI 388). Offers advanced topics courses such as Advanced Algorithms and specialized seminars in theoretical computer science. Has advised over a dozen senior theses at Reed, many co-advised and several resulting in peer-reviewed publications. Actively invites Reed undergraduates to join research projects in privacy and cryptography. Contact & Location Office: Library 313, Reed College, 3203 SE Woodstock Blvd, Portland, OR 97202 Phone: 503-517-5155 Email: agroce@reed.edu