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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 .

Y. Richard YangView profile

Professor

• Computer Networks
• Wireless Networking
• Mobile Computing
• +2 more

Y. Richard Yang is a Professor of Computer Science and Electrical Engineering at Yale University, where he leads research in computer networks, wireless systems, and distributed computing. He is a core member of Yale's Computer Systems Lab and has pioneered Internet standards like ALTO (RFCs 7285/9439/9569). His work on massive MIMO (Argos) laid foundations for 5G cellular networks. Education: Ph.D. in Computer Science, University of Texas at Austin (2001) M.S. in Computer Science, University of Texas at Austin (1998) B.E. in Computer Science, Tsinghua University (1993) Research Interests: Yang's work spans network architecture (ALTO/P4P), wireless innovations (beamforming, superposition coding), and network verification (Flash, Trident). His recent focus includes deep application-network integration and scalable data plane verification for cloud/CERN-scale systems. Publication Trends: Recent articles emphasize SDN programmability (Maple, Trident), Internet-scale optimization (ALTO extensions), and high-speed verification (Flash). His works consistently bridge theory (game-theoretic models) with practical deployment (RFCs, CERN integration). Awards: ACM SIGMobile Test of Time Award (2022) ACM SIGCOMM NAI Best Paper Award (2022) NSF CAREER Award Facebook/Google/Microsoft Faculty Research Awards Students & Funding: Advised recent graduates including Jackie Dong and Lily Zhou. Secured grants from U.S. NSF, Army, U.K. MoD, Facebook, Google, and Microsoft. Labs: Directs projects in the Computer Systems Lab at Yale , collaborating with CERN, Microsoft Research, and Tsinghua/Peking Universities.

Chulwoo PackView profile

Assistant Professor

• Document AI
• Computer Vision
• Deep Learning
• +6 more

Chulwoo Pack is an Assistant Professor in the McComish Department of Electrical Engineering and Computer Science at South Dakota State University. His research focuses on Document AI, Computer Vision, and Deep Learning, with applications in historical document analysis, semantic segmentation, and explainable AI. He holds a Ph.D. in Computer Science from the University of Nebraska-Lincoln (2023), an M.S. (2017), and B.S. (2015) in Computer Science from South Dakota State University. Key research areas include parameter-efficient fine-tuning, weakly-supervised learning, and adaptive image processing techniques for large document images. His work bridges computer science and digital humanities, addressing challenges in archival description, historical document restoration, and cultural heritage preservation. Notable collaborations include projects with the Library of Congress on digitization and data analytics. Professional roles include membership in the ACM, participation in the Graduate Program Development Committee, and contributions to the Faculty Search Committee. His technical expertise spans software engineering, robotic navigation simulators, and intelligent tutoring systems for API misuse correction. The Pack Research Site provides further details on ongoing projects and publications.

Martin RobillardView profile

Professor

• Software Engineering
• Information Privacy
• Human-Computer Interaction
• +4 more

Martin Robillard is a Professor at McGill University's School of Computer Science, where he leads the McGill Software Technology Lab. He holds a Ph.D. from the University of British Columbia. His research focuses on software engineering, emphasizing human aspects of development, including documentation design, test suite quality, and information privacy. He has authored the textbook Introduction to Software Design with Java and developed the JetUML tool, recognized with the 2024 ACM SIGSOFT Influential Educator Award. He has co-chaired major conferences (FSE 2012, ICSE 2017) and is a Distinguished Member of the ACM. Research Interests: His work bridges software engineering, AI, and HCI, addressing challenges in API usability, automated documentation generation, and privacy-preserving software design. Recent projects include dynamic documentation tools like Casdoc and studies on developer documentation formats. Professional Activities: He serves on editorial boards for IEEE TSE and Empirical Software Engineering, and chairs workshops like DySDoc. His contributions include over 100 publications, six SIGSOFT Distinguished Paper Awards, and leadership in software engineering education. Teaching: Teaches courses on software design (COMP 303), information privacy (COMP 555), and software architecture. His courses emphasize practical skills and ethical considerations in software development. Labs & Collaborations: The McGill Software Technology Lab investigates knowledge discovery in software systems, with projects on API documentation, test quality, and privacy in health contexts. Collaborators include industry partners like ActiveEon and General Motors.

Christian GerthView profile

Professor

• Business Informatics
• Software Engineering
• Model-Based Software Development
• +3 more

Prof. Dr. Christian Gerth is a Professor of Business Informatics and Software Engineering at Osnabrück University of Applied Sciences, affiliated with the Faculty of Economics and Social Sciences. His expertise spans model-based software development, business process management, and adaptive systems. He holds a PhD in Natural Sciences from the University of Paderborn and a Diplom-Informatiker degree. Educational background: Dr. rer. nat. (2012, University of Paderborn), Diplom-Informatiker & B.Sc. (2007, University of Paderborn), Bankkaufmann apprenticeship (2002, Commerzbank AG). Research interests focus on software engineering methodologies, business process modeling, model-driven engineering, and cross-device systems. He has contributed to frameworks like CrossEcore and XDAI-A, addressing challenges in process model versioning, blockchain applications in energy markets, and adaptive service composition. Teaching includes courses on databases, object-oriented programming, project management, and software engineering for business students. He actively participates in academic committees for conferences like BPM and CVSM, and reviews for journals such as Software and Systems Modeling and IEEE Transactions on Software Engineering. Key contributions include patents on process model merging and conflict resolution, and research on service-oriented architectures and On-The-Fly computing. His work bridges academic research with practical software solutions for industry challenges.

Michele MelchioriView profile

Associate Professor

• Information Systems
• Semantic Web Technologies
• Blockchain Integration
• +7 more

Michele Melchiori is an associate professor at the Università degli Studi di Brescia (Italy) since 1998, specializing in systems for information processing. He holds a PhD in Information Engineering from the University of Brescia and a Master's in Computer Science from the University of Milan. His research focuses on information systems design, semantic-based services, blockchain integration, and smart city technologies. Notable contributions include frameworks for smart contract design, blockchain applications in agri-food supply chains, and IoT-driven solutions for construction quality assurance. His work bridges theoretical advancements with practical implementations, spanning projects funded by collaborative initiatives. Key areas include personalized data exploration using semantic web technologies, trust management in decentralized systems, and healthcare applications like food recommendation systems. He has authored over 80 publications, emphasizing interdisciplinary approaches to data management challenges. Melchiori frequently contributes to academic events such as the Italian Symposium on Advanced Database Systems. His research bridges technical innovations (e.g., blockchain) with societal needs (e.g., smart city infrastructure and post-pandemic healthcare models).

• Computer Science
• Database Systems
• Business Process Management
• +5 more

Jianwen Su is a Professor at the University of California, Santa Barbara, USA, with a distinguished career spanning over three decades in Computer Science , particularly in Database Systems , Business Process Management , and Web Services . Their research bridges theoretical foundations with practical applications, focusing on data-centric process modeling , formal verification , and spatio-temporal data analysis . Key contributions include the design of artifact-centric workflow models , temporal constraint languages , and query systems for uncertain data . Recent work integrates machine learning with proteomic analysis for stress biomarker discovery and LLM-based extraction of structured data from clinical reports. Notable scientific recognition includes the 2019 ACM PODS Alberto O. Mendelzon Test-of-Time Award . Collaborations span institutions globally, with frequent co-authorship in journals like Information Systems , ACM Transactions on Management Information Systems , and conferences such as BIBM and TIME .

• Computational Linguistics
• Natural Language Processing
• Machine Translation
• +7 more

Jan Hajič is a Professor at Charles University in Prague , where he serves as Deputy Director of the Institute of Formal and Applied Linguistics. Since 2016, he holds an Adjunct Professor position at the University of Colorado Boulder. His leadership extends to directing the LINDAT/CLARIN infrastructure, a key part of the EU Clarin network, and chairing the META-NET executive board. PhD in Computational Linguistics from Charles University (1995) Over 180 publications and a book on computational morphology Principal Investigator for major NSF, EU, and Czech grants His research focuses on computational linguistics , natural language processing , machine translation , and semantic annotation . He pioneered the Uniform Meaning Representation (UMR) project and contributed to foundational resources like the Prague Dependency Treebank . His work spans multilingual NLP , language technology infrastructure , and digital language equality initiatives. Recent publications highlight advancements in semantic role labeling , event-type ontologies , and interoperable language technology platforms . He has led projects such as Humane-AI-Net and European Language Grid , emphasizing cross-cultural communication and open science. Scientific Awards: Donatio Prize of Charles University (2022) Silver Medal of Charles University (2020) Silver Medal I of Faculty of Mathematics and Physics (2012) Award of Czech Academy of Sciences for best 'Information Society' project (2009) Co-author of Best Student Paper at EMNLP (2005) Silver Medal of Charles University (2001)

Alessandro ScarsoView profile

Professor

• Organic Chemistry
• Catalysis
• Supramolecular Chemistry
• +4 more

Alessandro Scarso is a Full Professor at the Department of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice. He earned a PhD in Chemical Sciences from the University of Padua and completed postdoctoral research at The Scripps Research Institute (USA) and Ca' Foscari. His expertise spans organic chemistry, catalysis, and supramolecular chemistry, with a focus on sustainable processes and bisphosphonate drug development. Scarso has held leadership roles, including vice-coordinator of the PhD Programme in Chemistry (Ca' Foscari & Trieste) and editorial positions in journals like RSC Advances and Organics . Research interests include micellar catalysis, supramolecular nanocontainers, and enzyme-like catalytic systems. Notable awards include the 2010 Young Scientist Prize and Gian Paolo Chiusoli Medal. He teaches advanced courses in organic chemistry, catalysis, and scientific writing, and has supervised over 20 graduate and 6 PhD students. Scarso's work integrates experimental and computational methods, addressing challenges in green chemistry and drug design. He has secured grants and collaborates internationally on projects like the Cariparo SELECT program. His contributions include over 85 publications, with an H-index of 31, and active peer review roles recognized by Publons. Scarso also leads institutional initiatives, including Ca' Foscari's Harvard Summer School and quality assurance for bio/nano-materials programs.

Renee BryceView profile

Professor

• Software Testing
• Artificial Intelligence
• Mobile Computing
• +3 more

Renee Bryce is a Professor in the Department of Computer Science and Engineering at the University of North Texas, holding the distinction of University Distinguished Teaching Professor. She is affiliated with Discovery Park, a hub for interdisciplinary research. Her research focuses on software testing methodologies, mobile computing, AI-driven systems, and inclusive education practices in technology. Her work spans innovative applications such as IoT-driven drone simulations, context-aware mobile systems, and AI-enhanced bug triaging. She has pioneered reinforcement learning approaches for GUI testing and combinatorial testing strategies. Notable contributions include the Bug Wars competition platform for bug detection education and the development of tools like Caret-HM for Android session analysis. Renee has been recognized with the University Distinguished Teaching Professor award for her impactful educational contributions. Her research emphasizes practical tools for improving software quality and accessibility, including frameworks for sustainable mobile computing and inclusive online learning environments. She has collaborated on projects such as the REU Site: Bug Wars, fostering undergraduate research in software testing. Her ongoing work addresses challenges in user-centric testing, security coding bugs, and the intersection of technology with ecological and social values.

• Artificial Intelligence
• Genetic Algorithms
• Evolutionary Computation
• +9 more

Khaled Rasheed is a Professor at the School of Computing, University of Georgia, where he has served in various academic capacities since 2000. His current appointment as Professor in the Franklin College of Arts & Sciences - Division of Physical & Mathematical Sciences, School of Computing began in August 2017. Previously, he served as Associate Professor (2006-2017) and Assistant Professor (2000-2006) at the same institution. Dr. Rasheed also serves as Graduate Program Faculty in the School of Computing since 2003. Dr. Rasheed earned his Doctor of Philosophy in Computer Science from Rutgers State University of New Jersey in 1998, following a Master of Science in Computer Science from the same institution in 1995. His undergraduate education includes a Bachelor of Science in Computer Science from Alexandria University, Egypt, completed in 1990. Dr. Rasheed's research focuses on Artificial Intelligence, with particular expertise in Genetic Algorithms, Evolutionary Computation, Data Mining, and Machine Learning. His work bridges theoretical AI development with practical applications across diverse domains. His research spans Bioinformatics and Health Informatics, Computational Intelligence, Engineering Design Optimization, and specialized applications in Poultry Science and Agriculture. His interdisciplinary approach has led to significant contributions in applying AI techniques to solve real-world problems in agriculture, healthcare, and engineering. Recent work demonstrates his focus on deep learning applications for animal behavior monitoring, crop yield prediction, and protein structure analysis, showing both technical innovation and practical impact. Dr. Rasheed's scholarly output shows a clear progression from foundational AI research toward domain-specific applications. His recent publications (2023-2025) reveal a strong emphasis on agricultural applications of AI, particularly in poultry science and crop management, while maintaining contributions to core AI methodology development. His work demonstrates consistent citation impact across multiple domains, with particular influence in agricultural technology applications of computer vision and deep learning. Student Career Success Influencer Award 2023 Student Career Success Influencer Award 2022 Outstanding Faculty Service Award Second Best Paper Dr. Rasheed has secured multiple significant research grants, including a current project with COBB-VANTRESS INCORPORATED (2025-2027) for developing tracking systems for poultry, and a major USDA NIFA grant (2022-2028) for forest sustainability research. His funded projects demonstrate his ability to translate theoretical AI research into practical applications with economic and environmental impact. His grant portfolio spans multiple funding agencies including NIH, USDA, and industry partners, reflecting the interdisciplinary nature of his work. Dr. Rasheed maintains an active research laboratory focused on evolutionary computation and machine learning applications. His work often involves interdisciplinary collaborations across computer science, agriculture, biology, and engineering. His recent publications and grants indicate a strong emphasis on applying AI to agricultural challenges, particularly in poultry science and crop management, while maintaining a foundation in core AI methodology development.

• Drug Discovery
• Small Molecule Therapeutics
• Pharmaceutical Development
• +3 more

Stephen Munk is a Professor of Practice and Deputy Director of the Biodesign Institute at Arizona State University. He holds affiliations with the School of Molecular Sciences and has extensive industry experience in drug discovery and manufacturing. Previously served as CEO of Ash Stevens Inc., securing numerous FDA approvals for oncology drugs including Velcade and Vidaza. Elected Senior Member of the National Academy of Inventors (2022). Education: B.S. Chemistry, Arizona State University (1979) Ph.D. Organic Chemistry, UC Berkeley (1985) Postdoctoral Fellow under Dale Boger at Purdue University (1985-1988) Research Interests: Focuses on discovery and development of small molecule therapeutics, particularly anticancer drugs. Expertise in process development for safe synthesis of pharmaceuticals and regulatory compliance. Active in advancing drug discovery efficiency through interdisciplinary approaches. Awards: Senior Member, National Academy of Inventors (2022) Six NIH research contracts secured during Ash Stevens leadership Leadership & Boards: Former Chairman, AACR Chemistry in Cancer Research Working Group (2014) Chairman, MichBio Board of Directors (2009-2014) Member, Henry Ford Community College Biotechnology Advisory Board (2009-2016) Teaching: Teaches special topics courses in biomedicine and chemistry at ASU including BIO 598 and BCH 598.

Christophe HauserView profile

Assistant Professor

• Software Security
• Binary Program Analysis
• Reverse Engineering
• +6 more

Christophe Hauser is an Assistant Professor at Dartmouth College and a member of the Institute for Security, Technology and Society (ISTS). His research focuses on software security, binary program analysis, reverse engineering, and vulnerability discovery across software and hardware systems. He integrates formal methods, machine learning, and program analysis to enhance cybersecurity defenses. Education: Joint PhD from CentraleSupélec (France) and Queensland University of Technology (Australia). Prior roles include Research Lead at USC Information Sciences Institute (USC-ISI) where he founded the Binary Analysis and Systems Security (BASS) group, and postdoctoral researcher at UC Santa Barbara’s Seclab. Research Interests: Binary code and firmware analysis, intrusion detection, usable security, privacy-preserving systems. Notable projects include BinPool (vulnerability dataset), BinHunter (vulnerability localization), and Harm-DoS (DoS mitigation). His work emphasizes practical applications such as automated fuzzing, decompilation analysis, and neuro-symbolic code search systems. He has contributed to open-source tools like angr and developed frameworks for firmware integrity validation (BootKeeper).

• Epidemiology
• Genetic Epidemiology
• Ophthalmology
• +5 more

Robert Luben is a Principal Research Fellow at the Institute of Ophthalmology, University College London, and holds an Honorary Senior Visiting Fellowship at the University of Cambridge. His work integrates genetic epidemiology, machine learning, and ophthalmology to study chronic diseases in aging populations. Current Affiliation: Institute of Ophthalmology, UCL Previous Affiliation: MRC Epidemiology Unit, University of Cambridge Research Focus: Genetic and epidemiological analysis of glaucoma, dementia, and cardiovascular traits Key research areas include: Genetic epidemiology of angle closure glaucoma Data linkage of genomic data with retinal images and hospital statistics Development of AI tools for phenotyping and genetic prediction Study design for prospective cohort research His recent articles highlight trends in: Application of multimodal AI to correlate physiological waveforms with genetic traits Genome-wide association studies for retinal and systemic diseases Using retinal imaging as a biomarker for brain and cardiovascular health Methodological advances in unsupervised representation learning As a computer systems specialist fluent in statistical and programming languages, Luben develops high-performance computing workflows for genomic and clinical data analysis.

Barton P. MillerView profile

Professor

• Binary Code Analysis
• Software Security
• Distributed Systems
• +5 more

Barton P. Miller is a Vilas Distinguished Achievement Professor and the Amar & Balinder Sohi Professor of Computer Sciences at the University of Wisconsin, Madison, where he has made significant contributions to computer science research and education. As a faculty member in the Computer Sciences Department within the College of Engineering, he directs major research initiatives including the Paradyn Tools project and leads cybersecurity efforts as Chief Scientist of the DHS-funded Software Assurance Marketplace (SWAMP) research center. Miller received his B.A. degree from the University of California, San Diego in 1977, and M.S. and Ph.D. degrees in Computer Science from the University of California, Berkeley in 1980 and 1984. His educational background laid the foundation for his pioneering work in software testing and analysis. His research spans multiple critical areas of computer science, with a primary focus on binary code analysis and instrumentation , software security , and distributed and parallel program performance . Miller is particularly renowned for founding the field of Fuzz random software testing in 1988 and dynamic binary code instrumentation in 1992. His work bridges theoretical computer science with practical applications, addressing real-world challenges in high-performance computing systems, cybersecurity, and scalable distributed systems. His research has direct applications in national security through his work with DHS and TrustedCI, the NSF Cybersecurity Center of Excellence. Miller's publications reveal a consistent focus on binary analysis tools, security vulnerability detection, and performance optimization techniques. His recent work shows increasing emphasis on ransomware analysis, GPU performance optimization, and practical security tool development for developers. The trajectory of his research demonstrates how foundational work in binary instrumentation has evolved to address contemporary cybersecurity challenges while maintaining relevance to high-performance computing environments. Among his notable honors, Miller is a Fellow of the ACM and recipient of the prestigious Jean-Claude Laprie Award in Dependable Computing , an R&D 100 Award , and multiple best paper awards including at HPDC 2009 and CCGrid 2018. His contributions to the field have been recognized through distinguished lectureships at institutions including Ben Gurion University and IBM T.J. Watson Research Center. As an educator, Miller has mentored numerous students and taught courses spanning operating systems, software security, and distributed systems. He has received teaching awards and developed educational resources including free and open software security training materials. His work with TrustedCI has focused on cybersecurity for scientific communities, helping researchers secure their computational infrastructure while maintaining research productivity. Miller also co-directs the MIST software vulnerability assessment project in collaboration with colleagues at the Autonomous University of Barcelona. Miller directs the Paradyn Tools project, which investigates program scalability and binary program analysis technologies for use in HPC, systems design, and cyber-security. His work extends to practical applications through collaborations with government agencies including DHS and the U.S. Secret Service Electronic Crimes Task Force. His research group has developed tools like Dyninst, MRNet, and the Wisconsin Safety Analyzer that have become foundational in their respective domains.