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Louiqa RaschidView profile

Professor

• Database Systems
• Data Integration
• Data Mining
• +8 more

Louiqa Raschid is a Professor at the University of Maryland, holding appointments in the Robert H. Smith School of Business, the Institute for Advanced Computer Studies (UMIACS), and the Department of Computer Science. Her research bridges computer science and business information systems, focusing on data integration, management, and mining in non-traditional domains. Education: B.Tech (IIT Madras, 1980), PhD (University of Florida, 1987) Research Interests include: Data integration and mining across life sciences, health sciences, and financial ecosystems Humanitarian IT solutions for disaster management Semantic query optimization and data delivery techniques Grid and wide-area data management Article Trends reflect interdisciplinary efforts combining bioinformatics, database systems, and social behavior modeling. Key themes include ontology-driven data analysis, network-aware query optimization, and disaster relief systems development. Scientific Awards include: ACM Distinguished Member (2016) ACM Fellow (2016) IEEE Fellow (2000) DILS 2008 Best Paper Award Grants from NSF and DARPA have funded her work on biological data integration and financial cyberinfrastructure. She co-directs the Computational Linguistics and Information Processing (CLIP) Lab and collaborates with institutions worldwide.

Matthew TraxlerView profile

Professor

• Psycholinguistics
• Cognitive Neuroscience
• Language Comprehension
• +7 more

Matthew Traxler is a Distinguished Professor in the Department of Psychology at the University of California, Davis, and an affiliated faculty member of the UC Davis Center for Mind and Brain. His research focuses on unconscious processes in language comprehension, particularly syntactic parsing and semantic processing. Current NIH-sponsored work explores connections between working memory and syntactic parsing Former editorial roles include editorship of Language and Linguistics Compass and associate editorship of Quarterly Journal of Experimental Psychology Research Trends: Recent publications emphasize bilingual language processing, cognitive aging, syntactic priming, and electrophysiological correlates of language comprehension. Key methodologies include eye-tracking, ERP analysis, and multilevel modeling of individual differences. Scientific Awards & Roles: NIH-sponsored investigator Editorial Board Member - Journal of Memory and Language Consulting Editor - Journal of Experimental Psychology: Learning, Memory, and Cognition

• Programming Languages
• Compiler Technology
• Reversible Computation
• +5 more

Torben Ægidius Mogensen is an Associate Professor at the Department of Computer Science, University of Copenhagen, where he leads research in the Programming Languages and Theory of Computation section. His office is located at Universitetsparken 5, Copenhagen. His primary research focuses on: Automatic program analysis and transformation (especially partial evaluation and semi-inversion) Compiler technology for functional languages Domain-specific language design Reversible computing systems and languages Algorithms, complexity theory, and automata theory Applications in graphics and fractal generation His recent publications demonstrate a strong focus on reversible computation systems, including specialized programming languages like Hermes for encryption, reversible processor architectures, and functional programming extensions. His textbook publications on compiler design (2024) and programming language implementation (2022) indicate significant contributions to computer science education and foundational knowledge. He teaches courses on compilers, programming language technology, and game development, and maintains active research collaborations internationally. He is fluent in Danish and English, with working knowledge of German and Romanian.

Cynthia L FisherView profile

Professor

• Language Acquisition
• Cognitive Development
• Child Language Development
• +3 more

Cynthia L Fisher is a Professor in the Department of Psychology at the University of Illinois. She serves as Associate Head of the Psychology Department and holds a joint appointment in Linguistics. Her research focuses on children’s language acquisition, particularly how they learn verb meanings, syntactic structures, and phonological patterns from speech addressed to infants and young children. She received her Ph.D. from the University of Pennsylvania. Her work bridges developmental psychology, linguistics, and computational modeling to understand the cognitive mechanisms underlying early language development. Key research themes include syntactic bootstrapping, phonotactic learning, and the interaction between syntax and semantics. Her lab investigates how infants and toddlers use structural cues in language to build mental representations of events and words. Recent studies explore the generalization of phonotactic rules, the role of prosody in sentence comprehension, and the application of AI models (e.g., BabyBERTa) to child-directed language. Her publications span experimental studies with young children and computational models, addressing topics like verb learning, syntactic priming, and physical reasoning in artificial intelligence. Collaborations with researchers like Rochel Baillargeon and Greg Marcus highlight interdisciplinary approaches to cognitive development. No awards are explicitly mentioned, but her extensive body of work reflects sustained contributions to developmental linguistics. Advising and grants are not detailed in the provided text, though her lab’s activities imply active mentorship of students. Her research is centered in the Department of Psychology at Urbana-Champaign, with a focus on understanding foundational aspects of how children acquire language through auditory and contextual cues.

• Computer Science
• Programming Languages
• Software Engineering
• +3 more

Xinyu Wang is a Research Fellow at the University of Michigan's Department of Physics, affiliated with the School of Literature, Science, and the Arts (LSA). Their primary office is located in the Randall Laboratory, and they are also associated with the Homer A. Neal Lab. Wang's work focuses on advancing program synthesis techniques, web automation systems, and data-driven methodologies to enhance software development and user interaction. Their research addresses challenges in SQL query verification, cloud computing simplification, and integrating human feedback into automated processes. While specific educational background details are not provided in the text, Wang's research demonstrates expertise in computer science, programming languages, and software engineering. Their projects include developing tools like VeriEQL for SQL equivalence verification, Miwa for user-controlled web automation, and SlabCity for query optimization. These efforts highlight a trend toward creating systems that blend formal methods with practical usability. Key Research Themes: Program synthesis, compiler design, database systems, human-computer interaction, neurosymbolic AI, and automated workflows Wang’s contributions include innovations in data structure refinement, cloudless computing architectures, and tensor transformation tools. Their work often emphasizes reliability, user confidence, and scalable solutions. No formal advisees or grants are explicitly listed in the provided texts. However, their involvement in advising resources like 'Advising Career Resources' suggests a role in supporting academic and professional development within the department. Wang collaborates with labs and teams focused on physics and computational sciences, contributing to interdisciplinary projects. Their contact information includes the email wongxy@umich.edu and office phone numbers 734-764-4437 and 734-763-9694.

Andreas ZellerView profile

Professor

• Software Testing
• Automated Debugging
• Fuzzing
• +5 more

Andreas Zeller is a Professor at Saarland University and leads the Software Analysis and Testing Group at CISPA Helmholtz Center for Information Security. His research focuses on automated software testing, debugging, and security, with a strong emphasis on fuzzing techniques. He holds an ERC Advanced Grant for his 'Semantics of Software Systems' (S3) project, which explores massive test generation and oracle mechanisms. Zeller is renowned for his open-access books The Fuzzing Book and The Debugging Book , which provide interactive tools for learning and applying testing and debugging methods. His work includes developing the Fandango fuzzer, which combines grammars, constraints, and evolutionary algorithms for effective test generation. Zeller advises a group of over ten PhD students and collaborates internationally on cutting-edge research. In 2025, he received the ACM SIGSOFT Influential Educator Award for contributions to automated software engineering education. His research also extends to start-ups like InputLab GmbH, focused on synthesizing test data for enterprise applications. Recent projects include GDBMiner for input grammar extraction and Information Flow Fuzzing for detecting security leaks. Zeller actively participates in conferences like ICSE, FSE, and AST, delivering keynotes and organizing sessions on the future of software engineering.

• 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)

Ivan GavranView profile

Researcher

• Formal Verification
• Reinforcement Learning
• Multi-Robot Systems
• +3 more

Ivan Gavran is a Researcher at the Max Planck Institute for Software Systems (MPI-SWS), focusing on foundational and applied aspects of computer science. His primary research interests include formal verification, reinforcement learning, multi-robot systems, and cyber-physical systems. He explores the intersection of formal methods with machine learning and robotics, aiming to create robust, provably correct systems. His work emphasizes practical applications such as smart contract verification, human-robot collaboration, and distributed task planning. He has developed tools like Lassie for interactive theorem proving and Antlab for multi-robot task coordination. Gavran’s contributions bridge theoretical computer science with real-world systems, addressing challenges in security, reliability, and scalability. While no formal awards are listed in the provided text, his publications reflect significant engagement with leading conferences in formal methods and robotics. His research often involves collaborative projects, leveraging MPI-SWS’s interdisciplinary environment to tackle complex problems in distributed systems and artificial intelligence.

Alpay DORUKView profile

Lecturer

• Information Security
• Cryptology
• Embedded Systems
• +5 more

Alpay DORUK is a Lecturer and the Head of the Cyber Security Department at the Faculty of Engineering and Natural Sciences, Bandirma Onyedi Eylul University. Previously, he served as a Lecturer at Tekirdag Namik Kemal University (2011–2020) and a Research Assistant at Izmir Institute of High Technology (1999–2011). His expertise spans Information Security, IoT, and Embedded Systems, with a focus on ontology engineering, machine learning applications, and sensor networks. Research highlights include developing ontology-based frameworks for IoT sensors and web services, designing wheelchair control systems using image processing, and analyzing superconductor properties via SEM image statistics. He has supervised over a dozen academic projects and one Master’s thesis on facial movement tracking using image processing. Active in academic administration, he coordinated Erasmus and Farabi programs and led departmental initiatives as Department Head. His refereeing roles include peer review for journals like Turkish Journal of Electrical Engineering and conferences such as ICECENG. He has authored/co-authored two books on cybersecurity and computer engineering, and contributed to international projects like the Sayısal Kontrol Sistemleri software development (2006–2010). Recent work emphasizes IoT device monitoring, blockchain-inspired data structures, and machine learning for automotive efficiency analysis. His teaching spans operating systems, software engineering, and agile development, reflecting his blend of theoretical and applied expertise.

Sonia ChernovaView profile

Associate Professor

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +4 more

Sonia Chernova is an Associate Professor in the School of Interactive Computing at Georgia Tech's College of Computing. She leads the Robot Autonomy and Interactive Learning (RAIL) lab, focusing on developing intelligent and interactive autonomous systems. Her research spans robotics and AI, emphasizing semantic reasoning, human-robot interaction, and explainable AI. She directs the NSF AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups (AI-CARING), which develops AI systems to support aging adults in home environments. Research Interests: Chernova’s work integrates human-centric approaches to robotics, including adaptive autonomy, explainable AI, and AI for health. She explores how robots can learn from human feedback, navigate ambiguous tasks, and provide proactive assistance in daily environments. Her lab’s projects emphasize real-world applications in healthcare, smart homes, and collaborative human-robot teams. Key Contributions: Developed frameworks for preference adaptation in object rearrangement and human-robot collaboration Pioneered explainable AI techniques for robot failures and decision-making transparency Advanced semantic reasoning methods for robots operating in everyday environments Led initiatives in proactive assistive robotics and aging-in-place technologies Awards & Recognition: 2021 IEEE/ACM HRI Best Paper Award 2018 NAE Frontiers of Engineering Top 100 Researcher 2014 ONR Young Investigator Award 2012 NSF CAREER Award Teaching & Outreach: Teaches courses on robotics, human-robot interaction, and robotics research. Co-chaired the Conference on Robot Learning (CoRL 2023) and developed outreach programs to bridge pre-college computer science education gaps. Affiliations: GVU Center, Institute for Robotics and Intelligent Machines (IRIM), and the NSF AI-CARING Institute.

Paola MerloView profile

Associate Professor

• Computational Linguistics
• Machine Learning
• Linguistics
• +7 more

Paola Merlo is an Associate Professor at the University of Geneva, leading the Computational Learning and Computational Linguistics (CLCL) research group. Her work integrates linguistic modeling with machine learning, focusing on statistical language properties, lexical semantics, and syntactic/semantic parsing. She co-developed the Quantitative Computational Syntax framework and serves as Deputy Director (Geneva) for the NCCR Evolving Language center, investigating language evolution through computational methods. Education: Studied theoretical linguistics at the University of Venice and earned a PhD in Computational Linguistics from the University of Maryland, USA. She held visiting positions at the University of Pennsylvania (Institute for Cognitive Science), University of Edinburgh (School of Informatics), Stanford University, and Uppsala University, where she currently holds an adjunct professorship. Professional Service: Past editor of Computational Linguistics (MIT Press), member of ACL executive committees, and chair of major conferences (EMNLP 2011, EACL 2021). Served on the ERC panel for 'The Mind and its Complexity' (2020). Research Grants: Received an SNSF Advanced Grant (2021) for interdisciplinary work on linguistic intelligence. Her research emphasizes computational approaches to language universals and automatic generalization across languages. Dissemination: Active in science communication, including talks at the Collège de France and a video for the NCCR Women campaign celebrating Swiss women's suffrage anniversary (2021).

Shen Heng TaoView profile

Academic

• Artificial Intelligence
• Multimedia Computing
• Computer Vision
• +3 more

Shen Heng Tao is a Distinguished Professor and Dean of the School of Computer Science and Engineering at the University of Electronic Science and Technology of China (UESTC). He is also the Executive Dean of the AI Research Institute and Chief Scientist of Vision Intelligence at the Peng Cheng Laboratory. His academic journey includes a BSc (First Class Honours) and PhD from the National University of Singapore (2000 and 2004), followed by roles at the University of Queensland, where he became a Professor in 2011. His research focuses on artificial intelligence, multimedia computing, and computer vision, with notable contributions to cross-media intelligent analysis and real-time video retrieval systems. He has published over 400 peer-reviewed papers, including 160+ IEEE/ACM Transactions, and holds an H-index of 78. His work has been recognized with awards such as the IEEE Fellow, ACM Fellow, OSA Fellow, and Clarivate Highly Cited Researcher. He has led 15 major research grants, including projects from the Ministry of Science and Technology of China and National Natural Science Foundation. His service includes roles as Associate Editor for journals like ACM Transactions of Data Science and IEEE Transactions on Multimedia, and conference chairs like ACM Multimedia 2021. His lab, the Center for Future Media, explores advanced topics like multimodal learning, trustworthy AI, and human-robot interaction. Current research emphasizes cross-modal reasoning and real-world applications in metaverse, autonomous systems, and smart cities.

• Prosody and Syntax Acquisition
• Speech Perception
• Cochlear Implant Outcomes
• +4 more

Kara Hawthorne is an Associate Professor in the Department of Hearing, Speech, and Language Sciences at Gallaudet University's Human Services and Sciences school. Her work focuses on prosody-syntactic interactions, speech perception in cochlear implant users, and language processing in neurodiverse populations. She teaches graduate courses including Research Methodology, Speech Science, and Dissertation Seminars. Research interests include prosody's role in syntax acquisition, clinical practices for speech-language pathologists, and linguistic challenges faced by individuals with intellectual and developmental disabilities. Her grants include studies on cochlear implant outcomes, early intervention strategies, and accent adaptation in speech perception. Hawthorne has advised 11 doctoral students and serves on committees for Gallaudet’s PhD program and institutional review boards. She has published over 20 peer-reviewed articles, with recent work exploring prosody meta-analyses and intervention methods for children with language delays. Current research emphasizes clinical applications of prosody research and accessibility in communication technologies.

• Psycholinguistics
• Bilingualism
• Cognitive Control
• +3 more

Jared Novick is a Professor in the Department of Hearing and Speech Sciences at the University of Maryland. His work focuses on the cognitive and neural mechanisms underlying real-time language comprehension, particularly how domain-general systems like attention interact with language-specific processes. He co-directs the department’s honors program and serves as Director of Undergraduate Studies, emphasizing inclusive education and curriculum development. Novick holds a PhD (2003) and AM (2000) in Cognitive Psychology from the University of Pennsylvania, and a BA (1997) in Brain and Cognitive Sciences from the University of Rochester. His research employs eye-tracking, EEG, and fMRI to study bilingualism, cognitive control, and neural oscillations in language processing. Recent findings include how code-switching enhances bilingual attention and memory, and the role of theta-band oscillations in cognitive control during language tasks. He has advised over 9 graduate and postdoctoral researchers, and contributes to the Maryland Language Science Center and Program in Neuroscience & Cognitive Science. Teaching includes courses on psycholinguistics (HESP300), scientific literacy (HESP214), and professional development (HESP468H). His edited volume Cognitive and Working Memory Training (Oxford, 2019) synthesizes interdisciplinary perspectives on executive function.

Yang HuView profile

Assistant Professor

• Autonomous Systems
• Cybersecurity
• Cloud Computing
• +3 more

Dr. Yang Hu is an Assistant Professor of Electrical Engineering at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. His research focuses on autonomous systems, cybersecurity, and cloud computing, with a particular emphasis on rethinking autonomous driving infrastructure through multi-system networking. He has received an NSF CAREER Award for a project aiming to redesign autonomous driving systems using advanced computing and communication technologies, benefiting AR/VR and industrial IoT applications. Dr. Hu’s work bridges semantic gaps in virtual machine introspection and explores dynamic binary instrumentation frameworks like PEMU. His publications span cybersecurity, embedded systems, and graph processing optimizations. The NSF-funded project ($508,339) highlights his leadership in transforming autonomous systems through networked multi-object architectures. His research achievements include contributions to guest OS fingerprinting in cloud environments and efficient graph processing algorithms. Collaborations involve hypervisor-layer automation tools like HyperShell and hybrid techniques for semantic gap reduction.