جست‌وجوی استاد و پژوهشگر

Jocelyne Ventre-Domineyمشاهده پروفایل

پژوهشگر

• Neuroscience
• Cognitive Science
• Neurolinguistics
• +۳ مورد دیگر

Jocelyne Ventre-Dominey is a Senior Researcher at INSERM, affiliated with the University of Burgundy's Faculty of Sports Sciences (UFR Staps). Her primary research focuses on embodied cognition, neurocognitive mechanisms of language and perception, and motor control systems. She is part of the INSERM U1093 Laboratory, collaborating extensively with Prof. Philippe F. Dominey and other international researchers. Her work bridges robotics and neuroscience, investigating how visuo-tactile feedback impacts telepresence embodiment, and explores neural systems underlying sentence-picture comprehension across languages. She has contributed to understanding the role of dopamine vs. STN stimulation in Parkinson's disease and the structural-functional connectivity of semantic systems. Recent studies also address human-robot interaction acceptability and parallel neural processes in motor sequence execution. Publications span journals like Scientific Reports, NeuroImage, and Frontiers in Human Neuroscience, reflecting her multidisciplinary approach. Her research integrates EEG/ERP, neuroimaging, and behavioral experiments to dissect cognitive and neural processes in embodied systems and language. Based in Dijon, France, she maintains ties with the University of Burgundy's sports sciences faculty while engaging in international collaborations. No specific grants or awards are listed, though her active publication record indicates sustained research engagement.

Agnieszka Lijewskaمشاهده پروفایل

استادیار

• Psycholinguistics
• Second Language Acquisition
• Third Language Acquisition
• +۷ مورد دیگر

Agnieszka Lijewska is an Assistant Professor at the Faculty of English, Adam Mickiewicz University in Poznań, Poland. Her research focuses on psycholinguistics, bilingualism, multilingualism, and eye-tracking methodologies in language processing. She has led national research projects funded by the National Science Centre and has collaborated on interdisciplinary studies involving cognitive science and applied linguistics. Ph.D. in English, Poznań, 2007 M.A. in English, Poznań, 2003 Her research interests center on second and third language acquisition , multilingual lexical representation , and eye movement analysis during reading and language comprehension. She has extensively used eye-tracking to study cross-language activation, cognitive load, and reading behavior in bilingual and multilingual populations. Her work bridges theoretical psycholinguistics with experimental methods, contributing to models of the mental lexicon. Recent publications highlight trends in translation priming , cognate facilitation , and respeaking , often in collaboration with experts in interpreting and audiovisual translation. Her articles reflect a strong focus on empirical data, cognitive processing, and the application of advanced statistical methods such as Linear Mixed Models. Awardee of the Rector's research merit award in 2019 , she has also served as a peer reviewer for leading journals including Applied Psycholinguistics , International Journal of Multilingualism , and Second Language Research . She has advised on research methodology, taught TEFL and psycholinguistics, and participated in multiple international research visits at Lund University, McGill University, and Universität Potsdam. She has organized workshops on eye-tracking in language research and has contributed to academic discourse through numerous conference presentations across Europe and North America. Laboratory work and collaborative projects, particularly those involving eye-tracking and cognitive load measurement , form a core part of her research team's activities. She is actively involved in training researchers in advanced statistical methods and experimental design.

Cécile De Catمشاهده پروفایل

استاد

• Language Acquisition
• Bilingualism
• Pragmatics
• +۱۲ مورد دیگر

Professor Cécile De Cat is a leading academic in the field of linguistics at the University of Leeds , where she holds the position of Professor of Linguistics in the School of Languages, Cultures and Societies within the Faculty of Arts, Humanities and Cultures . She has been a key figure in interdisciplinary language research, notably serving as the former director of Language@Leeds and currently as the Speech and Language lead at the Centre for Applied Education Research in Bradford. From 2019 to 2024, she was an adjunct professor at the Arctic University of Norway, reflecting her international influence. Her research spans a wide range of topics in language acquisition, bilingualism, and pragmatics. Key areas include: Individual differences in language development and maintenance Quantification of bilingual experience (via the Q-BEx tool) Assessment of pragmatic and syntactic competence in children and adolescents Cross-linguistic influences in advanced L2 speakers Information structure and discourse competence Application of advanced statistical and data science methods (especially using R) Her recent publications reveal a strong trend toward interdisciplinary, policy-relevant research, particularly in educational and justice contexts. Projects like Q-BEx and Justice to Youth Language Needs demonstrate a commitment to translating linguistic research into practical tools for educators, clinicians, and policymakers. Her work increasingly integrates causal inference, psychometrics, and citizen science methodologies. She has secured funding from major bodies including the ESRC, AHRC, Leverhulme Trust, and COST. Her leadership in large-scale, cross-national projects underscores her role as a central figure in contemporary applied linguistics. Professional Memberships: Editorial Board, Journal of Child Language Editorial Board, Studies in Bilingualism (SiBil) series (Benjamins) Member, International Association for the Study of Child Language (IASCL) Member, Linguistics Association of Great Britain (LAGB) She actively supervises PhD students and welcomes interdisciplinary collaborations. Her advising spans experimental syntax, heritage language acquisition, and bilingual cognitive development. She has led numerous funded research initiatives and fosters partnerships across academia, education, and public policy sectors. She is also involved in innovative teaching, particularly in data science applications for linguistics. She leads or participates in several research groups including Language Acquisition , Multilingualism , Formal Linguistics , and Language at Leeds , contributing to a vibrant research ecosystem.

Christian Winklerمشاهده پروفایل

مدرس ارشد

• Computational Linguistics
• Natural Language Processing
• Requirements Engineering
• +۷ مورد دیگر

Christian Winkler is a Senior Lecturer at the Institute for Romance Studies and the Institute for Applied Informatics at the University of Klagenfurt (Alpen-Adria-Universität Klagenfurt). He has been actively involved in interdisciplinary research and teaching since 1994, bridging the fields of linguistics and computer science. His academic affiliations include the Faculty of Cultural Sciences (KUWI) and the Faculty of Technical Sciences (TEWI), where he contributes to programs in Romance studies, Anglistics, and computer linguistics. Education: Studied Romanistics, Anglistics, and Linguistics at the University of Klagenfurt. Languages: Fluent in English, Italian, French, Spanish, and Portuguese. Winkler's research is centered on the intersection of natural language and information systems. His primary interests include computational linguistics, natural language processing (NLP), requirements engineering, syntactic theory (especially infinitive constructions in European languages), and the application of linguistic principles to software engineering. He has made significant contributions to the development of linguistic tools for conceptual modeling and text analysis, particularly through the long-running NIBA (Natürlichsprachliche Informationsbedarfsanalyse) project. The 15 most recent publications reflect a strong trend in applying linguistic analysis to software and information systems. Key themes include natural language-based requirements engineering, text summarization, semantic tagging, ontology integration, and enterprise search optimization. These works are predominantly published in the ICSSEA and NLDB conference series, indicating a sustained focus on the practical application of linguistics in computing contexts. Subfields span AI-driven text evaluation, verb phrase similarity, collaborative knowledge repositories, and mobile instructional applications. Scientific Awards: No awards or fellowships are mentioned in the provided text. Christian Winkler has played a significant role in academic advising and research collaboration, particularly through his long-term involvement in major research projects. The NIBA project, ongoing since 1995 and funded by the Klaus Tschira Stiftung and the Austrian National Bank, represents a major collaborative effort in linguistically based requirements engineering. He has also contributed to numerous grants and initiatives in natural language processing and software engineering. While no formal advisees are listed, his co-authorship with students and researchers suggests mentoring and collaborative supervision. Labs and Research Teams: NIBA Project Team: Core member since 1995, focusing on natural language analysis for information systems. ICSSEA Conference Series: Regular participant and contributor, indicating integration into a broader European research network in software and systems engineering. Natural Language and Information Systems (NLIS) Community: Active in program committees, showing leadership in the academic community.

Adrian Sampsonمشاهده پروفایل

دانشیار

• computer architecture
• programming languages
• compilers
• +۴ مورد دیگر

Adrian Sampson is an Associate Professor in the Department of Computer Science at Cornell University's Bowers College of Computing and Information Science. He leads the Capra research group, focusing on breaking down abstraction barriers and rethinking the hardware-software interface. Prior to his current position, he served as an Assistant Professor at Cornell University from 2016 to 2022 and completed his Ph.D. at the University of Washington in 2015 under advisors Luis Ceze and Dan Grossman. His research spans computer architecture, programming languages, and compilers, with a notable focus on approximate computing—the concept that computers can be more efficient if allowed to make controlled mistakes. Sampson has made significant contributions to hardware acceleration, FPGA programming, and type systems for heterogeneous computing. His work bridges the gap between software abstractions and hardware realities, particularly in the realm of accelerator design languages. The publications reveal a consistent trajectory in hardware-software co-design, with recent work focusing on predictable accelerator design, timeline types for hardware description, and geometry types for graphics programming. His research group has produced influential work on tools like Dahlia, a programming language that uses type systems to restrict high-level synthesis programs to subsets with predictable semantics and performance. Cornell Bowers CIS Ann S. Bowers Research Excellence Award (2024) Cornell Bowers CIS Computer Science Faculty of the Year (2024) Distinguished Artifact Awards (ASPLOS 2023, 2024) IEEE TCCA Young Computer Architect Award (2021) NSF CAREER award (2019) Google Faculty Research Award (2016) Sampson has advised numerous Ph.D. students whose dissertations cover topics like geometry types for graphics programming, lightweight formal methods, and compiler-driven autovectorization. His research has been supported by prestigious organizations including NSF, Google, and Microsoft Research. He serves on numerous program committees and has held leadership roles in the computer architecture and programming languages communities, including serving on the ACM SIGARCH Board of Directors.

Jacob Andreasمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Jacob Andreas is an Associate Professor of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), affiliated with the MIT-IBM Watson AI Lab and the School of Engineering. His research focuses on advancing artificial intelligence, machine learning, and natural language processing, with particular emphasis on neurosymbolic methods, language model reasoning, and interdisciplinary applications such as AI governance and bioacoustic analysis of sperm whale communication. He explores the intersection of language models and robotics, developing techniques for scalable system-level reasoning, code generation, and efficient computation allocation. His work also addresses societal challenges, including mitigating misinformation through generative AI and informing policy through white papers on AI governance. Andreas’s contributions span foundational ML theory (e.g., scaling laws) and applied systems (e.g., WhaleLM for bioacoustic analysis). He collaborates across disciplines, integrating cognitive science insights into model design and advocating for ethically aligned AI development. His research has been recognized in MIT’s EECS Faculty Awards and contributes to MIT’s broader mission of impactful technological innovation. While no specific awards are listed, his active role in high-impact projects underscores his academic leadership. His advising and grant work drive collaborative research in AI, with a focus on training next-generation researchers through the MIT-IBM Watson AI Lab and interdisciplinary initiatives.

Daniel Beßlerمشاهده پروفایل

پژوهشگر

• Knowledge Representation
• Cognitive Robotics
• Hybrid Reasoning
• +۴ مورد دیگر

Dr. Daniel Beßler is a Researcher at the University of Bremen specializing in knowledge representation and cognitive robotics. Affiliated with the Institute for Artificial Intelligence, he contributes to the Collaborative Research Center EASE (Extracting and Applying Structure from Everyday Activities) and develops frameworks bridging theoretical AI with practical robotic applications. His educational background includes a PhD in Computer Science from the University of Bremen (2022), with dissertation research on ontological representation of activity context for flexible robot task execution. This foundational work underpins his contributions to semantic reasoning in dynamic environments. Beßler's research centers on hybrid symbolic-subsymbolic reasoning systems, with leadership in developing KnowRob 2.0 – a knowledge processing framework enabling cognition-enabled robotic agents. His work extends to semantic scene representation, activity recognition in virtual reality, and game technology applications for robotics simulation. Key innovations include the SOMA ontology for socio-physical activity modeling and FailRecOnt for failure recovery in robotic planning. Recent publications (2021-2024) reveal strong trends in ontological modeling for robot introspection, user preference representation, and universal scene description translation. His work consistently addresses challenges in activity parsing, metacognition, and knowledge-driven manipulation in cluttered environments. Notable scientific recognitions include: Finalist for Best Robotics Paper Award at AAMAS 2018 Selection as one of the most important publications by IEEE Technical Committee on Cognitive Robotics Beßler has over four years of teaching experience in AI and robotics courses, and six years supervising student projects including RoboCup@Home competitions and Unreal Engine-based human modeling. He has secured research funding through CRC EASE and international collaborations focused on knowledge-driven robotics. As co-author of IEEE 1872.2 standard ontology and lead developer of openEASE cloud platform, he actively shapes robotics standardization while maintaining lab affiliations with CRC EASE and virtual reality research groups exploring GPU programming for interactive AI applications.

Gary Tanمشاهده پروفایل

استاد

• Computer Security
• Formal Methods
• Programming Languages
• +۴ مورد دیگر

Professor Gary Tan is a faculty member in the Department of Computer Science and Engineering at Penn State University, holding the rank of Professor since 2020. He is Co-director of the Institute for Networking and Security Research (INSR) and a co-hire of the Institute for Computational and Data Sciences (ICDS). His research focuses on software security, formal methods, and programming languages, leading the Security of Software (SOS) Group. He has held academic positions at Lehigh University (2008–2020) and Boston College (2005–2008). Education: B.E. in Computer Science from Tsinghua University (1999), Ph.D. in Computer Science from Princeton University (2005), advised by Andrew W. Appel. Additional degrees include a B.E. in Economics from Tsinghua (1999). Research Interests: Gary's work centers on applying compiler, programming language, and formal method techniques to enhance software security. Key areas include secure compilation, binary analysis, control-flow integrity, IoT security, and formal validation of file formats. His SOS Group explores these topics with a focus on practical and verified security solutions. Grants & Funding: Gary has secured over $20 million in external grants, including multiple NSF awards (CAREER, CNS), DARPA projects (GAPS, SafeDocs), and industry collaborations with Microsoft Research, MIT Lincoln Lab, and Intel. His work on VeriPro (DARPA ICS) and SPARTA (DARPA SafeDocs) exemplifies his leadership in securing complex systems. Awards: Notable recognitions include the 2024 Distinguished Paper Award at PLDI, 2023 Outstanding Research Award from Penn State Engineering, and the 2018 Ruth and Joel Spira Excellence in Teaching Award. He is an ACM Distinguished Member and served on the DARPA ISAT study group (2020–2024). Labs & Teams: Gary leads the SOS Group and collaborates with interdisciplinary teams at INSR and ICDS. His research involves advanced tools like MCFI, Robusta, and RockSalt, emphasizing practical security solutions with formal guarantees.

David Demeterمشاهده پروفایل

استادیار

• Artificial Intelligence
• Natural Language Processing
• Medical Diagnostics
• +۳ مورد دیگر

David Demeter is an Assistant Professor of Instruction in the Department of Computer Science at Northwestern University. His research focuses on advancing artificial intelligence, natural language processing, and medical diagnostics through innovative applications of machine learning. He has contributed to projects spanning legal technology, healthcare solutions, and foundational studies of language models. His work includes developing LawLLM for legal system applications, creating diagnostic tools for Congenital Central Hypoventilation Syndrome (CCHS), and exploring prompt engineering strategies for large language models. His interdisciplinary approach bridges domains like sentiment analysis, spectrum sensing algorithms, and compiler-based neural training systems. No scientific awards or notable grants are explicitly mentioned in the provided texts. While his publications reflect active research collaboration, no advising relationships or lab affiliations are detailed in the current data.

Xiaoli Zhangمشاهده پروفایل

دانشیار

• Human-Robot Cooperation
• Knowledge-Based Robotics
• Intelligent Control
• +۸ مورد دیگر

Xiaoli Zhang serves as Associate Professor in the Department of Mechanical Engineering at Colorado School of Mines, where she leads cutting-edge research in human-robot cooperation, intelligent control systems, and teleoperation with applications spanning healthcare, surgery, additive manufacturing, and underground construction. Her work focuses on enhancing robot adaptability and robustness through optimal control, machine learning, and cognitive science principles, supported by facilities like the Intelligent Robotics and Systems Lab. Dr. Zhang's research integrates artificial intelligence with robotics to solve complex engineering challenges, particularly in smart human-machine interaction and shared autonomy systems. Key areas include natural-language-based robot control, gaze-driven assistance interfaces, and physics-informed machine learning for additive manufacturing processes. Her methodologies emphasize real-world applicability in medical robotics and industrial automation, where systems must dynamically adapt to environmental changes and human collaborators. Analysis of her recent publications reveals dominant trends in machine learning-enhanced robotics, with significant contributions to additive manufacturing quality control, dexterous manipulation, and safety-conscious teleoperation systems. Her work consistently bridges theoretical AI advancements with practical engineering applications, particularly in laser-based manufacturing and assistive robotics where human-robot synergy is critical. Scientific recognition includes: NSF CAREER award for pioneering research in robotics and intelligent systems Dr. Zhang directs the Intelligent Robotics and Systems Lab, which develops advanced control frameworks for human-robot teams while securing competitive funding like the NSF CAREER grant. Her educational impact extends through courses such as MEGN 545 Advanced Robot Control and MEGN 441 Introduction to Robotics, training next-generation engineers in autonomous systems design. The lab maintains strong industry partnerships for translating research into surgical robotics and manufacturing applications. The Intelligent Robotics and Systems Lab operates as a multidisciplinary hub where computer vision, machine learning, and mechanical engineering converge to solve real-world problems. Current projects focus on gaze-based control systems for surgical assistance, transfer learning for multi-platform additive manufacturing, and adaptive shared autonomy frameworks that maintain safety during human-robot collaboration in dynamic environments.

Keanan Joynerمشاهده پروفایل

استادیار

• Alcohol and Substance Use Disorders
• Externalizing Psychopathology
• Electroencephalogram/Event-Related Potentials
• +۴ مورد دیگر

Keanan Joyner serves as an Assistant Professor in the Department of Psychology at the University of California, Berkeley, where he directs the Clinical Research on Externalizing and Addiction Mechanisms (C.R.E.A.M.) Lab. His research program investigates the etiology of alcohol and substance use disorders through neuroscientific and behavioral approaches, with particular emphasis on cognitive-affective processes that contribute to the emergence of addiction. Dr. Joyner's research spans three interconnected domains: (1) understanding dispositional trait liabilities for addiction, particularly the interplay between disinhibition and reward sensitivity; (2) bridging between- and within-subject mechanisms of risk using ambulatory assessment techniques; and (3) evaluating and improving the generalizability of addiction models to minoritized and socioeconomically-disadvantaged populations. His work employs diverse methodologies including EEG/ERPs, ecological momentary assessment (EMA), behavioral genetic analyses, and advanced statistical modeling approaches to examine disturbances in cognitive-affective processes across time. Analysis of Dr. Joyner's recent publications reveals a sophisticated methodological approach focused on parsing complex relationships between neural markers and behavioral outcomes in addiction. His work demonstrates increasing attention to diversity and equity in clinical psychophysiology research, with publications addressing racial biases in neuroscience methods and the applicability of psychopathology models to underrepresented populations. A consistent theme across his research is the application of hierarchical taxonomies of psychopathology (HiTOP) to better understand the dimensional structure of externalizing behaviors. Principal Investigator: Clinical Research on Externalizing and Addiction Mechanisms (C.R.E.A.M.) Lab Secondary Advisor: Maria Martin Lopez (PhD candidate in Cognition) Dr. Joyner's laboratory includes graduate students and research staff working on various aspects of externalizing and addiction mechanisms. Current lab members include Maria Martin Lopez (Cognitive Science), Nick Nguyen (Clinical Science), Rishika Shah (Clinical Science PhD student), Geremy Lowe (History of Health Sciences), Danielle Jones (Research Engineer), and Geetika Kapoor (Postbaccalaureate Researcher). The lab's recent work includes projects on improving EEG data collection techniques for Black participants and exploring the semantic network of alcohol and cannabis-related language.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Egoitz Laparra is a Researcher and Adjunct Instructor at the University of Arizona's College of Information Science since 2017. His work focuses on advancing natural language processing (NLP) methods for analyzing human language in medical and environmental domains. He specializes in machine/deep learning techniques for tasks like domain adaptation, information extraction, and semantic parsing. Research Interests: - Natural Language Processing (NLP) with emphasis on medical and environmental applications - Machine learning and deep learning methodologies - Domain adaptation and transfer learning in clinical and policy texts - Geographical ontology development and toponym resolution - Lexical resources like WordNet and predicate matrices Publications highlight innovations in NLP for environmental policy analysis, clinical text mining, and cross-lingual semantic interoperability. His recent work addresses challenges in metadata extraction from environmental impact statements and improving geolocation entity recognition through deep learning. Collaborations include the NewsReader project for cross-lingual news analysis. Laparra contributes to open-source projects like Eidos and INDRA, which transform free text into causal models. He maintains active involvement in international NLP competitions (e.g., SemEval tasks) and develops tools like Taxonomy Builder for knowledge organization.

Doug Saddyمشاهده پروفایل

استاد

• Language Processing
• Cognitive Neuroscience
• Computational Modeling
• +۳ مورد دیگر

Doug Saddy is Professor of Language Sciences and Founding Director of the Centre for Integrative Neuroscience and Neurodynamics (CINN) at the University of Reading. As Director of the MSc in Cognitive Neuroscience program, he promotes interdisciplinary research bridging psychology, neuroscience, and linguistics. Research combines behavioral experiments, neurocognitive methods, and computational modeling to investigate language processing mechanisms. Current projects examine cognitive effects of multilingualism, hierarchical structure learning, and neural dynamics of language comprehension using Lindenmayer grammars. Publication output demonstrates consistent focus on neurocognitive aspects of language processing across typical and clinical populations. Recent work explores multilingual brain restructuring, rhythmic influences on syntax processing, and computational models of hierarchical learning. Leadership includes establishing two university research centers: the Centre for Literacy and Multilingualism and CINN. These initiatives foster collaboration across psychology, neuroscience, and computational disciplines to address complex questions in cognitive science.

Taesoo Kimمشاهده پروفایل

استاد

• Systems Security
• Operating Systems
• Programming Languages
• +۳ مورد دیگر

Taesoo Kim is a Professor at Georgia Tech's College of Computing, jointly affiliated with the School of Cybersecurity and Privacy and the School of Computer Science. He serves as Director of the GTS3 lab and leads research in systems security, operating systems, programming languages, and distributed systems. His work emphasizes foundational security principles and practical tools for system resilience. Education: PhD in EECS from MIT (2014), SM from MIT (2011), BS in Computer Science/Electrical Engineering from KAIST (2009) Affiliations: Georgia Tech's School of Computer Science, School of Cybersecurity and Privacy, ML@GT, and Online Master of Science in Computer Science program Kim's research focuses on building secure computing systems through formal system design, implementation analysis, and trusted component isolation. Notable contributions include tools for automatic vulnerability detection, intrusion recovery frameworks, and secure enclave technologies like SGX-Tor. His work has secured grants from ONR, NSF, DARPA, and industry partners. Awards include the 2015 Internet Defense Prize and a finalist placement in the DARPA Cyber Grand Challenge. Key projects include QSYM (concolic execution engine), RAIN (attack tracing), and FREEDOM (DOM fuzzer). Kim teaches courses on information security and blockchain technologies. His lab (SSLab) collaborates with industry on critical security challenges, including hardware-software co-design for trusted execution environments.

Viktor Kunčakمشاهده پروفایل

دانشیار

• Program Synthesis
• Program Verification
• Automated Reasoning
• +۳ مورد دیگر

Viktor Kunčak is an Associate Professor with tenure at the École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences. He leads the Laboratory for Automated Reasoning and Analysis (LARA) and has been at EPFL since 2007 after completing his PhD at the Massachusetts Institute of Technology (MIT). His educational background includes: PhD from Massachusetts Institute of Technology (MIT), 2007 Professor Kunčak's research focuses on bridging the gap between human goals and computational realizations through program synthesis , verification , and automated reasoning . His work has significant applications in software development, formal methods, and programming languages. He is particularly known for developing practical tools like Leon and Stainless that implement theoretical advances in automated reasoning. His recent publications demonstrate a consistent focus on advancing program synthesis techniques, verification frameworks, and formal methods. The research trajectory shows progression from foundational theoretical work to practical applications and tools that can be used by developers. Many papers focus on making verification and synthesis more accessible and efficient for real-world programming tasks. His notable scientific achievements include: ACM SIGSOFT Distinguished Paper Award for work on automated testing European Research Council (ERC) Grant of 1.5M EUR (2012) Communications of the ACM Research Highlight for a PLDI paper Professor Kunčak has supervised 13 completed PhD theses and teaches courses on functional and parallel programming, compilers, and verification at EPFL. He has also co-taught a popular MOOC on Parallel Programming that reached over 100,000 learners worldwide. His research has been supported by significant funding including a 5-year ERC grant. He has served in leadership roles for major conferences including as program co-chair for FMCAD 2014 and VMCAI 2012. He leads the Laboratory for Automated Reasoning and Analysis (LARA) at EPFL, which develops tools like Stainless for program verification. The lab has established an international presence through collaborations including a European COST Action to establish standardized formats for verification and synthesis (Rich Model Toolkit).