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Zachary KincaidView profile

Associate Professor

• Program Analysis
• Formal Methods
• Programming Languages
• +4 more

Zachary Kincaid is an Associate Professor in the Department of Computer Science at Princeton University's School of Engineering and Applied Science. His research focuses on program analysis, logic, and programming languages, with an emphasis on making program analysis compositional and robust. He received his PhD from the University of Toronto under the supervision of Azadeh Farzan. His work has been implemented in the Duet program analyzer, and he has an Erdős number of 3. Dr. Kincaid's research interests include: Compositional program analysis techniques Algebraic approaches to program analysis Termination analysis and ranking function synthesis Verification of concurrent and parallel programs Automated reasoning and decision procedures Analysis of numerical programs and loops His recent publications show a strong focus on developing novel techniques for program analysis that bridge theoretical computer science with practical verification tools, particularly in nonlinear analysis, quantified reasoning, and compositional verification. Dr. Kincaid has received research support from ONR grant N00014-19-1-2318 for his work on robust program analysis. He has advised graduate students including: Current: Jake Silverman, Nicolas Koh, Nikhil Pimpalkhare Graduated: Shaowei Zhu (PhD 2024, Researcher at Amazon), Charlie Murphy (PhD 2023, Postdoc at University of Wisconsin–Madison) Dr. Kincaid teaches courses including: COS 320 – Compiling Techniques (Spring 2024, 2022, 2020, 2019) COS 516 / ELE 516 – Automated Reasoning about Software (Fall 2025, 2022, 2018) COS 217 – Introduction to Programming Systems (Fall 2024) COS IW – Practical Solutions to Intractable Problems (Fall 2023, Spring 2023, 2018, 2017) COS IW – Little Languages (Spring 2018) COS 597D – Reasoning about concurrent systems (Fall 2016)

Felix Xiaozhu LinView profile

Associate Professor

• Systems Software
• Operating Systems
• Computer Architecture
• +4 more

Felix Xiaozhu Lin serves as Associate Professor and William Wulf Faculty Fellow in the Department of Computer Science at the University of Virginia's School of Engineering and Applied Science, where he directs the Computer Science Ph.D. Program and MCS/MS Program. Previously a tenured Associate Professor at Purdue University's School of Electrical and Computer Engineering, Lin joined UVA Engineering in August 2020 after completing his doctoral research at Rice University. His educational credentials include: Ph.D. in Computer Science, Rice University (2014) M.S. in Computer Science, Tsinghua University (2008) B.S. in Automation, Tsinghua University (2006) Lin's research centers on systems software at the intersection of operating systems, compilers, and computer architecture, with emphasis on accelerating and safeguarding software systems. His current projects target on-device large language models and speech processing for low-cost hardware ( Analysis of his recent publications reveals a strong trajectory in edge computing and efficient AI systems. His research demonstrates increasing focus on hardware-software co-design for autonomous devices, with significant contributions in video analytics for energy-constrained cameras, kernel virtualization for heterogeneous architectures, and stream processing frameworks leveraging emerging memory technologies. The work consistently addresses real-world constraints like power limitations and network intermittency while maintaining rigorous academic standards. His scientific recognition includes: National Science Foundation CAREER Award (2019) Google Faculty Research Award (2016) NSF CISE Research Initiation Initiative Award (2015) ACM ASPLOS Best Paper Award (2014) Lin leads the XSEL research group mentoring graduate and undergraduate students in systems software development. His educational initiatives include CS4414/CS6456, a modern operating systems course featuring Arm64 baremetal kernel development, multicore systems, trusted execution environments, and filesystem forensics. The course's experiential approach has received strong student feedback for its modern content and practical relevance. His group actively recruits for projects spanning on-device AI, hardware-accelerated speech processing, and next-generation OS development. Based in Charlottesville, Virginia, Lin's research benefits from UVA's proximity to Shenandoah National Park and collaborative opportunities within the university's vibrant computing ecosystem, including the 2024 LLM Workshop he co-organized with Professor Yangfeng Ji.

Jeff ZhangView profile

Assistant Professor

• Deep learning
• Computer architecture
• Embedded systems
• +5 more

Jeff Zhang is an Assistant Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. He joined ASU in January 2023 after completing a postdoctoral fellowship at Harvard University. His research spans deep learning, computer architecture, embedded systems, and EDA, with particular emphasis on energy-efficient and fault-tolerant design for AI/ML systems and hardware accelerators. Education: Ph.D., New York University M.Eng., B.Eng., Hunan University Dr. Zhang's research bridges theoretical machine learning with practical hardware implementation, developing novel architectures that optimize performance, power consumption, and reliability. He has pioneered approaches for hardware acceleration of large language models, efficient sparse matrix operations, and novel memory technologies for AI workloads. His work has received multiple awards including IEEE Top Picks in Test and Reliability (2023) and IEEE Micro Best Paper Award (2022). His recent publications demonstrate a strong trend toward heterogeneous computing, with significant work in chiplet-based AI accelerators, photonic computing for AI, and 2.5D/3D integration techniques. The research spans from high-level compiler frameworks to circuit-level innovations, with a consistent theme of co-designing algorithms and hardware for optimal AI performance. His work on the SODA toolchain has been particularly influential in bridging Python to silicon. Scientific Awards: IEEE Top Picks in Test and Reliability, IEEE ITC, 2023 Best Paper Award, IEEE Micro, 2022 Best Paper Award Candidate, IEEE DATE, 2022 Best Presentation Award Nomination, ACM SIGDA DATE PhD Forum, 2020 Best Paper Award Nomination, IEEE VLSI Test Symposium, 2018 Ernst Weber Ph.D. Fellowship, New York University, 2015, 2016 Dr. Zhang actively mentors a diverse group of graduate and undergraduate students, with several alumni now working at leading technology companies including Apple, TSMC, and Ansys. His research is supported by prestigious grants from NSF, Sandia National Labs, and industry partners. He serves on technical program committees of numerous top conferences and has organized special sessions on emerging topics like Gen AI for Chip Design and LLM-Aided Design. Dr. Zhang leads a vibrant research group that collaborates extensively with industry partners and national laboratories. Current projects focus on next-generation AI hardware, including chiplet-based systems, photonic accelerators, and novel memory technologies for large language models. His group has developed several open-source tools and frameworks, including the SODA toolchain for bridging Python to silicon.

• Health Literacy
• Public Health
• Education
• +7 more

Orkan Okan is a Professor of Health Literacy at the Department of Health and Sport Sciences , Technical University of Munich (TUM) , since 2021. He holds a PhD in Educational Science (2020, Bielefeld University, summa cum laude) and studied Educational Science with a focus on teacher training at the University of Duisburg-Essen. His research centers on health literacy in childhood and adolescence , particularly within school and educational contexts , integrating digitalization, media literacy, and infodemiology . He leads the WHO Collaborating Centre for Health Literacy and coordinates global networks like Covid-HL and GLOBHL . Education : PhD in Educational Science (Bielefeld University, 2020), MSc in Educational Science (University of Duisburg-Essen) Leadership Roles : Vice President of the International Health Literacy Association (2022), Deputy Chair at IUHPE (2019) Research Interests include: Health literacy as a social vaccine during pandemics Organizational health literacy in school systems Development of cross-cultural measurement tools for health literacy Digital health literacy and infodemic management Integration of health literacy into educational policy Gender disparities in health literacy outcomes Recent Publications (2022–2023) reveal trends in: Global pandemic responses using health literacy frameworks Psychosocial impacts of pandemic stress on school leaders Digital transformation in health education School-based interventions for adolescent health Cross-national comparisons of literacy models Policy development for health-literate institutions Scientific Awards include: Vice President, International Health Literacy Association (2022) Vice President, EUPHA Health Promotion Section (2016) Deputy Chair, IUHPE Global Working Group on Health Literacy (2019) Advising and Grants involve: Co-founding the Global Covid-19 Health Literacy Network Leading the BMBF-funded HLCA research consortium (since 2015) Contributing to WHO’s international health literacy measurement frameworks Lab and Team Affiliations include: Head of the Health Literacy Unit at TUM Member of the Unesco Chair Global Health and Education (since 2019) Coordinating international research teams across Germany, Denmark, Finland, and Ecuador

• English Linguistics
• Lexicography
• Spoken Language Analysis
• +3 more

Dr. Brigitta Mittmann is a Senior Lecturer at the Department of English and American Studies, Friedrich-Alexander University Erlangen-Nuremberg (FAU), holding the Alexander von Humboldt Professorship for Language and Cognition. Her work focuses on lexicography, phraseology, and comparative analysis of spoken English varieties.

• Corpus Linguistics
• Applied Linguistics
• Theoretical Linguistics
• +3 more

Professor Tony McEnery is a Distinguished Professor of English Language and Linguistics at Lancaster University, where he has held various senior roles, including Dean of the Faculty of Arts and Social Sciences (2008–2014) and Head of the Department of Linguistics and English Language (2000–2005). His research focuses on corpus linguistics, applied linguistics, and sociolinguistics, with notable contributions to corpus-based analyses of historical medical discourse, media representation of Islam, and swearing in English. He has led major research projects, including the ESRC Centre for Corpus Approaches to Social Science (CASS) and the Trinity Lancaster Corpus. McEnery has secured over £10 million in research funding and holds visiting professorships at institutions worldwide, including Zhejiang University of Media and Communications and Shanghai International Studies University. He is a Fellow of the Academy of Social Sciences, Trinity College London, and the Royal Society for the Arts. Education: No explicit details provided, but his career trajectory implies advanced degrees in linguistics. Research Interests: Corpus linguistics applications in theoretical and applied linguistics, historical language analysis, and language as a socially situated phenomenon. McEnery’s work extends to interdisciplinary collaborations, including projects with the Environment Agency and the Home Office. His teaching includes summer schools in corpus linguistics and a Futurelearn MOOC, reaching tens of thousands globally. He advises on research funding for international bodies like the Irish Research Council and the Qatar National Research Foundation. Grants and Awards: Queen’s Anniversary Prize (2015), Changjiang Chair (2021), and multiple fellowships. Current grants include the Lancaster-Northern Arizona corpus and the Trinity Lancaster Corpus projects. Advising and Labs: Supervises postgraduate students in linguistics and collaborates with teams like the ESRC CASS Centre and UCREL (University Centre for Computer Corpus Research on Language).

Yingfei XiongView profile

Associate Professor

• Software Engineering
• Programming Languages

Yingfei Xiong is an active Associate Professor at Peking University, China, specializing in software engineering and programming languages. With a consistent research trajectory from 2013 through 2026, Xiong has established themselves as a prominent figure in the software engineering research community, regularly contributing to top-tier conferences including SPLASH, ICSE, ASE, and PLDI. Dr. Xiong's research primarily focuses on program synthesis, automated program repair, and software analysis techniques. Their work bridges theoretical programming language concepts with practical software engineering applications, particularly in developing novel approaches for code generation, bug fixing, and program optimization. The research demonstrates strong interdisciplinary connections between traditional software engineering, programming languages theory, and emerging AI techniques. Analysis of Xiong's publication trends reveals a clear evolution in research focus, beginning with foundational work in API transformations and program adaptation around 2013-2016, shifting toward program repair techniques from 2017-2020, and most recently incorporating machine learning and neural approaches into program synthesis and repair (2021-2026). The work consistently addresses practical challenges in software development while maintaining theoretical rigor, with increasing integration of AI techniques in recent years. Dr. Xiong has served in various leadership roles across the software engineering conference ecosystem, including program committee membership and session chair positions at major conferences. Their extensive service demonstrates recognition by peers as a subject matter expert in software engineering and programming languages research. While specific grant information isn't detailed in the provided text, the sustained publication record suggests successful research funding.

Stephanie Smith MatthewsView profile

Associate Professor

• Hebrew Bible
• Ancient Israel
• Gender Studies
• +6 more

Stephanie Smith Matthews is a Full-Time Associate Professor of Old Testament at Point Loma Nazarene University (PLNU). She holds a PhD in Hebrew Bible and Ancient Israel from Vanderbilt University, an M.T.S. in Biblical Studies from University of Notre Dame, and dual B.A. degrees in Biblical Studies & Spanish from Olivet Nazarene University. Specializes in Hebrew Bible, Gender Studies, and Theological Ethics Focuses on reproductive health narratives, prophetic imagination, and justice themes Active in Society of Biblical Literature and Wesleyan Theological Society Her research connects ancient texts with modern bioethical concerns through interdisciplinary approaches. Publications span topics from maternal pain in Genesis to Wesleyan theological applications. 2024 presentations on ancient pain narratives and AuDHD preaching 2020-2024 grants and fellowships support her theological scholarship Notable contributions include co-edited textbooks and critical analyses of gender dynamics in biblical contexts.

Farzaneh DerakhshanView profile

Assistant Professor

• Type Theory
• Proof Theory
• Programming Languages
• +7 more

Dr. Farzaneh Derakhshan is an Assistant Professor in the Computer Science Department at Illinois Institute of Technology (Illinois Tech), where she explores logical foundations of concurrency and develops formal methods for program verification. She earned her Ph.D. in Pure and Applied Logic from Carnegie Mellon University in 2021 under Frank Pfenning, followed by a postdoctoral fellowship at CMU with Limin Jia and Stephanie Balzer. Current affiliation: Illinois Tech (since ~2021) Previous affiliation: Carnegie Mellon University (Ph.D. and postdoc) Research focus: Type theory, logical verification, and security for concurrent systems Teaching: Courses on programming languages, type systems, and security Her research addresses fundamental challenges in concurrent programming, including: Developing modal logic frameworks for system verification Designing type systems for intermittent computing Creating behavioral type systems for security guarantees Applying relational logic to GPU security and secure compilation Investigating logical foundations of session-typed processes Formal verification of cyclic process networks Current research trends include: Hybrid dynamic verification for parallel systems Logical approaches to side-channel security Formal methods for cyber-physical systems Crash-resilient computing models Security verification in decentralized applications Noninterference proofs in session-typed concurrency Scientific recognition: NSF SaTC CORE Collaborative Award #2350217 Organizing committee member at Dagstuhl Seminar 26071 Professional leadership: Program committee co-chair for PLACES 2025 Committee roles at LICS 2026, ESOP 2026, ICFP 2025, and ECOOP 2025 Regular reviewer for ACM Transactions journals Laboratory involvement: Co-director of behavioral types research at Illinois Tech Collaboration with Carnegie Mellon's formal verification group Key participant in the FACCT workshop

Afshin AshariView profile

Assistant Professor

• Computational Design
• Mixed-Reality Environments
• Public Space Design
• +6 more

Afshin Ashari is an Assistant Professor in Landscape Architecture at the School of Environmental Design and Rural Development , University of Guelph. Prior to academia, he worked at BrookMcIlroy Inc., an interdisciplinary firm in Toronto, on architectural and landscape projects in public and private sectors. Education : Masters in Landscape Architecture, University of Toronto Bachelor of Computer Engineering, Azad University of Tehran Research Interests : Afshin explores the intersection of computational design and mixed-reality environments, focusing on: Art-Technology Unity in Public Spaces Algorithmic and Parametric Modeling Data-Driven Design Approaches Interactive Immersive Environments Biophilic Design Agricultural Urbanism Article Trends : His publications emphasize: AI tools for design processes Parametric modeling in urban rehabilitation Climate change communication via social media Drones for visual impact assessments Augmented reality in public spaces Historical and future-oriented design frameworks

Pasquale Davide SchiavoneView profile

Lecturer

• Embedded Systems
• RISC-V Architecture
• Ultra-low-power Computing
• +5 more

Pasquale Davide Schiavone holds multiple research and teaching positions at École Polytechnique Fédérale de Lausanne (EPFL), serving as a Lecturer at the School of Computer and Communication Sciences (IC) and as a Scientist at both the Embedded Systems Laboratory (ESL) within the School of Engineering (STI) and PAT Administration. His interdisciplinary work bridges computer architecture, embedded systems design, and biomedical applications, with office located at ELG 136 in Lausanne, Switzerland. Dr. Schiavone's research focuses on ultra-low-power computing systems, particularly RISC-V architectures and TinyML applications for edge devices. His work develops open-source hardware platforms like X-HEEP and HEEPOCRATES that enable energy-efficient AI at the edge, with applications spanning biomedical monitoring, neural interfaces, and wearable computing. He explores innovative hardware-software co-design approaches to overcome energy constraints in resource-limited environments. His recent publications reveal a consistent research trajectory centered on open, configurable computing platforms for specialized applications. The work spans from fundamental RISC-V architecture improvements (ARCANE, e-GPU) to application-specific implementations for biomedical contexts (BiomedBench, neural interfaces). A strong emphasis on energy efficiency permeates all his research, whether through novel arithmetic approaches (Posit), system architecture (near-memory computing), or specialized accelerators (Strela, Quadrilatero). Lecturer, School of Computer and Communication Sciences (IC) Scientist, Embedded Systems Laboratory (ESL), School of Engineering (STI) Scientist, PAT Administration, School of Engineering (STI) Dr. Schiavone teaches courses on hardware compilation, presenting algorithms and methods for transforming hardware description languages into optimized circuit implementations. His Embedded Systems Laboratory work places him at the forefront of developing practical, open-source solutions for next-generation computing challenges in energy-constrained environments.

Ilia PolianView profile

Professor

• Circuit Architecture
• System Design
• Hardware Reliability
• +6 more

Prof. Ilia Polian serves as Head of the Institute of Computer Engineering and Chair of the Hardware-Oriented Computer Science (HOCOS) department at the University of Stuttgart. His leadership spans research, teaching, and institutional coordination across multiple high-impact projects. Prof. Polian's research focuses on developing circuit and system architectures based on both traditional and novel principles, including neuromorphic, stochastic, and approximate architectures. His second major research focus is systematic design methodology and design automation, with particular emphasis on safety and reliability properties of developed systems. Current research directions include quantum computing engineering, secure mixed-signal neural networks, and resource-efficient stochastic circuits for near-sensor computing applications. His recent publications demonstrate strong trends in quantum computing (particularly circuit partitioning and compilation for multi-QPU architectures), hardware security (including memristive cryptographic implementations), and AI-driven approaches to hardware testing and reliability. These works bridge fundamental computer architecture research with practical industrial applications. University of Stuttgart's Publication Prize for Paper on Partitioning of Quantum Circuits Prof. Polian actively supervises doctoral students including Devanshi Upadhyaya, and leads significant research grants such as the DFG Priority Program Nano Security which he coordinates. His department offers numerous thesis and research opportunities for students interested in cutting-edge hardware research. The Hardware-Oriented Computer Science department maintains strong collaborations with industry partners including IBM, Infineon Technologies, and Advantest, as well as academic institutions through the IQST Graduate School and QuantumBW initiatives.

Sarah E. ChasinsView profile

Assistant Professor

• Programming Languages
• Human-Computer Interaction
• Program Synthesis
• +3 more

Sarah E. Chasins is an Assistant Professor in the Electrical Engineering and Computer Sciences (EECS) department at the University of California, Berkeley, with research spanning programming languages and human-computer interaction. She leads the PLAIT Lab (Programming Languages for Approachable and Inclusive Tools) and serves as a faculty affiliate at the Berkeley Institute for Data Science (BIDS). Her work bridges computer science with social sciences, climate reporting, legal systems, and biological research through extensive collaborations. Dr. Chasins' research focuses on democratizing programming for non-traditional programmers including scientists, social scientists, journalists, and data scientists. Her work emphasizes creating approachable programming tools that help practitioners reach correct programs while understanding, extending, and trusting those programs. She specifically investigates program synthesis, programming tools for scientific domains, and human-centered programming language design. Her research mission aims to make programming a path to a more informed and evidence-driven society rather than just a way to get wrong answers faster. Her recent publications demonstrate a clear trajectory toward making programming more accessible and understandable. The work spans code search techniques, program synthesis approaches, refactoring tools, and studies of how domain experts interact with programming languages. A consistent theme across her research is placing human needs at the center of programming language design and implementation. Dr. Chasins actively mentors PhD students including Justin Lubin, Eric Rawn, Parker Ziegler, Sarah "Slim" Lim, Hellina Hailu Nigatu, David Minh-Duy Cao, and Marlena Preigh. She has previously advised numerous master's and undergraduate students who have gone on to work in both academia and industry. Her teaching includes core courses like CS164 (Programming Languages and Compilers) and specialized courses like CS294-184 (Building User-Centered Programming Tools) and CS39-001 (Technology, Society, and Power). She maintains an active service record in the programming languages community, having served on program committees for major conferences including PLDI, POPL, OOPSLA, and SPLASH. Notably, she co-chaired the Student Research Competition at PLDI 2020 and 2021 and has been involved in organizing workshops focused on programming languages and human-computer interaction.

Todd MillsteinView profile

Professor

• Network Verification
• Programming Languages
• Probabilistic Programming
• +3 more

Todd Millstein is a Professor in the Computer Science Department at the University of California, Los Angeles (UCLA). He served as the Computer Science Department Chair from 2022-2025 and is also an Amazon Scholar. His research focuses on making software systems more reliable through programming languages techniques, with significant contributions to network verification and probabilistic programming. Millstein received his Ph.D. from the University of Washington Department of Computer Science, where he was a member of the Cecil group led by Craig Chambers. Prior to that, he completed his undergraduate studies at Brown University under the guidance of Paris Kanellakis and Pascal Van Hentenryck. Millstein's research spans several areas of programming languages and systems with a focus on reliability. He has made significant contributions to network verification, developing the Batfish network configuration analyzer which is now managed by Amazon Web Services and forms the basis of Oracle Cloud's Network Path Analyzer. His work has been recognized with the ACM SIGCOMM Networking Systems Award in 2025. He also works on interactive program verification through lemma synthesis and scalable reasoning methods for probabilistic programming languages. His research bridges programming languages theory with practical systems challenges, as highlighted in his SPLASH/OOPSLA 2024 keynote "Everything is a Program (even if it's not)". Millstein's recent publications demonstrate a consistent focus on verification and reliability across multiple domains. His work shows a progression from foundational programming language techniques to practical applications in networking and probabilistic systems. Key themes include data-driven approaches to program analysis, synthesis of verification artifacts, and applying programming languages techniques to non-traditional domains like network configuration. Millstein's scientific achievements have been recognized with numerous prestigious awards including an NSF CAREER Award, an ACM SIGPLAN Most Influential PLDI Paper Award, an ACM SIGCOMM Networking Systems Award, IEEE Micro Top Picks selection, best-paper awards from PLDI, OOPSLA, and SIGCOMM, a Microsoft Research Outstanding Collaborator Award, an Okawa Foundation Research Grant, an IBM Faculty Award, and a Facebook Research Award. He has also received both the Northrop Grumman Excellence in Teaching Award (for junior faculty) and the Eon Instrumentation Inc. Excellence in Teaching Award (for senior faculty) from UCLA Engineering. Millstein advises several Ph.D. students including Ana Brendel, Poorva Garg (co-advised with Guy Van den Broeck), Rajdeep Mondal (co-advised with George Varghese), and Rathin Singha (co-advised with George Varghese). His research has been supported by various grants including an NSF CAREER Award, Okawa Foundation Research Grant, IBM Faculty Award, and Facebook Research Award. He has also been a Co-Founder and Chief Scientist of Intentionet, which was later acquired by Amazon Web Services. Millstein is actively involved in the Batfish project, an open-source network configuration analyzer that has had significant practical impact. Batfish is now managed by AWS, powers Oracle Cloud's Network Path Analyzer, and is used by dozens of companies. His research group continues to work on network reliability, developing techniques for scalable BGP policy verification and behavioral testing of protocol implementations.

Haiyang AiView profile

Associate Professor

• Corpus Linguistics
• Natural Language Processing
• Second Language Acquisition
• +3 more

Haiyang Ai is an Associate Professor in the Literacy and Second Language Studies program at the University of Cincinnati's School of Education. His research applies corpus linguistics and natural language processing to investigate second language acquisition, writing complexity, and bilingual language processing. His educational background includes a Ph.D. in Applied Linguistics from The Pennsylvania State University (2015), an M.A. in Linguistics & Applied Linguistics from the University of Chinese Academy of Sciences (2006), and a B.A. in English from Shaanxi Normal University (2003). Dr. Ai's research spans corpus linguistics, natural language processing, second language acquisition, and computer-assisted language learning. He specializes in compiling and analyzing native and learner corpora to develop intelligent language learning systems and investigate lexical/syntactic complexity in L2 writing. His methodological approach integrates computational tools with theoretical linguistics to address practical language teaching challenges. His recent publications (2019-2023) demonstrate consistent focus on lexical bundles in professional communication, automating complexity measurement in Chinese, speech perception mechanisms in bilinguals, and grammatical puzzles in English learning. These works bridge corpus-based analysis with psycholinguistic experimentation across diverse subfields including morphosyntax, pragmatic competence, and cognitive processing in L2 acquisition. Dr. Ai has secured multiple University of Cincinnati grants including three CECH Faculty Development Grants ($2500 in 2017-2018 for verb-noun collocation research, $2000 in 2016-2017 for corrective feedback tools) and the NCFDD Faculty Success Program ($3250 in 2017), all supporting his development of computational language learning resources.