جستجوی استاد راهنمای دانشگاهی

Mithuna S. Thottethodiمشاهده پروفایل

استاد

• Computer Architecture
• Interconnection Networks
• Distributed Systems
• +۷ مورد دیگر

Mithuna S. Thottethodi is a Professor and Interim Associate Head of Teaching and Learning at the Elmore Family School of Electrical and Computer Engineering at Purdue University. He holds a B.Tech. from the Indian Institute of Technology, Kharagpur (1996), and a Ph.D. in Computer Science from Duke University (2002). His research focuses on computer architecture, interconnection networks, distributed systems, and security, with notable work on sparse tensor accelerators and processing-near-memory architectures. His work has been funded by the NSF, AT&T, and SK Hynix. Research interests include security, interconnection networks in multicores, storage performance optimization, and memory hierarchies. Notable contributions span hardware accelerators for machine learning, secure speculative execution, and datacenter network congestion control. He has advised over 20 graduate students, many of whom have joined top tech firms like Google, Microsoft, and Intel. Awards: NSF CAREER Award (2007) Wilfred Hesselberth Teaching Excellence Award (2021) Multiple Eta Kappa Nu Outstanding Professor Awards Teaching includes undergraduate courses like EE 437 (Computer Design) and graduate courses such as ECE 666 (Advanced Computer Architecture). He also advises VIP and EPICS student teams.

Phillip B. Gibbonsمشاهده پروفایل

استاد

• Parallel Computing
• Distributed Systems
• Databases
• +۴ مورد دیگر

Phillip B. Gibbons is a Professor in both the Computer Science Department and Electrical & Computer Engineering Department at Carnegie Mellon University. He received his Ph.D. in Computer Science from the University of California at Berkeley in 1989 and has held research positions at AT&T Bell Laboratories, Lucent Bell Laboratories, and Intel Research Pittsburgh before joining CMU's faculty. His research spans parallel computing, distributed systems, databases, computer architecture, and machine learning. Gibbons' work bridges theory and systems, with publications in top-tier conferences including SOSP, OSDI, SIGMOD, VLDB, NeurIPS, and many others across computer science and engineering disciplines. His research has been supported by significant funding from NSF, Intel, and other organizations. Gibbons has made substantial contributions to streaming algorithms, parallel computing frameworks, distributed systems security, and large-scale machine learning systems. His work on data stream algorithms with Alon, Matias, and Szegedy has been particularly influential in the field. He has served in numerous leadership roles including Editor-in-Chief of ACM Transactions on Parallel Computing (2012-2018) and on the editorial boards of Journal of the ACM and IEEE Transactions on Cloud Computing. He has also been active on program committees for major conferences in systems, databases, and theory. IEEE Fellow (2014) - For contributions to parallel computing and databases ACM Fellow (2006) - For contributions to parallel computing, databases, and sensor networks Selected for Oral Presentation at NeurIPS '13 (only 20 selected out of 1420 submissions) Co-winner of the best paper award for NSDI '06 Gibbons has advised numerous students and mentored researchers who have gone on to make significant contributions in academia and industry. His research has been supported by major grants including the $15M Intel Science and Technology Center for Cloud Computing (2011-2015) where he served as Co-PI/Co-Director. He currently leads research projects on write-efficient algorithms, big learning systems, and visual cloud systems. His laboratory work focuses on bridging theoretical computer science with practical systems implementation, particularly in the areas of parallel and distributed computing. Current research directions include adapting algorithms for emerging memory technologies and optimizing machine learning systems for large-scale deployment.

• Formal Verification
• Software Testing
• Programming Languages
• +۱۲ مورد دیگر

Alastair F. Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he leads the FastPL research group. His work bridges formal methods, software testing, and programming languages, with a focus on enhancing the reliability of high-performance and parallel software systems. He has held key roles including Director of Research (since 2023) and previously served as Lecturer (2011–2014), Senior Lecturer (2014–2017), and Reader (2017–2020) before being promoted to Professor in 2020. His research interests include formal verification, compiler testing, GPU programming, concurrency, and fuzzing. He has made significant contributions to the verification of GPU kernels, metamorphic testing of graphics drivers, and the development of tools like GPUVerify and GraphicsFuzz. His work combines theoretical rigor with practical impact, demonstrated by the acquisition of his startup GraphicsFuzz by Google in 2018 and his subsequent roles as Senior Software Engineer and Visiting Researcher at Google. His recent publications reflect a sustained focus on compiler and system reliability, with trends in fuzzing, formal specification, and automated testing of complex systems such as WebGPU, CXL cache coherence, and large language models for code generation. His work increasingly integrates empirical validation with formal techniques to uncover subtle bugs in real-world systems. Scientific awards and recognitions include: 2017 BCS Roger Needham Award EPSRC Early Career Fellowship Fellow of the British Computer Society Best Paper awards at EuroSys 2024, MET 2021, IISWC 2019, IWOCL 2019, and ICST 2016 Best Industry Paper at ICST 2024 ACM SIGSOFT Distinguished Paper at ISSTA 2023 ACM SIGPLAN Most Influential OOPSLA Paper Award (2012 paper), awarded in 2022 Best Student Paper at PPoPP 2014 He has advised numerous PhD students and leads a vibrant research group. He has secured significant research funding and collaborates extensively with industry and academia. His service includes leadership roles such as General Chair of PLDI 2020, PC Chair of ECOOP 2019, and Steering Committee Chair of PLDI (2022–2025). He also serves on the advisory board of PACM-PL and on program committees for top venues including POPL, OOPSLA, PLDI, ICSE, and ISSTA. He leads the FastPL research group, which focuses on the design and implementation of programming tools and techniques for reliable software. The group conducts cutting-edge research in compiler testing, formal methods, and high-performance systems, fostering collaboration across academia and industry.

Jai Massariمشاهده پروفایل

مدرس

• Banking and Financial Regulation
• Digital Assets
• Cryptocurrencies
• +۴ مورد دیگر

Jai Massari serves as a Lecturer at the University of California, Berkeley School of Law and holds a Fellowship at the Berkeley Center for Law and Business, while concurrently acting as cofounder and Chief Legal Officer of Lightspark. Her academic appointment complements extensive industry experience: after 11 years at Davis Polk & Wardwell LLP—including five as partner leading the firm's fintech and cryptocurrency practice—she specializes in financial regulatory frameworks spanning digital assets, banking, derivatives, and payment systems. Educational credentials include a JD from Duke University School of Law and a BA in Chemistry from Cornell University. Research interests center on Banking and Financial Regulation with particular emphasis on cryptocurrency applications and evolving regulatory challenges in digital finance, drawing directly from her frontline legal practice. Her industry leadership informs practical curriculum development in financial law despite limited traditional academic publication output. Professional narrative highlights a seamless integration of private-sector legal expertise into academic instruction, with no documented student advisement or formal research grants but significant real-world impact through corporate governance and regulatory compliance initiatives at Lightspark.

Timothy M. Jonesمشاهده پروفایل

استاد

• Compilers
• Computer Architecture
• Binary Modification
• +۳ مورد دیگر

Timothy M. Jones is a Professor of Computer Architecture and Compilation at the University of Cambridge Computer Laboratory, where he leads research in systems-level computing. He is also a Fellow at Gonville and Caius College, contributing to academic leadership and student mentorship within the collegiate system. His primary affiliation with the Computer Laboratory positions him at the forefront of systems research within the university. Dr. Jones's research focuses on extracting various forms of parallelism (thread-level, data-level, memory-level) to enhance computational performance while addressing energy efficiency and reliability challenges. His work spans compiler design, binary translation, and microarchitecture optimization, with specific interest areas including: Compiler technologies for functional and parallel programming Hardware reliability and fault tolerance mechanisms Binary analysis and instrumentation frameworks Memory system optimization and virtual memory management Security enhancements through binary modification Runtime systems for heterogeneous architectures Analysis of his recent publications reveals strong emphasis on systems-level innovation, particularly in fault tolerance techniques, binary analysis tools, memory optimization, and parallel execution frameworks. His work consistently bridges theoretical computer science with practical hardware implementation challenges. Dr. Jones maintains active participation in the academic community through conference leadership roles, including serving as Program Co-Chair for CGO 2026 and committee positions at premier venues including ISMM, CGO, and ECOOP. He contributes to open-source academic resources through GitHub and maintains professional engagement via Twitter.

Victor R. Leeمشاهده پروفایل

دانشیار

• Data Science Education
• STEM Education
• K-12 Education
• +۴ مورد دیگر

Victor R. Lee serves as an Associate Professor at Stanford University's Graduate School of Education, with his office located at CERAS Building (520 Galvez Mall, Suite 531) in Stanford, California. He is actively affiliated with the Center for Studies in Education and Technology (CSET), where he conducts interdisciplinary research at the intersection of technology and learning. Dr. Lee holds a Ph.D. in Learning Sciences from Northwestern University and earned dual Bachelor's degrees in Cognitive Science and Mathematics from the University of California, San Diego. His academic trajectory bridges technical disciplines with educational research, establishing a foundation for his work in data-intensive learning environments. His research program centers on two interconnected domains: data literacy development in K-12 contexts and STEM education innovation across diverse learning spaces. He investigates how individuals make meaning from data during inquiry-based learning, with particular emphasis on self-collected student data and the epistemological challenges of data sense-making. Concurrently, his STEM education work spans traditional classrooms, makerspaces, computer labs, and school libraries, examining engaged learning practices and conceptual change in mathematics and science. Current projects focus on identifying the specialized knowledge teachers require to effectively scaffold student interactions with complex real-world datasets. Recent publications (2023-2024) reveal a strategic pivot toward artificial intelligence education, examining both teacher preparation and student understanding of AI systems. His work demonstrates consistent methodological rigor through design-based research, classroom implementations, and analysis of student reasoning patterns, particularly regarding how learners conceptualize algorithmic processes in platforms like YouTube. As a core faculty member within CSET, Dr. Lee collaborates with multidisciplinary teams to develop and evaluate educational interventions that bridge theoretical learning sciences with practical classroom applications, with recent emphasis on AI literacy tools and data-enabled pedagogical approaches.

• Programming Language Design
• Program Verification
• Type Theory
• +۳ مورد دیگر

Neelakantan R. Krishnaswami is a Professor of Computer Science at the University of Cambridge's Computer Laboratory , and a Fellow of Trinity College . His research focuses on the intersection of program verification, programming language design, and foundational topics like type theory and semantics. His work spans areas such as refinement types, parser design, separation logic for systems software, and the semantics of reactive programming. Notable contributions include the Datafun language for higher-order Datalog and the λert type theory for explicit refinement types. He has also developed foundational frameworks for verifying imperative programs using advanced type systems and logical relations. Key publications include 'Explicit Refinement Types' (ICFP 2023), 'flap: A Deterministic Parser with Fused Lexing' (PLDI 2023), and 'CN: Verifying Systems C Code' (POPL 2023). His work frequently addresses challenges in efficiency, correctness, and modularity for both functional and imperative systems. His awards include Distinguished Paper Awards at PLDI 2019 and POPL 2020. His research integrates theoretical rigor with practical tooling, exemplified by contributions to languages like Coq, Lean, and Haskell.

David Moreno-Mateosمشاهده پروفایل

دانشیار

• Restoration Ecology
• Ecosystem Recovery
• Biodiversity Conservation
• +۴ مورد دیگر

David Moreno-Mateos is Associate Professor in Physical Geography and Tutorial Fellow in Geography at the University of Oxford, joining St Edmund Hall in September 2023 as a Governing Body Fellow. He concurrently holds a part-time Research Professor position at the Basque Center for Climate Change (BC3). His academic journey includes a PhD with honours from the Spanish National Research Council (CSIC) and University of Alcala (2008), followed by postdoctoral fellowships at UC Berkeley, Stanford University, and CNRS France. Key research areas focus on Restoration Ecology and Ecosystem Recovery across biomes from arctic to tropics, examining century-scale responses to anthropogenic disturbances through observational, experimental, and analytical review methodologies. Publications reveal consistent emphasis on recovery debt, ecosystem complexity restoration, and biodiversity offset limitations, with high-impact contributions in Nature journals and PLOS Biology. His work bridges theoretical ecology with practical conservation strategies for degraded ecosystems. Major recognitions include: Ikerbasque Fellowship (Basque Country government) Ramon y Cajal Fellowship (Spanish government) He directs the Ecosystem Recovery Lab, investigating global recovery patterns to inform restoration efficacy. His tutorial fellowship involves undergraduate geography instruction while leading interdisciplinary research on long-term ecological trajectories.

Sarah Howardمشاهده پروفایل

استاد

• Educational Technology
• Learning Analytics
• Data Science in Education
• +۳ مورد دیگر

Sarah Howard is an Honorary Professor at the School of Education, University of Wollongong, and concurrently holds roles such as Visiting Professor at Vrije Universiteit Brussel. Her research focuses on leveraging new technologies and data science to understand classroom practices, teacher change, and technology integration. Key areas include cultural and individual factors influencing teachers' digital technology use, blended learning environments, and automated classroom observation systems. She leads projects like national app use studies in primary schools and data/video mining methods for digital-physical space integration. Her academic roles include supervision of higher-degree research students across multiple institutions. Funding includes ARC grants and internal university schemes exploring rural student potential, generative AI in education, and flexible learning spaces. Her work emphasizes innovative educational technologies, teacher professional development, and systemic educational change. Recent publications span AI in education, blended learning frameworks, and teacher readiness for online instruction. She collaborates internationally, with a focus on integrating theoretical and practical insights to drive educational innovation.

Zoran Budimlićمشاهده پروفایل

دانشیار

• High Performance Computing
• Parallel Computing
• Compiler Optimizations
• +۳ مورد دیگر

Zoran Budimlić is an Instructional Associate Professor in the Department of Computer Science and Engineering at Texas A&M University. He also serves as Director of Undergraduate Studies for Galveston. His roles include teaching and academic leadership in computer science education and high-performance computing. He holds a Ph.D. in Computer Science from Rice University (2001) and a B.S. in Computer Science and Engineering from the University of Belgrade (1994). His research interests focus on high-performance and parallel computing, compiler optimizations, programming languages, runtime systems, and high-level programming models. He emphasizes improving educational practices in computer science through innovative methods and curricula. His recent publications span parallel algorithms, task parallelism integration with MPI, and compiler optimizations for performance. Earlier work includes contributions to Java runtime optimization and static analysis techniques. Zoran Budimlić has no explicitly listed scientific awards or grants in the provided text, but his contributions to parallel computing and compiler design are notable. He advises students in these areas but no names are provided in the text.

• Educational Technology
• Virtual Reality in Education
• Augmented Reality in Education
• +۶ مورد دیگر

Rafael Villena Taranilla is a Professor at Camilo José Cela University (UCJC) and the International University of La Rioja (UNIR), teaching in master's programs on advanced teaching competencies, digital technology in teaching, and inclusive education. He concurrently serves as a primary school teacher, integrating practical classroom experience with academic research in educational technology. His academic credentials include: PhD in Education from the University of Castilla-La Mancha (Outstanding Cum Laude), focusing on Virtual Reality for Social Studies in Primary Education Master's degree in Educational Research and Innovation from the University of Castilla-La Mancha Bachelor's degree in Primary Education with specialization in History, Culture, and Heritage Villena Taranilla's research centers on emerging technologies in education, particularly virtual reality, augmented reality, educational robotics, and artificial intelligence applications for primary education. He investigates their impact on learning outcomes, historical thinking development, and teacher digital competence, with significant contributions to motivation studies and technology acceptance models in educational contexts. His recent publications (2022-2025) demonstrate a concentrated focus on virtual reality for history and social sciences education in primary schools, supported by rigorous meta-analyses and technology acceptance frameworks. The work shows progressive expansion into gamification for historical thinking, augmented reality for geometry instruction, and robotics for computational thinking, reflecting a cohesive interdisciplinary approach bridging education, cognitive science, and technology innovation. His scientific recognition includes: Second prize in the 'Thesis in three minutes' contest (UCLM, 2020) National finalist in the #HiloTesis contest (CRUE Universidades) Villena Taranilla has supervised numerous Master's theses and academic internships across educational innovation programs. He has secured research funding from prestigious entities including FECYT, La Caixa Foundation, and the University of Valencia, while contributing to teacher training initiatives as a digital competence tutor with Castilla-La Mancha's Regional Teacher Training Center. He is an active member of the Labintic research group at the University of Castilla-La Mancha, dedicated to critical ICT integration in teaching. His collaborative research extends to the University of Valencia, where he completed a 2024 research stay and has scheduled another for June-September 2025 under Dr. Pascual D. Diago Nebot's supervision.

Yihan Sunمشاهده پروفایل

استادیار

• Parallel Computing
• Algorithms
• Data Structures
• +۱۲ مورد دیگر

Yihan Sun is an Assistant Professor at the University of California, Riverside (UCR) since January 2020. He earned his Ph.D. in Computer Science from Carnegie Mellon University (CMU) , advised by Guy Blelloch , and holds a Bachelor's degree in Computer Science from Tsinghua University . Research Interests: Yihan Sun focuses on the theory and practice of parallel computing , including Parallel algorithms and data structures Write-efficient algorithms for Non-Volatile Memory (NVM) Computational geometry (range trees, Delaunay triangulations) Graph algorithms (SSSP, SCC, cluster-based BFS) Concurrent and persistent data structures Multi-version concurrency control (MVCC) with garbage collection Applications in databases, transactional systems, and computational biology Recent Research Trends: His work on join-based parallel balanced trees has been foundational, supporting four balancing schemes (AVL, red-black, weight-balanced, treaps) and enabling efficient implementations in graph analytics, spatial queries, and dynamic programming. Recent publications focus on output-sensitive algorithms , scalable graph libraries (PASGAL) , and pedagogical approaches to teaching parallel algorithms. Teaching: He teaches CS260 (Parallel Algorithms) at UCR and has served as a guest lecturer for MIT 6.886 (Algorithm Engineering) and CMU 15-859 (Algorithms in the real world) . He also contributed to algorithm education through a tutorial at the ACM Symposium on Principles and Practice of Parallel Programming (PPoPP 2019) . Labs & Collaborations: Yihan is a core contributor to the PAM (Parallel Augmented Maps) library, which has been integrated into systems like Aspen (graph-streaming) and C-trees . He collaborates with teams at CMU-Parlay , PBBS , and Ligra , with his code available on Github for community feedback.

Christy Thomasمشاهده پروفایل

دانشیار

• Collaborative Leadership
• Professional Learning
• Teacher Education
• +۶ مورد دیگر

Christy Thomas, EdD serves as Dean of the School of Education and Associate Professor at Ambrose University, where she joined as a sessional instructor in Fall 2019, became Assistant Professor in August 2020, and was promoted to Associate Professor in March 2024. She concurrently holds an Adjunct Assistant Professor position at the Werklund School of Education, University of Calgary, where she has taught since 2016. Her academic credentials include: EdD in Education (University of Calgary, 2016) MEd (University of Alberta, 2011) BEd (University of Calgary) Dr. Thomas's research centers on collaborative leadership frameworks and professional learning ecosystems in educational settings. She employs mixed-methods approaches including design-based research and action research to investigate how communities of practice foster teacher development. Her work bridges theoretical scholarship with practical implementation, focusing on creating environments where educators and students can thrive through collaborative risk-taking and supportive structures. Current projects examine digital-age pedagogies and leadership development models that integrate care ethics. Analysis of her 2021-2024 publications reveals strong thematic convergence around educational transformation through collaboration. Key trends include decolonization of teacher education (evident in Métissage leadership frameworks), pandemic-responsive teaching strategies, and technology-mediated social connectedness. Her scholarship consistently addresses systemic challenges in K-12 education while proposing actionable solutions through professional learning communities and leadership development. Dr. Thomas has secured substantial research funding as Principal Investigator (PI) and Co-Investigator (Co-I), including: Alberta Education Research Partnership Program Grant (2025-2027): New Teacher Transition: Early Career Supports (PI) SSHRC Insight Grant (2025-2029): Examining Implementation of Policies Restricting Mobile Devices in K-12 Schools (Co-I) SSHRC IDG (2021-2023): Exploring Online Pedagogies for Social Connectedness (Co-PI) Ambrose Research Fund (2021-2022): Building Faculty Capacity for Online Teaching (PI) She actively translates research into practice through instructional design consulting at Ambrose University and faculty development workshops at both Ambrose and the University of Calgary's Taylor Institute. Her consulting specializes in bridging academic theory with classroom application, particularly in online pedagogies and collaborative leadership models. Dr. Thomas emphasizes creating partnerships between researchers and practitioners to address real-world educational challenges.

Tej Chajedمشاهده پروفایل

استادیار

• Formal verification of systems software
• Concurrent systems verification
• Crash-safe file systems
• +۵ مورد دیگر

Tej Chajed is an Assistant Professor in the Department of Computer Science at the University of Wisconsin-Madison, where he conducts research in formal verification of systems software. His work focuses on building and proving the correctness of critical systems, particularly file systems and concurrent software. Dr. Chajed earned his PhD from MIT in the PDOS group, followed by a one-year postdoc at VMware Research before joining UW-Madison. His academic journey reflects a strong commitment to bridging theoretical formal methods with practical systems implementation. Chajed's research centers on formal verification techniques for systems software, with particular emphasis on concurrent and crash-safe systems . His work aims to eliminate bugs in critical software through mathematical proofs of correctness. Key contributions include DaisyNFS (a verified concurrent file system), the Perennial framework for reasoning about crash safety, and Goose for connecting proofs to Go code. His research spans the intersection of programming languages, operating systems, and formal methods, developing practical tools that bring verification to real-world systems. His recent publications demonstrate a consistent trajectory toward more practical and scalable verification techniques for increasingly complex systems. The research shows progression from foundational verification frameworks to applied work on specific systems like file systems, journaling, and distributed protocols. A notable trend is the focus on making verification more accessible and practical for systems developers, bridging the gap between theoretical formal methods and real-world software engineering. Dr. Chajed serves on numerous program committees including OSDI 2025 PC, PLDI 2024 PC, SySDW 2023 PC, ECOOP 2023 ERC, CPP 2023 PC, POPL 2023 PC, PLDI 2022 PC, POPL 2022 AEC, EuroDW 2021 PC, POPL 2021 AEC, PLDI 2020 AEC, POPL 2020 AEC, and SOSP 2019 AEC, reflecting his standing in the systems and programming languages research community. In teaching, Chajed has developed and instructed courses on systems verification, operating systems, and protocol verification. He previously helped create MIT's 6.826 (Principles of Computer Systems) during his PhD. His passion for technical communication was cultivated during his time as a Communication Fellow in the EECS Communication Lab at MIT, where he continues to offer guidance to students on writing and presentation skills. His research group at UW-Madison focuses on advancing the state of the art in systems verification, with current projects centered around practical verification frameworks for concurrent and crash-safe systems.

Tim Wattsمشاهده پروفایل

مدرس ارشد

• Agriculture
• Veterinary Science
• Sheep Farming
• +۳ مورد دیگر

Tim Watts serves as an Adjunct Senior Lecturer at the Institute of Agriculture, The University of Western Australia, while concurrently managing a 1,497-hectare mixed farming operation in Pingelly, WA. His leadership extends to Chair of the Western Australian Livestock Research Council (2017–present) and membership on the Sheep Industry Leadership Council (2015–present) and Sheep's Back Advisory Board (2010–present). Master of Veterinary Studies, University of Melbourne (1987) Bachelor of Veterinary Medicine and Surgery, Murdoch University (1984) Bachelor of Science (Veterinary Biology), Murdoch University (1982) His research integrates veterinary science with practical agriculture , specializing in oestrogenic pasture impacts on livestock fertility, benchmarking high-performance sheep/cropping systems, and implementing no-till permanent cropping rotations. As a host farmer for national programs like Life-Time Wool and Pastures from Space, he bridges academic research with commercial farming through intensive grazing techniques and data-driven enterprise management. He currently serves as Investigator 02 on the Department of Primary Industries and Regional Development project "Determining the impacts of grazing oestrogenic clovers on cattle fertility" (2022–2025), collaborating with researchers including Vercoe and Blache to assess clover effects on cattle reproduction. Watts contributes to undergraduate education through AGRI2201 in the Agriculture Science major, leveraging his dual expertise as both academic and practicing farmer to deliver industry-relevant instruction grounded in real-world mixed-farming systems.