جستجوی استاد راهنمای دانشگاهی

Mike Kirbyمشاهده پروفایل

استاد

• Scientific Computing
• Physics-Informed Machine Learning
• Computational Science and Engineering
• +۴ مورد دیگر

Mike Kirby is a Professor at the Kahlert School of Computing, University of Utah. He also holds adjunct professorships in the Department of Bioengineering and the Department of Mathematics. His current roles include leadership in scientific computing and informatics initiatives, including former directorships of the Utah Informatics Initiative (2019-2023) and the Multi-Scale Multidisciplinary Modeling of Electronic Materials (MSME) Collaborative Research Alliance (2016-2022). He has extensive experience in strategic research initiatives, including serving as Assistant Vice President for Research (2024-2025). Education: Dr. Kirby earned a PhD in Applied Mathematics (2002) and MS in Computer Science (2001) from Brown University, and a BS in Applied Mathematics and Computer Science from Florida State University (1997). Research Interests: Focus on large-scale scientific computing, physics-informed machine learning, computational science and engineering, high-order numerical methods, and visualization. His work bridges applied mathematics and computer science to address real-world engineering challenges. Publications: Over 150 peer-reviewed articles, including high-impact contributions in journals like Journal of Computational Physics and SIAM Journal on Scientific Computing . Recent work emphasizes machine learning for differential equations, topology optimization under uncertainty, and multi-fidelity modeling. Awards: Recognized for leadership in computational science and informatics, including contributions to University of Utah’s Clery Compliance Program. Advising & Grants: Supervised over 50 graduate students and postdocs. Secured funding from NSF, DOE, and industry partnerships, totaling millions in research grants. Active in interdisciplinary collaborations across engineering, materials science, and medicine. Labs/Teams: Scientific Computing and Imaging (SCI) Institute, Utah Informatics Initiative, and the Center for Multiscale Modeling of Electronic Materials (MSME).

• Distributed Systems
• High Performance Computing
• Fault Tolerance
• +۴ مورد دیگر

Aishwarya Ganesan is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign. Her research focuses on distributed systems, storage systems, and fault tolerance mechanisms, with emphasis on high-performance computing and datacenter infrastructure. She leads projects addressing challenges in replicated storage, consensus protocols, and system resilience. Her work explores fault tolerance in disaggregated datacenters, log abstractions for low-latency applications, and novel replication strategies for modern storage systems. She has developed frameworks like LazyLog and IONIA to improve system efficiency and reliability. Her research also extends to automatic reliability testing for cluster management controllers and analyzing distributed storage vulnerabilities. Key contributions include demonstrating how redundancy alone does not guarantee fault tolerance, and proposing consistency-aware durability mechanisms for storage systems. She received the NSF CAREER Award in 2024 for her research on storage-aware fault tolerance. Her work spans 21 peer-reviewed publications, with notable contributions in conferences like SOSP, EuroSys, and FAST. Current projects investigate fault tolerance in emerging memory technologies and system recovery protocols for consensus-based storage.

Gene Coopermanمشاهده پروفایل

استاد

• High-Performance Computing
• Computer Systems
• Transparent Checkpointing
• +۴ مورد دیگر

Gene Cooperman is a Professor at the Khoury College of Computer Sciences at Northeastern University, with an affiliation in the College of Engineering. His research focuses on high-performance computing (HPC), transparent checkpoint-restart systems, and model checking. He leads the High Performance Computing Laboratory, where he explores checkpointing technologies like DMTCP, MANA for MPI, and CRAC for CUDA, aiming to enhance HPC workflows on supercomputers such as NERSC's Perlmutter. His work bridges distributed computing, parallel algorithms, and system software to address challenges in fault tolerance, scalability, and resource management. Cooperman has advised 10 PhD students and co-authored over 125 refereed publications, contributing to projects like Geant4-MultiThreaded and Roomy for disk-based computation. His teaching includes courses on computer systems and HPC seminars. Education: Background in computational algebra and parallel computing, transitioning to HPC systems and checkpointing. Research Themes: Transparent checkpointing, MPI agnostic solutions, CUDA integration, and HPC resource optimization. Recent articles emphasize MPI checkpointing, reversible debugging (FReD), and CUDA support, reflecting trends in distributed and GPU-accelerated systems. His grants include NSF, NERSC/DOE, and MemVerge funding. Cooperman collaborates with institutions like CERN and NERSC, advancing applications in particle physics simulations and supercomputing. Current students include Aayushi Gautam, Jiajun Cao, Rohan Garg, and Twinkle Jain.

Stanislaw Jareckiمشاهده پروفایل

دانشیار

• Cryptography
• Cybersecurity
• Distributed Systems
• +۳ مورد دیگر

Stanislaw Jarecki is an Associate Professor of Computer Science at the Donald Bren School of Information and Computer Sciences (ICS) at the University of California, Irvine (UCI). He joined UCI in 2003 after earning his Ph.D. in Computer Science from MIT in 2001 under Prof. Shafi Goldwasser. His research focuses on applied and distributed cryptography, with significant contributions to threshold cryptography, secure computation, and password-authenticated key exchange (PAKE) protocols such as OPAQUE, which secures 2 billion WhatsApp users. He also worked at Intertrust’s StarLab and Stanford’s applied cryptography group under Prof. Dan Boneh. Education: Ph.D., Massachusetts Institute of Technology, 2001. Research Interests: Distributed cryptography, secure multi-party computation, privacy-preserving protocols, threshold security, blockchain applications, and efficient cryptographic primitives. His work emphasizes practical solutions for real-world systems, including protocols resilient to server compromises and scalable encryption methods. Awards: 2023 IACR Fellow for contributions to distributed cryptography and efficient secure computation. Advising and Grants: Jarecki’s research has been supported by grants including NSF SaTC programs. He advises students on cryptographic protocol design and security mechanisms. His work on OPAQUE and CHIC protocols exemplifies his focus on bridging theoretical cryptography with practical implementation. Labs/Teams: Leads a research group focused on applied cryptography and security within ICS at UCI, collaborating on projects like secure computation, privacy-preserving data processing, and cryptographic protocol development.

Clyde Kruskalمشاهده پروفایل

دانشیار

• Parallel Computing
• Algorithms
• Computer Architecture
• +۳ مورد دیگر

Clyde Kruskal is an Associate Professor in the Department of Computer Science at the University of Maryland, College Park. His research focuses on parallel architectures, models, and algorithms. He earned a Ph.D. from New York University in 1981 and a bachelor’s degree from Brandeis University in 1976. His work includes foundational contributions to parallel computing, such as the read–modify–write concept in distributed systems. Kruskal’s research spans topics like interconnection networks, synchronization mechanisms, and algorithm design for parallel systems. Education: Bachelor’s Degree: Brandeis University, 1976 Master’s Degree: New York University (Courant Institute), 1978 Ph.D.: New York University (Courant Institute), 1981 Research Interests: Parallel computing architectures, parallel algorithms design, multiprocessor synchronization, interconnection networks, and computational geometry problems like graph coloring and visibility analysis. His work emphasizes theoretical foundations and practical implementations in parallel systems. Notable Contributions: Kruskal co-authored the book Problems With A Point: Exploring Math And Computer Science (2019), and his research includes foundational papers on parallel prefix operations, sparse matrix algorithms, and synchronization protocols. His publications span over three decades, reflecting sustained contributions to parallel computing theory and practice. Advising & Outreach: He has mentored students through programs like the Summer Combinatorial Algorithms REU at UMD, fostering undergraduate research in algorithm design and parallel computing.

Tianzheng Wangمشاهده پروفایل

دانشیار

• Database Systems
• Operating Systems
• Parallel Programming
• +۵ مورد دیگر

Tianzheng Wang is an Associate Professor and Director of the Dual-Degree and Partnerships Programs at the School of Computing Science, Simon Fraser University. His research focuses on database systems, transaction processing, parallel and distributed computing, and embedded systems. He holds a PhD in Computer Science from the University of Toronto (2017) and a BSc in Computing from Hong Kong Polytechnic University (2012). Research Interests: Database systems optimized for modern hardware, parallel programming, synchronization, and distributed architectures. His work emphasizes high-performance transaction processing and efficient indexing techniques, with applications in cloud and embedded systems. Awards: ACM SIGMOD Best Paper Award (2025), IEEE TCSC Early Career Award (2019), and multiple distinguished reviewing recognitions (SIGMOD/VLDB 2021-2024). His research has been integrated into systems like Amazon Redshift and DragonflyDB. Teaching: Leads courses such as CMPT 454 (Database Systems II), CMPT 300 (Operating Systems), and special topics in databases. Actively mentors graduate and undergraduate students in research projects. Labs & Collaborations: Heads the Data-Intensive Systems Lab, part of SFU's Data Science and Systems groups. Collaborates on tools like PiBench for persistent memory benchmarking and contributes to open-source projects like CoroBase and Tabular.

Jeremy Gibbonsمشاهده پروفایل

استاد

• Functional Programming
• Programming Languages
• Software Engineering
• +۳ مورد دیگر

Jeremy Gibbons is a Professor of Computing at the University of Oxford, affiliated with the Department of Computer Science within the Faculty of Computer Science. He serves as Director of the Professional Programmes, overseeing part-time postgraduate degrees in Software Engineering. His roles include Chair of the Faculty of Computer Science (2012–2016), Director of the Software Engineering Programme, and Fellow of Kellogg College. Gibbons' research focuses on programming methodologies, particularly functional and object-oriented languages, with an emphasis on program calculation, design patterns, and bidirectional transformations. He leads the Algebra of Programming research group and is Editor-in-Chief of the Journal of Functional Programming and The Art, Science, and Engineering of Programming . Education includes a D.Phil. from Oxford University. His work spans formal methods, domain-specific modeling for clinical trials (e.g., CancerGrid project), and semantic frameworks for software systems. He has advised numerous students and contributed to open-access initiatives in publishing. Key collaborations include roles in ACM SIGPLAN and IFIP Working Groups 2.1 and 2.11. Research interests emphasize foundational aspects like profunctor optics, categorical programming, and algorithm design. Notable projects include datatype-generic programming and metadata-driven engineering for clinical trials. His work bridges theoretical computer science with practical applications in software architecture and system design.

• Algorithms
• Game Theory
• Automata Theory
• +۷ مورد دیگر

Marcin Jurdzinski is an Associate Professor (Reader) in the Department of Computer Science at the University of Warwick , UK. He has been a faculty member since 2004 and is a core member of the Foundations of Computer Science and Discrete Mathematics and its Applications research groups. University: University of Warwick School: Faculty of Science Department: Department of Computer Science Position: Associate Professor (Reader) Email: Marcin.Jurdzinski@warwick.ac.uk Office: CS2.19 His research lies at the intersection of algorithms, game theory, automata, and logic , with a strong emphasis on formal verification , model checking , and theoretical computer science . He is best known for his foundational work on parity games , including the development of small progress measures and discrete strategy improvement algorithms. The recent publications reveal a consistent focus on computational complexity in games and verification. Key themes include stochastic games, timed automata, bisimilarity, and quantitative analysis . His work often bridges theoretical insights with practical verification challenges, especially in real-time and probabilistic systems. He has supervised several PhD students and hosted postdoctoral researchers such as Laure Daviaud and Alexander Kozachinskiy. He has led EPSRC-funded projects including Solving Parity Games in Theory and Practice and Counter Automata: Verification and Synthesis . PhD Students: Aditya Prakash, Thejaswini K. S., Michail Fasoulakis, John Fearnley, Michal Rutkowski, Ashutosh Trivedi Postdocs: Laure Daviaud, Alexander Kozachinskiy He is actively involved in the academic community, serving on the steering committee of the Highlights of Logic, Games and Automata conference and on program committees for major venues such as CONCUR, ICALP, and LICS. He has also organized workshops including FORMATS and ICALP co-located events.

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.

Jürgen Bergesمشاهده پروفایل

استاد

• Quantum Field Theory
• Non-equilibrium Dynamics
• Heavy-Ion Collisions
• +۲ مورد دیگر

Jürgen Berges is a full Professor of Theoretical Physics at Heidelberg University's Faculty of Physics and Astronomy, holding the Chair of Theoretical Physics since 2011. He concurrently serves as an ExtreMe Matter Institute (EMMI) Professor at GSI Helmholtzzentrum for Heavy Ion Research in Darmstadt and acts as Spokesperson for the Steering Board and Principal Investigator in multiple projects within the STRUCTURES Cluster of Excellence. Education includes Habilitation (2003), Doctorate (1997), and Diploma (1994) from Heidelberg University, plus Intermediate Diploma (1990) from Osnabrück University. Research Interests focus on quantum field theory applications in non-equilibrium dynamics , particularly thermalisation phenomena in heavy-ion collisions , nonthermal fixed points , and quantum field simulators . His work integrates topological data analysis for quantum systems within the STRUCTURES Cluster of Excellence (Quantum Structure and Dynamics). Scientific Awards : Karl-Freudenberg Prize (2004) Landesgraduiertenförderung Fellowship (1995-1997) Leadership & Grants : Served as Department Chair (2021-2023), Deputy Chair (2019-2021), and Spokesperson for CRC 1225 (ISOQUANT). Currently Principal Investigator in STRUCTURES Cluster projects A01 (Thermalisation dynamics), B03 (Nonthermal fixed points), and B04 (Quantum field simulators), with prior DOE review panel membership (2018). Labs & Teams : Leads theoretical research groups within Heidelberg's Institute for Theoretical Physics, focusing on infrared phenomena in quantum fields and quantum simulator development through ISOQUANT and STRUCTURES collaborations.

• Programming Languages
• Formal Methods
• Software Engineering
• +۴ مورد دیگر

Alexander Summers is an Associate Professor at the Department of Computer Science , University of British Columbia . He joined UBC in March 2020 after serving as a Senior Researcher (Oberassistent) at ETH Zurich from 2014-2020. His research bridges Programming Languages , Formal Methods , and Software Engineering , with a focus on automated verification tools for heap-based and concurrent programs. MSc Joint Mathematics and Computer Science, Imperial College London (2004) PhD Computer Science, Imperial College London (2009) Postdoc, ETH Zurich (2009-2014) Summers leads the Prusti Project , developing deductive verification tools for Rust, and contributes to the Viper Project for intermediate verification languages. His work addresses challenges in: Memory safety and concurrency verification Ownership models and aliasing control Automated reasoning with SMT solvers Resource-oriented programming specifications Debugging verification condition quantifiers Formal validation of verification infrastructure His research has been recognized with a Amazon Research Award and ACM SIGPLAN Distinguished Paper Awards . He teaches courses like Advanced Software Engineering and Program Verifiers and Program Verification , and supervises graduate students in formal verification and Rust-related research.

Henry F. (Hank) Korthمشاهده پروفایل

استاد

• Database Systems
• Blockchain Systems
• Distributed Systems
• +۷ مورد دیگر

Henry F. (Hank) Korth is a Professor of Computer Science and Engineering at Lehigh University, with a courtesy appointment in the Department of Decision and Technology Analytics in the College of Business. He serves as Director of the Blockchain Lab in the Center for Financial Services and Co-Director of the Computer Science and Business Program. Korth is a Fellow of the ACM and IEEE, and a recipient of the VLDB 10-Year Award and Bell Labs President's Silver Award for contributions to database technologies. PhD in Computer Science from Princeton University MA, MSE in Computer Science from Princeton University BA in Mathematics from Williams College Korth's research spans database systems, blockchain systems, distributed systems, and real-time systems. He has pioneered transaction management in parallel and distributed systems, query processing, and the impact of modern computing architectures on database performance. His recent work focuses on blockchain applications in enterprise databases, including acceleration of zero-knowledge proofs, benchmarking frameworks, central-bank digital currencies, and private-yet-provable accounting systems. His contributions are rooted in both theoretical advancements and practical implementations, such as the QTM™ aggregation engine and the DataBlitz™ main-memory storage manager. Scientific awards include: ACM Fellow IEEE Fellow 10-Year Award at the VLDB Conference Bell Labs President's Silver Award Korth actively supervises research within the Blockchain Lab and is affiliated with the Scalable Software Systems Research Group at Lehigh. His scholarly output reflects a deep engagement with blockchain benchmarking, concurrency control, verifiable databases, and the evolution of database systems in response to technological shifts.

• Machine Learning
• Computer Vision
• Medical Image Analysis
• +۷ مورد دیگر

Professor Arcot Sowmya is a distinguished academic at the University of New South Wales, serving as Professor in the School of Computer Science and Engineering. With a strong background in both computer science and mathematics, she has established herself as a leading researcher in machine learning and computer vision applications, particularly in medical imaging and diagnostics. Dr. Sowmya earned her PhD in Computer Science from the Indian Institute of Technology, Bombay, along with an MTech in Computer Science, MSc in Mathematics, and BSc in Mathematics from the same institution. Her academic journey has positioned her at the intersection of theoretical computer science and practical medical applications. Her research interests span multiple domains with a primary focus on Machine Learning for Computer Vision . She has made significant contributions to learning object models, feature extraction, segmentation, and recognition techniques. Her work extends into medical image analysis, computer-aided diagnostics, high-resolution remote sensing, and biomedical informatics. More recently, she has applied similar techniques to social sciences domains, developing improved forecasting models for genocide and politicide. Her earlier work also includes contributions to real-time, concurrent, and embedded systems. Analyzing her recent publications reveals a strong trend toward medical applications of computer vision and deep learning. Her work spans from OCT-based glaucoma diagnosis to tumor segmentation, lung disease detection, and breast cancer prognosis. She has successfully bridged computer science with clinical medicine, developing practical tools for disease diagnosis and prediction that incorporate explainable AI approaches. Professor Sowmya's collaborative approach is evident in her extensive publication record across multiple journals and conferences. She has worked with researchers from diverse fields including ophthalmology, oncology, neurology, and public health, demonstrating the interdisciplinary nature of her research. Her laboratory work focuses on developing robust deep learning architectures for medical image analysis, with particular attention to segmentation networks, transformer models, and multimodal data fusion techniques. Her team has developed specialized networks for lung segmentation, tumor detection, and disease classification that address specific challenges in medical imaging.

• Business Analytics
• AI
• Operations Management
• +۵ مورد دیگر

Tingliang Huang holds concurrent roles as the Amazon Distinguished Professor of Business Analytics at the University of Tennessee's Haslam College of Business and Honorary Professor at the UCL School of Management. He earned his PhD from Northwestern University's Kellogg School of Management. His research focuses on business analytics, AI-driven strategies, supply chain optimization, and behavioral operations, with notable contributions to Marketing Science, Management Science, and Production and Operations Management. Affiliations: Amazon Distinguished Professor, Haslam College of Business, University of Tennessee Honorary Professor, UCL School of Management Former tenured Associate Professor at Boston College's Carroll School of Management Education: PhD in Management, Kellogg School of Management, Northwestern University (2011) M.S. and B.S. from University of Science and Technology of China (USTC) Research Interests: Huang’s work bridges analytics and operations, exploring topics like opaque selling, bounded rationality in consumer decisions, supply chain dynamics, and sustainable operations. He has pioneered frameworks for probabilistic selling and dynamic pricing under uncertainty. His interdisciplinary approach integrates behavioral economics and big data analytics. Publications: Over 20 peer-reviewed articles in top journals, emphasizing service systems, supply chain strategy, and marketing-operations interfaces. Recent work explores AI's societal impacts and algorithmic targeting in vertical markets. Awards: 2025 Vallett Family Outstanding Researcher Award 2018 POMS Wickham Skinner Early Career Award 2015 POMS Best Paper Award Multiple Meritorious Service Awards (M&SOM, Management Science) Editorial Roles: Senior Editor at Production and Operations Management, Associate Editor at Manufacturing & Service Operations Management, Decision Sciences, and others. He also serves on editorial review boards for leading journals. Teaching & Mentorship: Award-winning educator recognized as Carroll School Teaching Star (2021). Advises doctoral students at UCL, UTK, and Chinese institutions, with placements at top schools like George Mason University and USTC. Labs & Teams: Leads the Business Analytics PhD Program at UTK and collaborates on AI ethics research through cross-institutional projects.

• Homomorphic Encryption
• Big Data Analysis
• Database Systems
• +۶ مورد دیگر

Hayato Yamana serves as Professor at Waseda University's Faculty of Science and Engineering and concurrently holds the position of Vice President for IT Promotion and Chief Information Officer since October 2020. His academic journey began with a Dr. Eng. degree from Waseda University in 1993, followed by positions at the Electrotechnical Laboratory of MITI, before joining Waseda University as Associate Professor in 2000 and becoming full Professor in 2005. He has held significant leadership roles including Director of the Database Society of Japan and the Information Processing Society of Japan, as well as Vice Chair of IEICE's Information and Communication Society. Waseda University, Faculty of Science and Engineering (2005-Present) National Institute of Informatics, Visiting Professor (2005-Present) Waseda University, Vice President for IT Promotion (2020-Present) Deputy Chief Information Officer (2015-2020) His research spans homomorphic encryption, big data analysis, and computer architecture, with notable contributions in privacy-preserving computation, recommender systems, and secure data processing. His work bridges theoretical cryptography with practical applications in smart cities, healthcare, and e-commerce security. Recent publications demonstrate strong focus on accelerating homomorphic encryption operations, improving recommendation system diversity, and developing novel authentication mechanisms. Analysis of his 15 most recent publications reveals consistent emphasis on privacy-preserving technologies (particularly homomorphic encryption applications), innovative recommender system architectures, and biometric security solutions. His research group produces highly cited work at the intersection of cryptography, machine learning, and systems security, with practical implementations in real-world scenarios including smart grids, e-commerce, and healthcare. Fellow, Information Processing Society of Japan (IPSJ), 2020 Golden Core Award, IEEE Computer Society, 2018 Fellow, Institute of Electronics, Information and Communication Engineers (IEICE), 2018 IBM Faculty Award, 2009 Multiple Best Paper Awards from IEICE, IPSJ, and ITE Yamana has secured substantial research funding for projects in homomorphic encryption, smart city infrastructure, and privacy-preserving systems. His leadership extends to advising numerous doctoral students and directing major research initiatives including the Smart Systems and Services Innovative Professional Education Program. He maintains active collaborations with industry partners through projects involving secure computation and data analytics. His research group operates at the forefront of secure computing, with specialized laboratories focused on homomorphic encryption acceleration, privacy-preserving machine learning, and secure mobile authentication. The team actively develops practical implementations of cryptographic protocols for real-world applications in healthcare, finance, and smart city infrastructure, bridging theoretical cryptography with deployable security solutions.