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Erez PetrankView profile

Professor

• Concurrent Computing
• Programming Languages
• Memory Management
• +5 more

Erez Petrank is a Professor at the Department of Computer Science , Technion - Israel Institute of Technology , where he holds the Andrew and Erna Viterbi Chair. His research focuses on concurrent computing , programming languages , and systems with an emphasis on memory management . Additional interests include parallelism , cryptography , data structures , approximation algorithms , and distributed computing . Research Trends Recent publications highlight his work on safe memory reclamation (ERA Theorem, VBR), lock-free data structures (queues, stacks, B+ Trees), and persistent memory algorithms (NVTraverse, Mirror). These works span concurrent computing , distributed systems , and memory efficiency in multi-threaded environments. Scientific Awards Distinguished Paper Award at Euro-Par 2015 Contact Information Email: erez@cs.technion.ac.il Office: Taub 528, Technion Phone: +972-73-378-4942

• Computer Architecture
• Operating Systems
• Memory Management
• +5 more

Youngjin Kwon is an Associate Professor at the School of Computing, KAIST, and a member of the Computer Architecture and Systems Lab (CASYS). His work bridges systems research with practical applications in memory management, concurrency debugging, and energy-efficient computing. Recipient of Best Paper Awards at ACM SOSP'24, SOSP'21, and USENIX ATC'18 Honored with KAIST's EWON Endowed Chair Professor (2021) and Soo-Young Lee Teaching Innovation Award (2021) Awarded KAIST Breakthrough (2023) and Technology Innovation Award (2023) Research focuses on: Processing-in-Memory (PIM) and DRAM architectures Concurrency bugs in kernel and hypervisor systems Energy-efficient frameworks for large language models Memory disaggregation and tiered memory systems Trusted Execution Environments (TEE) for secure computing SmartNIC offloading and eBPF-based optimizations His recent publications highlight innovations in speculative decoding, memory safety, and system scalability. Awards reflect both technical excellence and pedagogical impact. He actively mentors graduate and undergraduate students in his lab, emphasizing hands-on research in cutting-edge system design.

Christian DietrichView profile

Professor

• Operating Systems
• Real-Time Systems
• Embedded Systems
• +3 more

Christian Dietrich is a Professor at the Technische Universität Hamburg (TUHH) in the Operating System Group (OSG) . His research focuses on Operating Systems , Real-Time Systems , and Embedded Systems , with specific interests in Software Fault Tolerance , Memory Management , and Software Variability . Projects: ParPerOS (Parallel Persistency OS), ATLAS (Adaptable Thread-Level Address Spaces), CLASSY-FI (Cross-Layer Fault Injection), AHA (Automated Hardware Abstraction), CADOS (Configurability-Aware OS) Supervised Theses: 10+ completed theses on topics like io_uring Integration , Heterogeneous Multi-Core , Virtual Memory Primitives , and Fault Injection His recent publications (2022-2024) address Heterogeneous Computing , Virtual Memory Interfaces , and Crash-Consistent Systems . He received awards including USENIX ATC 2017 Best Paper , RTAS 2015 Best Paper , and ISORC 2022 Outstanding Paper .

Armando Solar-LezamaView profile

Associate Professor

• Software Synthesis
• High-Performance Computing
• Information Flow Security
• +3 more

Armando Solar-Lezama is an Associate Professor at the Massachusetts Institute of Technology (MIT) where he leads the Computer Aided Programming Group within CSAIL. His research bridges programming languages, formal methods, and machine learning to advance program synthesis techniques for real-world applications. His primary research focuses on software synthesis with applications spanning high-performance computing, information flow security, and probabilistic programming. He investigates how to automatically generate correct and efficient programs from specifications, with recent work emphasizing neurosymbolic approaches that combine neural networks with symbolic reasoning for complex synthesis tasks. Analysis of his publication trends (2021-2025) reveals a strategic evolution from foundational synthesis algorithms toward practical applications in probabilistic programming and security-critical systems. His work consistently integrates machine learning with formal verification, demonstrating growing emphasis on coarse-to-fine synthesis methods and knowledge compilation techniques for discrete probabilistic models. Award highlights: SIGPLAN Milner Award As leader of MIT's Computer Aided Programming Group, Solar-Lezama mentors graduate researchers and collaborates across institutions. His extensive service as Program Chair for POPL 2025 and committee roles at premier conferences (PLDI, POPL, SPLASH) demonstrates significant community leadership. While specific grant details aren't provided, his sustained publication output in top venues indicates robust funding support. He directs the Computer Aided Programming Group at MIT CSAIL, which develops tools for program synthesis, verification, and analysis. Current projects focus on neurosymbolic programming frameworks, probabilistic program synthesis, and security-aware compilation techniques that integrate information flow control with high-performance computing optimizations.

Val TannenView profile

Professor

• Database Systems
• Logic in Computer Science
• Computational Theory
• +3 more

Val Tannen is a Professor at the University of Pennsylvania in the Department of Computer and Information Science . His research focuses on Databases , Logic , and Computation , with notable contributions to provenance analysis, semiring semantics, and stream processing systems like DBSP. 2023 : Best Paper at VLDB 2023 : Member of Academia Europaea 2013 : Fellow of the ACM His recent work includes incremental computation frameworks for databases, hierarchical query algorithms, and semantic-web integration middleware. He has co-advised PhD students Jesse Comer and Lawrence Dunn . Research groups: Databases and Logic and Computation .

Sam WestrickView profile

Assistant Professor

• Parallel Programming
• Functional Programming
• Compiler Design
• +4 more

Sam Westrick is an Assistant Professor in the Courant Institute of Mathematical Sciences at New York University . Previously, he was a postdoctoral researcher at Carnegie Mellon University , where he also earned his PhD in 2022 . Research Focus : Provably efficient implementations of high-level parallel programming languages, with key contributions in parallel garbage collection , automatic granularity control , and functional language design Teaching : Currently teaching CSCI-GA.3033-121: Programming Parallel Algorithms at NYU; was a TA for CMU courses 15-210 and 15-122 His work includes the development of MaPLe (MPL) , an open-source parallel functional language with performance comparable to C/C++. Notable awards include the SIGPLAN Reynolds Doctoral Dissertation Award (2023) and best/distinguished paper recognitions at QCE'24, POPL'24, and others. Selected Publications explore topics like quantum circuit simulation , cache coherence specialization , and separation logic for disentanglement . Active in conference service as ML Family Workshop chair and PLDI/SPAA committee member. Mentoring : Advises PhD students, master's and undergraduate researchers at NYU and CMU Collaborators : Umut Acar, Guy Blelloch, Stephanie Balzer, and 20+ others

Donald S. FussellView profile

Professor

• Computer Architecture
• Computer Graphics
• Networking
• +3 more

Donald S. Fussell serves as Department Chair and Trammell Crow Regents' Professor in the Department of Computer Sciences at The University of Texas at Austin. He directs the Laboratory for Real-time Graphics and Parallel Systems and maintains affiliations with multiple research centers including the Computer Engineering Research Center and the Institute for Computational Engineering and Sciences. Education: B.A. in Mathematics and Social Science (1973) from Dartmouth College M.S. and Ph.D. in Computer Science (1977, 1980) from University of Texas at Dallas Professor Fussell's research spans computer architecture, computer graphics, networking, digital arts, VLSI systems design, and database concurrency control. His teaching portfolio includes undergraduate and graduate courses in Computer Graphics (CS354, CS384G), Computer Game Technology (CS378), and Computer Systems Architecture (CS352H). His research laboratory focuses on real-time graphics and parallel systems development. Professional Recognition: Recipient of the CNS Rom Rhome Award for leadership Professor Fussell has demonstrated extensive commitment to computer science education through his long-standing teaching career at UT Austin. His work bridges theoretical computer architecture concepts with practical applications in graphics and visualization. He maintains active collaborations across departments including Electrical and Computer Engineering.

Orna GrumbergView profile

Professor

• Computer Science
• Formal Verification
• Model Checking
• +8 more

Orna Grumberg is a Professor at the Computer Science Department , Technion – Israel Institute of Technology . She is a member of the Academia Europaea and an ACM Fellow , recognized for her work in formal verification and model checking. PhD in Computer Science, Technion Honorary Doctorate from Technical University of Munich (2017) Her research focuses on automated verification of software and hardware systems, including model checking , program repair , and abstraction-refinement techniques . She pioneered the CEGAR (Counterexample-guided Abstraction Refinement) framework, which won the CAV award. Her work spans temporal logics , automata on infinite objects , and security vulnerability detection using formal methods. Her publications highlight trends in SAT-based model checking , compositional verification , and multi-valued systems , with applications to UML systems , STE refinement , and distributed model checking . She has co-authored foundational texts such as Model Checking (1999) and its second edition (2018). CAV Award (2000) for CEGAR ACM Fellow Dr.h.c. from Technical University of Munich (2017) Member, Academia Europaea Grumberg has delivered tutorials and lectures at prestigious events like the NATO Summer School Marktoberdorf (2001–2017), covering topics such as 3-valued abstraction , SAT-based model checking , and program repair . She served on the steering committee of the Computer-Aided Verification (CAV) conference and contributed to distributed and parallel model checking algorithms.

Mahmut KandemirView profile

Professor

• Optimizing Compilers
• Runtime Systems
• Embedded Systems
• +5 more

Mahmut Kandemir is a Professor in the Department of Computer Science and Engineering at Pennsylvania State University, where he leads the Microsystems Design Lab. His work bridges compiler design, runtime systems, and hardware-software co-design for energy-efficient computing. Education: B.S. in Computer Engineering, Istanbul Technical University (1988) M.S. in Computer Engineering, Istanbul Technical University (1992) Ph.D. in Computer Science, Syracuse University (1999) Research Interests span optimizing compilers, runtime systems, embedded systems, high-performance storage, power-aware computing, and multi-core architectures. His innovations include compiler-directed techniques to address memory bottlenecks, adaptive runtime systems for dynamic resource allocation, and energy-efficient designs for GPUs and 3D NAND SSDs. Publication Trends highlight interdisciplinary work integrating machine learning into hardware-software co-design. Key focus areas include graph neural networks (KDD, NeurIPS), GPU-optimized molecular docking (J. Chem. Inf. Model.), 3D NAND SSD resource allocation (HPCA, ASPLOS), and energy-efficient VR streaming (ISCA). Awards & Honors: NSF CAREER Award Penn State Premier Research Award IEEE Fellow Best Paper Award at DATE 2007 Top Download from ACM Digital Library (2006) Advising & Grants include mentoring 15 Ph.D. and 5 master’s students, with 32 Ph.D. and 20 master’s graduates. His research is funded by NSF, DOE, DARPA, SRC, Intel, and Microsoft, spanning 11 active projects. Labs & Collaborations include the Microsystems Design Lab at Penn State and partnerships with Argonne National Lab, Microsoft, HP Labs, Intel, and NVIDIA. His work has transitioned into product file systems for large-scale simulations in astrophysics and computational chemistry.

• Computer Engineering
• Computer Science
• Program Synthesis
• +5 more

Xiaokang Qiu is an Associate Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. His research focuses on program synthesis, formal verification, and hardware/software design with an emphasis on automated reasoning and system resilience. He holds a leadership role in advancing techniques for scalable verification of hardware systems and developing efficient program synthesis methods. His research interests include program synthesis, formal methods, hardware design, and algorithm optimization. He explores applications in concurrent systems, network protocols, and safety-critical systems, often integrating machine learning and automated reasoning approaches. Recent work trends show a focus on leveraging large language models for invariant generation, optimizing network and hardware systems through formal methods, and advancing recursive algorithm verification. His publications span topics from concurrent programming to runtime verification frameworks for autonomous systems. Xiaokang Qiu’s contributions include over 20 peer-reviewed articles since 2004, with recent highlights in 2025-2024 addressing cutting-edge challenges in program synthesis and hardware verification. He maintains an active research lab focusing on resilient autonomous systems and compiler optimizations. Office: BHEE 329 | Email: xkqiu@purdue.edu | Website: https://engineering.purdue.edu/~xqiu/

• Data Mining
• High-Performance Computing
• Bioinformatics
• +7 more

Zina Ben Miled is an Associate Professor of Electrical and Computer Engineering at IUPUI and holds a courtesy appointment as Associate Professor of Chemical Engineering at Purdue University's Davidson School of Chemical Engineering. She has been affiliated with Purdue since 1997, holding degrees in Computer Engineering from Purdue (Ph.D., 1997; M.S., 1990) and Oregon State University (B.S., 1988). Her research focuses on data mining, high-performance computing, bioinformatics, and cheminformatics. Notable contributions include developing integrated systems for biological and chemical data (BACIIS), blockchain-based supply chain solutions, and machine learning models for water demand prediction and health surveillance. She has also pioneered educational models for digital system design courses. Her awards include the NSF Career Award (2002), Abraham Max Outstanding Research Award (2001), and Violet Haas Outstanding Academic Women Award (1996). She is an IEEE Senior Member and has led numerous industry-funded projects with Eli Lilly and the Office of Naval Research. Grants: Over 10 industry and federal grants as PI/Co-PI, including NSF, ONR, and Eli Lilly initiatives. Labs/Teams: Leads interdisciplinary teams in Purdue’s Chemical Engineering and IUPUI’s ECE departments, focusing on database systems, blockchain, and health informatics.

T N. VijaykumarView profile

Professor

• Computer Architecture
• Machine Learning
• High-Performance Computing
• +7 more

T. N. Vijaykumar is a Professor of Electrical and Computer Engineering at Purdue University, with a courtesy appointment in Computer Science. He joined the university in 2003. His research focuses on computer architecture, machine learning acceleration, high-performance computing, and hardware-software co-design. He holds degrees from Birla Institute of Technology and Science (BE, MSc) and the University of Wisconsin (MS, PhD in Computer Science). Education: B.E. (Hons), Electrical and Electronics Engineering, Birla Institute of Technology and Science (1990) M.Sc. (Tech), Computer Science, Birla Institute of Technology and Science (1992) M.S. and Ph.D., Computer Science, University of Wisconsin (1997) His research interests span GPU architectures , memory systems , neural network acceleration , and secure computing . Recent work includes optimizing sparse tensor processing, secure speculative execution, and distributed training frameworks for mobile robotics. Publications highlight contributions to GPU kernel concurrency, neural radiance fields, and memory consistency verification. His work often bridges hardware design and software efficiency, with applications in data centers and edge computing. Notable grants include projects like QED (scalable hardware memory verification) and ESPIM (sparse processing-in-memory for ML inference). He has also contributed to frameworks like Disorf for real-time rendering in robotics. Labs/Teams: Active involvement in Purdue’s Computer Science and ECE departments, with collaborations on AI hardware and systems research.

Eddie KohlerView profile

Professor

• Computer Science
• Systems
• Networks
• +5 more

Eddie Kohler is the Microsoft Professor of Computer Science at Harvard University's Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), where he also serves as Director of Undergraduate Studies in Computer Science. His research focuses on high-performance systems, networks, and databases with an emphasis on concurrency control, data privacy, and scalable software design for multicore processors. He has contributed to foundational work in transactional systems, web application backends (e.g., Noria), and privacy-preserving technologies (e.g., Edna). His research spans theoretical frameworks like the Scalable Commutativity Rule and practical implementations such as the Alto lightweight virtualization system. Kohler's work often bridges theory and practice, addressing challenges in distributed systems, sensor networks, and regulatory compliance (e.g., GDPR). Notable contributions include innovations in in-memory database concurrency, optimistic transaction processing, and network congestion control protocols (e.g., TFRC-SP). His projects frequently emphasize system correctness through formal verification and empirical evaluation. His articles reflect a trajectory from foundational concurrency research to applied systems engineering, with recent focus on privacy in web applications and optimizing modern multicore architectures. No specific grants or advisees are listed in the provided information. Kohler leads research initiatives in scalable systems and maintains active collaboration with industry through his academic leadership roles.

Umut AcarView profile

Associate Professor

• Programming Languages
• Parallel Computing
• Algorithms and Complexity
• +3 more

Umut Acar is an Associate Professor in the Computer Science Department at Carnegie Mellon University. His research focuses on programming languages, parallel computing, and algorithms, with an emphasis on raising the level of abstraction for software development while ensuring efficiency. He leads efforts in dynamic and incremental computation, parallelism optimization, and quantum computing systems. His work spans theoretical foundations and practical implementations, including systems like Atlas for quantum circuit simulation and Atomique for neutral atom quantum compilers. He advises students on advanced topics such as quantum algorithms and parallel programming models. Notable awards include Best Paper and Distinguished Paper recognitions at top conferences like SC and ISCA. Education: PhD in Computer Science (University of Chicago, 2005) Key Projects: Development of self-adjusting computation frameworks, parallel algorithms for dynamic data, and quantum compiler optimization tools. Grants: Collaborative research grants from NSF for parallelism and quantum computing initiatives. Dr. Acar’s contributions bridge theory and practice, enabling scalable software systems for modern hardware architectures and emerging technologies like quantum computing.

Seth GoldsteinView profile

Associate Professor

• Programming Languages
• Systems
• Computer Architecture
• +9 more

Seth Goldstein is an Associate Professor in the Computer Science Department at Carnegie Mellon University's School of Computer Science. His research focuses on ensembles (massively scalable systems), distributed systems, reconfigurable computing, and programmable matter (Claytronics). He leads projects like BoLT (a decentralized lending platform) and Phoenix (computing without traditional processors). He has advised numerous graduate students and teaches courses including Compiler Design, Computer Architecture, and Cloud Computing. Research Interests : Goldstein explores systems with massive interacting components, such as molecular-scale devices, modular robotics, and economic systems. His work spans compilers (e.g., register allocation optimizations), time synchronization protocols for embedded systems, and algorithms for self-reconfiguring robots. Recent projects include BlockGraph (a secure distributed ledger) and peer code review methodologies. Key Contributions : Goldstein's work on Claytronics pioneered programmable matter, enabling shape-shifting materials. His BoLT platform addresses lending market inefficiencies using blockchain principles. He has also developed algorithms for modular robot coordination and energy-efficient self-reconfiguration. Labs/Teams : Goldstein directs research in the CMU Robotics Institute and collaborates with interdisciplinary teams on projects like the PipeRench and Phoenix architectures. His lab explores intersections between nanotechnology, distributed systems, and societal applications like new monetary systems.