جست‌وجوی استاد و پژوهشگر

John Wickersonمشاهده پروفایل

دانشیار

• Computer Hardware
• Electrical and Electronic Engineering
• Computer Software
• +۷ مورد دیگر

Dr. John Wickerson is an Associate Professor in the Circuits and Systems group at the Department of Electrical and Electronic Engineering, Imperial College London. His research focuses on improving the reliability of high-performance computing through formal methods, with contributions to high-level synthesis, memory models, and concurrency verification. He holds leadership roles including Course Director for the Electrical and Information Engineering degree and Deputy Tutor for PhD students. Research Interests: Formal Verification of Hardware/Software Systems High-Level Synthesis (HLS) and FPGA Compilation Weak Memory Models and Concurrency Semantics Fuzz Testing for Hardware Tools Compiler Optimization and Correctness Digit Elision and Arbitrary-Precision Arithmetic Notable Achievements: Best Paper Award at EuroSys 2024 (database isolation validation) Pioneered formal methods for HLS tools (e.g., QuteFuzz, C4) Co-developed the C4 C compiler concurrency checker Published over 60 peer-reviewed papers across top venues (ASPLOS, PLDI, FPGA) Lab/Team: Part of the Circuits and Systems group at Imperial College, collaborating with industry partners like Kaihong Yann and ARM.

• Reconfigurable Computing
• FPGA Accelerators
• Parallel and Distributed Computing
• +۳ مورد دیگر

Viktor Prasanna is the Charles Lee Powell Chair in Engineering and Professor of Electrical and Computer Engineering and Computer Science at the University of Southern California. He holds courtesy appointments in Computer Science and leads the Center for Energy Informatics, focusing on interdisciplinary research linking energy technologies, computer science, and engineering. Education: BE in Electronics (Bangalore University), ME (Indian Institute of Science), PhD in Computer Science (Pennsylvania State University) His research spans reconfigurable computing, FPGA accelerators, parallel and distributed systems, and big data applications. He has pioneered high-performance architectures and algorithms using FPGAs, impacting domains like networking, security, HPC, and machine learning. Prasanna has published over 600 papers, received 22 best paper awards, and secured >$50M in grants. His work emphasizes energy-efficient computing, with recent grants totaling $12.9M (2016–2021). His h-index is 73, with 23,454 total citations. Scientific Awards: IEEE Fellow, ACM Fellow, AAAS Fellow, W. Wallace McDowell Award, multiple Distinguished Alumnus Awards He has advised over 70 doctoral students and led major centers including CiSoft (Big Data in oilfield tech) and CAST. His editorial roles include Editor-in-Chief of IEEE Transactions on Computers and Journal of Parallel and Distributed Computing.

Rajeev Balasubramonianمشاهده پروفایل

استاد

• Computer Architecture
• Memory Systems
• DRAM/NVM Technologies
• +۷ مورد دیگر

Rajeev Balasubramonian is a Professor and Associate Director at the School of Computing, University of Utah. He specializes in computer architecture, with a focus on memory systems, emerging technologies, and energy-efficient computing. His research addresses challenges in DRAM/NVM architectures, security, and acceleration for big data and machine learning workloads. Education: PhD in Computer Science (University of Rochester, 2003), M.S. (University of Rochester, 2000), B.Tech in Computer Science (IIT Bombay, 1998). Research Interests: Memory reliability, near-data processing, cache hierarchies, transactional memory, and hardware-software co-design for emerging technologies. He has led projects on crossbar accelerators, secure memory systems, and resistive memory architectures. Recent Trends in Publications: Focus on encrypted inference (Hyena), data prefetching (PATHFINDER), and neuromorphic computing (SpinalFlow). His work bridges hardware and software, emphasizing practical acceleration and security solutions. Awards: IEEE Fellow (2021), Google Faculty Awards (2019/2020), Intel Research Award (2017), and multiple best paper awards (ISCA, ISPASS, PACT). Grants & Students: Over $4M in NSF/industry funding. Advised 15+ PhD students (e.g., Ali Shafiee, Karl Taht) and currently mentors researchers in resistive memory and security accelerators. His lab includes teams like Utah Arch Research Group. Labs & Teams: Leads the Utah Arch Research Group , organizing workshops on near-data processing and memory systems (e.g., ISCA, HPCA).

Alexandros Daglisمشاهده پروفایل

دانشیار

• Rack-Scale Computing
• Network-Compute Integration
• Low-Latency Datacenter Architecture
• +۵ مورد دیگر

Alexandros Daglis is an Associate Professor of Computer Science at the Georgia Institute of Technology, with an adjunct appointment in the School of Electrical and Computer Engineering. His research focuses on blurring boundaries between network and compute for high-performance, scalable microsecond-scale services in datacenters, particularly through network endpoints and memory-centric computing. Primary Affiliation: Georgia Tech College of Computing, School of Computer Science Adjunct Affiliation: School of Electrical and Computer Engineering Key research areas include: Rack-scale computing and network-compute co-design CXL-based memory systems Low-latency datacenter architectures Transactional memory and concurrency control Edge-cloud continuum and geo-distributed infrastructures He has received prestigious awards including the NSF CAREER Award, Google Faculty Research Award, and Georgia Tech's Outstanding Junior Faculty Teaching Award. His students include Marina Vemmou (network-compute co-design), Albert Cho (memory system design), and Peidi Song (microsecond-scale scheduling). Grants: NSF, IARPA, Intel, Samsung Teaching: High Performance Computer Architecture, Systems and Networks, Datacenter Design

Anomadarshi Baruaمشاهده پروفایل

استادیار

• System Design and Security
• Healthcare Assistive Systems
• Industrial Control Systems (ICS)
• +۵ مورد دیگر

Anomadarshi Barua is an Assistant Professor in the Department of Cyber Security Engineering at George Mason University, leading the System Design and Security research group. His work spans hardware-software co-design for securing cyber-physical systems (CPS), robotics, and sensors. Prior Affiliation: PhD from University of California, Irvine (2023) Industry Experience: Intel Corporation, Solidigm, Nordic Semiconductor, IDEAS Research Themes: Focuses on multimodal system security (audio, visual, electromagnetic data), analog-digital signal integrity, and quantum-inspired defenses in CPS. Key applications include healthcare systems, smart grids, and industrial control systems (ICS). Recent ACSAC 2024 paper acceptance Best Paper Award at ACSAC 2022 NSF panel reviewer (2024) Labs & Collaborations: Collaborates with University of Louisville on robotics and works on Commonwealth-funded UG research (2024). Publications in ACM CCS, USENIX, CHES, and IEEE Transactions (TDSC, TIFS).

• Emerging memory and storage technologies
• Embedded systems
• Cyber-Physical Systems (CPS)
• +۵ مورد دیگر

Dr. Yiran Chen is the John Cocke Distinguished Professor at Duke University's Department of Electrical and Computer Engineering, leading the NSF AI Institute for Edge Computing (Athena) and the Duke Center for Computational Evolutionary Intelligence (DCEI). A global leader in neuromorphic computing, emerging memory systems, and edge AI, he holds prestigious roles including IEEE Fellow and Editor-in-Chief of IEEE Transactions on Circuits and Systems for AI. His research spans machine learning accelerators, security-hardened hardware, and co-design of EDA tools with LLMs. With over 700 publications and 96 patents, he has been awarded 15 paper awards and 17 nominations, including rare Technical Achievement Awards from IEEE societies. He advises over 60 PhD students and 4 postdocs, many of whom hold academic positions worldwide. His work bridges academia and industry, contributing to startups and venture capital through his board roles. Education: B.S. (Tsinghua, 1998) → M.S. (Tsinghua, 2001) → Ph.D. (Purdue, 2005). Career path: Assistant/Associate Professor at University of Pittsburgh (2010–2014) → Duke since 2014. Awards include the ACM SIGDA Outstanding New Faculty Award (2014), NSF CAREER Award (2013), and the Stansell Family Distinguished Research Award (2022). Research focuses on innovations in: (1) Non-volatile memory architectures for AI acceleration, (2) Hardware-software co-design for edge computing, (3) Security in neuromorphic systems, and (4) Large-scale ML for EDA. His group pioneered ReRAM-based accelerators like ReBNN and MARC, and introduced novel edge AI frameworks like Ecco and Prosperity. These works address scalability, energy efficiency, and real-time performance challenges. Key initiatives include the NSF IUCRC for Alternative Sustainable & Intelligent Computing (ASIC), advancing sustainable computing through novel materials and architectures. His leadership in standard-setting bodies like the IEEE Circuits and Systems Society ensures cutting-edge research translates into industry practices. Grants: Lead PIs for multiple NSF AI Institutes and industry partnerships. Labs: Directs the Athena Institute and DCEI, fostering collaboration between academia and industry. Current projects include quantum computing placement algorithms (QPlacer), federated learning frameworks (FedGPT), and neuro-symbolic architectures.

Yanan Guoمشاهده پروفایل

استادیار

• Computer Architecture
• Cybersecurity
• GPU Computing
• +۴ مورد دیگر

Yanan Guo is an Assistant Professor in the Department of Computer Science at the University of Rochester, specializing in computer architecture and cybersecurity. Her research focuses on GPU memory safety, side-channel attacks, quantum computing, and machine learning security, with recent projects exploring cross-VM side-channel vulnerabilities and quantum circuit simulation. PhD, University of Pittsburgh (advisor: Dr. Jun Yang) Her work bridges hardware and software security, addressing issues like GPU cache eviction mechanisms, memory corruption attacks, and adversarial threats in neural networks. She actively collaborates with researchers like Youtao Zhang and Jun Yang, with publications in top venues including USENIX Security, MICRO, and ICML. Recent publications highlight trends in GPU security (memory safety, side-channel attacks), quantum computing optimizations, and adversarial machine learning. Her team’s projects have received recognition such as the NSF OAC grant for AI workflow security and features in IEEE Transactions on Computers. Featured Paper in IEEE Transactions on Computers (02/22 issue) Shortlisted for Top Picks in Hardware and Embedded Security 2023 Dr. Guo mentors PhD students and offers weekly office hours for undergraduates, emphasizing career paths, graduate applications, and research guidance. She serves on program committees for conferences like USENIX Security and ASPLOS.

Marco Serafiniمشاهده پروفایل

استادیار

• Database Systems
• Distributed Systems
• Data Science
• +۳ مورد دیگر

Marco Serafini is an Assistant Professor in the Department of Computer Science at the University of Massachusetts Amherst, affiliated with the College of Information and Computer Sciences (CICS). He leads the DREAM Lab (Data systems Research for Exploration, Analytics, and Modeling) and is part of the Center for Data Science. Prior to UMass, Serafini worked as a Senior Scientist at the Qatar Computing Research Institute (QCRI) and held a postdoctoral fellowship at Yahoo! Research in Barcelona. He earned his PhD in Computer Science from TU Darmstadt (Germany), where his thesis was recognized through nominations for best thesis awards across German, Swiss, and Austrian computer science societies. His research focuses on the intersection of database systems, distributed systems, and data science, emphasizing scalable architectures for big data analytics and machine learning. Key areas include computation pushdown in cloud DBMSs, graph neural network training systems, and efficient graph pattern matching. His work addresses challenges in tail latency mitigation, resource optimization, and transparent scaling of ML models. Serafini has contributed to influential systems like Arabesque (for distributed graph mining), E-Store (elastic partitioning), and Aion (event-time stream processing). He has been awarded an NSF CNS Core grant to advance scalable GNN training. His publications span top venues such as ACM SIGOPS, VLDB, and ICDE, reflecting his expertise in both theoretical foundations and practical system implementations. Professional recognition includes thesis nominations from major computer science societies and sustained contributions to open-source projects in distributed computing. Serafini advises students through the DREAM Lab, focusing on preparing the next generation of data systems researchers.

Yongshan Dingمشاهده پروفایل

استادیار

• Quantum Computing
• Computer Architecture
• Quantum Algorithms
• +۴ مورد دیگر

Yongshan Ding is an Assistant Professor of Computer Science and Applied Physics at Yale University. He leads the Quantum Systems Lab (QSL) and directs Yale's Quantum Science and Engineering Certificate program. Affiliated with the Yale Quantum Institute (YQI) and Computer Systems Lab (CSL), his research focuses on quantum computing systems spanning algorithms, architecture, and hardware/software co-design. Dr. Ding earned his Ph.D. from the University of Chicago and a B.Sc. from Carnegie Mellon University. He has received prestigious awards including the Siebel Scholarship (2020) and William Rainey Harper Dissertation Fellowship (2020). Research Interests: Quantum computing architectures, noise-resilient quantum algorithms, error correction methods, quantum compilation, hardware-software co-design, and NISQ system optimization. Editorial Roles: Editor at Quantum journal and Associate Editor at ACM Transactions on Quantum Computing . Labs: Founder of Yale's Quantum Systems Lab (QSL) and contributor to the Computer Systems Lab (CSL). Awards: Siebel Scholarship (2020) William Rainey Harper Dissertation Fellowship (2020) QCE Best Paper Award (2024) IEEE Micro Top Picks Honorable Mention (2023, 2020) IBM Q Best Paper Award, First Prize (2020) Mathematics Competition Runner Up (2016)

Mark Battyمشاهده پروفایل

استاد

• Concurrent Systems
• Formal Verification
• Programming Languages
• +۳ مورد دیگر

Mark Batty is a Professor in the School of Computing at the University of Kent, specializing in formal methods for concurrent systems. His work bridges hardware-software interfaces, focusing on memory models for C/C++, OpenCL, and architectures including x86, ARM, POWER, and GPUs. As a member of the Programming Languages and Systems Research Group, he develops mathematical specifications and verification tools for real-world concurrency challenges. His research centers on empirical testing of hardware/compiler behavior, formal modeling of system components, and verification of fine-grained concurrent algorithms. Key contributions address relaxed memory semantics, transactional memory, and compositional reasoning for concurrent data structures. His work combines theoretical rigor with practical tool development to ensure correctness in complex concurrent environments. Analysis of his 2015-2025 publications reveals consistent focus on memory consistency models, formal verification of weak memory concurrency, and compiler optimizations. Dominant themes include C/C++11 standards, GPU concurrency semantics, and mechanized verification techniques. His research demonstrates strong industry relevance through collaborations with hardware vendors and contributions to language standards. Mark Batty has received significant recognition: John C. Reynolds Doctoral Dissertation Award (2015) from ACM SIGPLAN CPHC and BCS Distinguished Dissertation Award (2015) Lloyds Register Foundation and Royal Academy of Engineering Research Fellowship (2016) He actively leads major research initiatives and mentors next-generation researchers: Current Funding: EPSRC Standard Grant 'Verifiably Correct transactional memory' (2018), VeTTS Grant 'Specification and verification of C++ data structure libraries' (2018), EPSRC First Grant 'Compositional, dependency-aware C++ concurrency' (2018) PhD Recruitment: Actively seeking candidates for UKRI-funded studentship in Verified Trustworthy Software Systems Batty drives community engagement through Kent Concurrency Workshop (2016) and South of England Programming Language Seminars, fostering national collaboration in programming languages research. His leadership in organizing Royal Society discussions underscores his influence in trustworthy systems verification.

Xin Pengمشاهده پروفایل

استاد

• Software Analytics
• Intelligent Software Development
• Microservice
• +۴ مورد دیگر

Xin Peng is a Professor and Deputy Dean at the School of Computer Science, Fudan University, China. He leads the CodeWisdom research team focusing on intelligent software engineering techniques for development, maintenance, and operation of software systems. His educational background includes a PhD in Computer Science (2001-2006) and Bachelor's degree in Computer Science (1997-2001), both from Fudan University. He progressed through the academic ranks from Assistant Professor (2006-2010) to Associate Professor (2010-2015) and finally to Professor (2015-present). Professor Peng's research interests span Software Analytics, Intelligent Software Development, Microservice systems, and AIOps. His work leverages AI technologies including deep learning and knowledge graphs to develop intelligent software engineering techniques. A significant portion of his recent work focuses on applying Large Language Models to various software engineering tasks, including vulnerability detection, API usage analysis, and test automation. His publication record shows a clear trend toward increasingly sophisticated applications of AI in software engineering, with recent work heavily featuring LLMs for tasks ranging from vulnerability patch porting to resource leak detection. The research spans multiple domains including microservice systems, automotive software, and Web of Things security. Best Paper Award of ICSM 2011 ACM SIGSOFT Distinguished Paper Award of ASE 2018 and 2021 IEEE TCSE Distinguished Paper Award of ICSME 2018, 2019, and 2020 IEEE Transactions on Software Engineering Best Paper award for 2018 Professor Peng serves in numerous leadership roles including Deputy Director of CCF Technical Committee on Software Engineering, Co-Editor-in-Chief of Journal of Software: Evolution and Process, and Associate Editor for ACM Transactions on Software Engineering and Methodology. He has been actively involved in program committees for major software engineering conferences including ICSE, ASE, ESEC/FSE, and ICSME. He leads the CodeWisdom research team at Fudan University, which has developed several benchmark systems including TrainTicket for microservice research. The team's work bridges academic research with industrial applications, particularly in microservice systems analysis and intelligent software development tools.

Hui Luمشاهده پروفایل

استادیار

• Operating Systems
• Systems Virtualization
• Cloud Computing
• +۶ مورد دیگر

Dr. Hui Lu is an Assistant Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington (UTA), where he has been serving since September 2023. Prior to joining UTA, he was an Assistant Professor at SUNY Binghamton from 2017 to 2023. His academic journey includes a Ph.D. in Computer Science from Purdue University (2017), and Master’s and Bachelor’s degrees in Electronic Engineering from Shanghai Jiao Tong University. Ph.D., Computer Science, Purdue University, 2017 M.S., Electronic Engineering, Shanghai Jiao Tong University, 2009 B.S., Electronic Engineering, Shanghai Jiao Tong University, 2006 Dr. Lu's research centers on systems software with a focus on operating systems, virtualization, cloud computing, file and storage systems, and computer networks. His work emphasizes performance optimization and security in cloud-native environments. He has collaborated with leading industrial research labs including HPE Labs, IBM Research, Microsoft Research, AT&T Labs, and NEC Labs. His recent publications span top-tier venues such as OSDI, SOSP, USENIX ATC, and VLDB. The article trends reflect a strong emphasis on secure container technologies, memory tiering, packet processing optimization in virtualized networks, and efficient cloud storage systems. His work increasingly integrates hardware-aware optimizations and lightweight security mechanisms. NSF CAREER Award (2023) UT System Rising STARs Award (2023) Summer Faculty Fellowship, Air Force Research Lab (2019) Dr. Lu has successfully advised multiple Ph.D. students, including Jiaxin Lei, who is now an Assistant Professor at Kean University. His research is supported by major grants from the National Science Foundation (NSF) and the Air Force Research Lab (AFRL), focusing on secure containers, non-volatile memory management, and cloud-native virtualization. He has served as Principal Investigator (PI) on multiple funded projects, demonstrating strong leadership in research and innovation. He is actively involved in teaching core courses such as Operating Systems and advanced topics in systems and architecture. He mentors a growing group of Ph.D. students and welcomes motivated individuals to join his research group.

• Computer Networks
• Network Reliability
• Wireless Mesh Network
• +۳ مورد دیگر

Dr. Sie Teng Soh is an Associate Professor at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences. With qualifications including a PhD from Louisiana State University, he specializes in computer networks, wireless systems, and algorithm design. Research focuses on: Network topology optimization for UAV systems Energy-efficient IoT task scheduling Reliable wireless communication protocols Game-theoretic network management Green computing in software-defined networks Publication trends show advancing work in UAV network optimization, with recent articles addressing max-min rate optimization, energy harvesting in IIoT, and machine learning approaches for coverage prediction. His research consistently addresses practical challenges in wireless network deployment under real-world constraints. Teaching areas include advanced courses in network reliability and traffic engineering. Professional service includes editorial roles for IEEE Transactions on Parallel and Distributed Systems and program committee memberships for major conferences including FAST and EuroSys.

Pablo Aragónمشاهده پروفایل

استاد مدعو

• Computational Social Science
• Social Computing
• Wikipedia Studies
• +۴ مورد دیگر

Pablo Aragón is a Research Scientist at the Wikimedia Foundation and an Adjunct Professor at Universitat Pompeu Fabra. His work bridges computational social science, civic technology, and technopolitics, with a focus on Wikipedia's governance, digital democracy tools, and participatory systems. He co-founded the Democratic Innovation Lab in Barcelona and the DatAnalysis15M research network. Key research interests include analyzing knowledge integrity in Wikipedia, configuring digital participatory budgeting systems, and studying platform effects in civic technologies. He has led projects like DECODE (decentralized citizen engagement) and contributed to platforms like Decidim, which empower participatory democracy in cities like Barcelona. Recent conference engagements include KDD 2024 (data mining), ICWSM 2024 (social media analysis), and Wikimedia CEE Meeting 2024. His work emphasizes cross-cultural collaboration, with studies published in ACM Transactions on Computer-Human Interaction and peer-reviewed conferences like CIKM and ACM SIGKDD. Professional affiliations include the Decidim association, Amnistía Internacional España, and the open knowledge advocacy group Civio. His research often intersects with open science, free culture movements, and gender equity in urban mobility.

Farzaneh Derakhshanمشاهده پروفایل

استادیار

• Type Theory
• Proof Theory
• Programming Languages
• +۷ مورد دیگر

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