جست‌وجوی استاد و پژوهشگر

Muhammad Rashedمشاهده پروفایل

استادیار

• Electronic Design Automation (EDA)
• In-Memory Computing
• Artificial Intelligence Acceleration
• +۵ مورد دیگر

Dr. Muhammad Rashed is an Assistant Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington, within the College of Engineering. He holds a Ph.D. in Computer Engineering from the University of Central Florida (2024) and a B.S. in Electrical and Electronics Engineering from Bangladesh University of Engineering and Technology (2015). Ph.D. : Computer Engineering, University of Central Florida, 2024 B.S. : Electrical and Electronics Engineering, Bangladesh University of Engineering and Technology, 2015 His research focuses on electronic design automation (EDA), in-memory computing, AI acceleration, and sustainable computing. He explores novel computing paradigms to overcome the limitations of traditional architectures, particularly in data-intensive applications such as AI and scientific computing. His work emphasizes hardware-software co-design and leveraging emerging non-volatile memories for energy-efficient processing. The 15 most recent publications highlight a consistent focus on in-memory computing, particularly in path-based and flow-based architectures, logic synthesis, and AI acceleration. Key themes include optimization, fault tolerance, verification, and the use of advanced data structures like sentential decision diagrams. His work is published in top-tier venues such as DAC, ICCAD, ASP-DAC, and IEEE/ACM journals. Scientific Awards: UTA CARES Grant for OER Creation Research Experiences for Undergraduates (REU) Grant Alireza Seyedi Doctoral Research Innovation Endowed Scholarship David T. & Jane M. Donaldson Memorial Scholarship IEEE/ACM William J. McCalla ICCAD Best Paper Award Nomination Best Research Video Award, Design Automation Conference (DAC) Dr. Rashed advises several graduate and undergraduate students in the NextGen Computing Lab and is involved in research grants including the UTA CARES Grant and REU funding. He actively contributes to academic service through roles such as conference TPC member, journal reviewer (e.g., IEEE TCAD, ACM TODAES), and committee participation in the department and college. His lab, the NextGen Computing Lab, is dedicated to building scalable, energy-efficient computing systems for next-generation AI and scientific workloads, aligning with national initiatives in advanced computing.

John Wawrzynekمشاهده پروفایل

استاد

• Computer Architecture
• Reconfigurable Computing
• Wireless Systems
• +۳ مورد دیگر

John Wawrzynek is a Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is affiliated with the Department of Electrical Engineering and Computer Sciences in the College of Engineering and serves as Co-Director of the Berkeley Wireless Research Center and Co-PI of the CONIX Research Center, one of the six centers in the Joint University Microelectronics Program sponsored by DARPA. Dr. Wawrzynek received his B.S. in Electrical Engineering from SUNY, Buffalo (1977), M.S. in EE from the University of Illinois, Urbana/Champaign (1979), and Ph.D. in Computer Science from Caltech (1987). Before joining the Berkeley faculty in 1988, he worked as a consultant at Schlumberger Palo Alto Research. His research focuses on Computer Architecture, Reconfigurable Computing, Wireless Systems, and Integrated Circuit and System Design . His work spans both theoretical foundations and practical implementations, with particular emphasis on FPGA-based computing systems, reconfigurable architectures, and wireless communication systems. His research group has made significant contributions to the field of reconfigurable computing, including the development of the Garp architecture and various tools for reconfigurable computing systems. Analysis of his recent publications (2022-2025) reveals continued focus on reconfigurable computing, FPGA design, wireless networking, and formal methods for hardware verification. His work shows an evolution from traditional computer architecture towards specialized hardware acceleration, machine learning for EDA, and wireless systems research, with particular emphasis on SAT sampling, differentiable computing, and efficient FPGA implementation of neural networks. DAC's Most Influential Paper Award (2025) NSF Presidential Young Investigator (PYI) (1989) Charles Lee Powell Fellowship (1985) NASA Certificate of Recognition (1983) Rensselaer Engineering and Science Medal (1975) Professor Wawrzynek has advised numerous graduate students throughout his career, many of whom have gone on to prominent positions in both industry and academia including Google, Xilinx, and MIT Lincoln Laboratory. His research has been supported by various grants from NSF, DARPA, and industry partners. He leads the Berkeley Wireless Research Center, which focuses on next-generation wireless communication systems and technologies, and is actively involved in the CONIX Research Center which explores connected intelligence at the network's edge.

Allison Sullivanمشاهده پروفایل

استادیار

• Software Engineering
• Formal Methods
• Programming Languages
• +۳ مورد دیگر

Allison Sullivan is an Assistant Professor of Computer Science at the University of Texas at Arlington (UTA), where she also serves as the Undergraduate Software Engineering Program Director. She is a member of the Software Engineering Research Center (SERC) at UTA and serves as faculty advisor for UTA's Society of Women Engineers (SWE) club. Dr. Sullivan received her PhD in Software Verification, Validation and Testing (SVVAT) from the University of Texas at Austin in 2017 under Sarfraz Khurshid. Her educational background includes: PhD in Software Verification, Validation and Testing, University of Texas at Austin (2017) M.S. in Software Engineering, University of Texas at Austin (2014) B.S. in Software Engineering, University of Texas at Dallas (2012) Dr. Sullivan's research focuses on two primary areas: Automated Software Engineering : Test/Oracle Generation, Automated Bug Localization and Repair, Mutation Testing, and Regression Testing Formal Methods and Programming Languages : Abstractions, Finite Model Finders, Program Synthesis, and SAT/SMT Solvers She leads the SCOPE lab which focuses on 'showing the correctness of all program executions' and has published extensively on Alloy modeling language applications. Her recent publications demonstrate a strong focus on applying formal methods to software engineering problems, with a growing emphasis on the intersection of large language models and software development practices. Her work spans theoretical foundations, tool development, and empirical studies of how developers use modeling languages. Her scientific achievements have been recognized with: NSF CAREER Award (2024) UTA CSE department Rising Star Research Award (2024) UTA College of Engineering Outstanding Early Career Faculty Award (2025) NSF grant for building an educational tool for software modeling ($400k) Dr. Sullivan has successfully advised two PhD students to completion: Dr. Ana Jovanovic (defended November 2024) and Dr. Anahita Samadi (defended February 2025). She actively mentors undergraduate researchers and has secured significant research funding including the NSF CAREER grant. Her service includes committee roles for major conferences including ASE, ISSRE, and FormaliSE. She leads the SCOPE lab at UTA, which brings together graduate and undergraduate researchers to develop techniques for improving software verification and validation, with particular emphasis on making formal methods more accessible to practitioners.

• Automated reasoning
• Formal methods
• Autonomous systems
• +۵ مورد دیگر

Zhe Hou is a Senior Lecturer at the School of Information and Communication Technology , Griffith University, Australia. His academic journey includes a PhD in automated reasoning for separation logic from the Australian National University (2015) and prior research roles at Nanyang Technological University, Singapore (2015-2017). He joined Griffith University in 2017 and became permanent faculty in late 2019. Research Interests : Formal methods for software verification Automated reasoning with logical frameworks Blockchain technology and security Quantum computing verification Integration of LLMs with rigorous reasoning Sports analytics via model checking Recent Publications demonstrate expertise in neural-symbolic reasoning, blockchain security, quantum SAT solvers, and runtime verification frameworks. His work combines formal logic with machine learning for applications in cybersecurity and AI trustworthiness. Scientific Awards : ACM SIGSOFT Distinguished Paper Award (2025) Supervision Roles : Principal/Associate Supervisor for 6+ doctoral projects in blockchain security, AI verification, and network security. Professional Activities : Editor for Springer-Nature and Formal Aspects of Computing special issues, conference chair for ICFEM, ICECCS, and ISACE symposia.

• Model Checking
• Symbolic Execution
• Compositional Verification
• +۷ مورد دیگر

Corina Pasareanu is an ACM Fellow and IEEE ASE Fellow serving as a Principal Scientist at Carnegie Mellon University's CyLab Security and Privacy Institute and Technical Professional Leader for Data Science at NASA Ames Research Center through KBR. Her work bridges formal methods, software verification, and artificial intelligence to ensure the safety and security of complex systems, particularly autonomous systems and machine learning applications. Dr. Pasareanu received her academic training at: Ph.D. in Computer Science, Kansas State University (2001) M.S. in Computer Science, University Politehcnica of Bucharest (1995) B.S. in Computer Science, University Politehcnica of Bucharest (1994) Her research focuses on developing formal verification techniques that can provide mathematical guarantees about the behavior of complex software systems. She specializes in applying model checking, symbolic execution, and compositional verification methods to challenges in autonomy, security, and AI safety. Her recent work addresses the verification of systems incorporating machine learning components, particularly neural networks used in safety-critical applications like autonomous vehicles. She investigates how to ensure these systems behave correctly even when their perception components have uncertainties or are subject to adversarial attacks. Analysis of her recent publications shows a strong trend toward verifying AI and machine learning systems, particularly focusing on neural networks in autonomous systems. Her work increasingly addresses the challenges of Large Language Models, examining both their vulnerabilities to attacks and methods to defend against them. She also continues to advance traditional software verification techniques while adapting them to modern programming languages and paradigms. Dr. Pasareanu has received numerous prestigious awards recognizing her contributions to the field: ACM Fellow IEEE ASE Fellow ETAPS Test of Time Award (2021) ASE Most Influential Paper Award (2018) ESEC/FSE Test of Time Award (2018) ISSTA Retrospective Impact Paper Award (2018) ACM Impact Paper Award (2010) ICSE 2010 Most Influential Paper Award (2010) As an advisor, Dr. Pasareanu mentors several PhD students and postdoctoral researchers, often in collaboration with other faculty members at CMU. Her students focus on cutting-edge research at the intersection of formal methods and AI safety. Her research is supported by substantial funding from diverse sources including NSF, DARPA, NASA, AWS, and industry partnerships. She leads multiple projects focused on AI security, formal verification of neural networks, and software analysis techniques. Dr. Pasareanu also plays a significant role in the broader research community, serving as Program/General Chair for major conferences including ICSE 2025, and as an associate editor for IEEE TSE and STTT. Dr. Pasareanu leads research teams working on projects like "Trinity: Neurosymbolic Learning and Reasoning" (DARPA) and "HUGS: Human-Guided Software Testing and Analysis" (NSF). Her work often involves interdisciplinary collaboration between computer scientists, formal methods experts, and domain specialists to address complex safety challenges in autonomous systems.

Ruben Martinsمشاهده پروفایل

استادیار

• Constraint Programming
• Program Synthesis
• Formal Verification
• +۳ مورد دیگر

Ruben Martins is an Assistant Professor at Carnegie Mellon University's School of Computer Science and serves as the program director of the Master of Science in Computer Science (MSCS) . His research focuses on the intersection of constraint programming, program synthesis, analysis, and verification, with recent work aiming to make formal methods tools more accessible through automated reasoning. Ruben earned his Ph.D. with honors from the Technical University of Lisbon, Portugal (2013) , followed by postdoctoral research at the University of Oxford (2014-2015) and UT Austin (2015-2017) . Research Interests : Ruben's work bridges constraint programming and program synthesis , with applications in software verification , optimization , and automated reasoning . He has developed award-winning tools like Open-WBO , a modular MaxSAT solver that has won gold medals in international competitions. His publications span top-tier venues such as POPL , PLDI , FSE , SAT , and CP , often addressing real-world challenges from program analysis to network security. Scientific Awards include: Distinguished Paper Award at PLDI 2018 Distinguished Paper Award at FSE 2021 Distinguished Paper Award at SAT 2022 Gold medals for Open-WBO in MaxSAT competitions Teaching & Advising : Ruben mentors Ph.D., Master’s, and undergraduate students in research projects related to program synthesis, formal methods, and constraint solving. He teaches courses such as Bug Catching: Automated Program Verification and Advanced Topics in Logic: Automated Reasoning and Satisfiability , emphasizing hands-on experience with tools like Why3. His advising spans topics from AI-driven program repair to network protocol verification , fostering collaboration across disciplines.

Koushik Senمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Formal Methods
• +۸ مورد دیگر

Koushik Sen is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He holds a B.Tech from IIT Kanpur and M.S./Ph.D. from UIUC. His research focuses on Software Engineering, Programming Languages, and Formal Methods, emphasizing tools like DART, CUTE, and Jalangi for improving software reliability. He leads projects such as CORVETTE and Sky Computing Lab, and collaborates with Samsung Research America on JavaScript analysis. Sen has received prestigious awards including the Sloan Fellowship and ACM SIGSOFT Impact Award. Education: B.Tech, Indian Institute of Technology, Kanpur M.S. and Ph.D., University of Illinois at Urbana-Champaign Research Interests: Software Testing, Verification, Symbolic Execution, Security, and Quantum Computing. His work bridges automated testing (e.g., concolic testing) with machine learning for bug detection and program synthesis. Projects include Hindsight Logging for ML reproducibility and quantum circuit optimization (QFAST). Awards: NSF CAREER, IFIP Manfred Paul, ACM SIGSOFT Distinguished Paper (multiple), and Sloan Fellowship. Advising: Supervised over 30 students/postdocs, leading to faculty roles at UBC, CMU, and industry positions at Google, Facebook, and Samsung. Labs/Teams: Berkeley Center for Responsible, Decentralized Intelligence (RDI), EPIC Data Lab, and Sky Computing Lab. Active in quantum computing and hardware fuzzing (RTL-FuzzLab).

Kinan Dak Albabمشاهده پروفایل

استادیار

• Data Privacy
• Systems Security
• Secure Computation
• +۷ مورد دیگر

Kinan Dak Albab is an Assistant Professor at the Faculty of Computing and Data Sciences (CDS) at Boston University, where he joined in summer 2024. His research spans systems, cryptography, and programming languages, focusing on building practical tools for data privacy and compliance-by-construction. He has developed influential systems such as Sesame, K9db, and DP-PIR, which have been published in top venues like SOSP, OSDI, and USENIX Security. PhD in Computer Science, Brown University MS in Computer Science, Boston University (2020) BS in Computer Science, American University of Beirut (2015) Kinan's research centers on data privacy , secure computation , and systems security . He designs tools that allow developers to build applications that are privacy-compliant by construction. His work leverages systems design, cryptographic protocols, and language-level enforcement to reduce developer burden while ensuring strong privacy guarantees. He is particularly interested in GDPR compliance, private information retrieval, and usability of secure systems. His publications span high-impact areas including end-to-end privacy enforcement (Sesame), database systems with built-in privacy (K9db), and efficient private information retrieval (DP-PIR). These works combine systems performance with strong theoretical foundations, enabling real-world deployment in domains like wage gap analysis and public policy. Presidential Award for Excellence in Teaching, Brown University (2025) Teaching Excellence Award, Boston University (2020) Vivli and Microsoft datatheon Outstanding Graduate Submission (2019) Hariri Institute Graduate Fellow (2017–2020) Mark Sawaya Excellence Award, AUB (2015) 1st Place, ACM Lebanese Collegiate Programming Contest (2015) Kinan has advised and collaborated on real-world secure computation deployments, including a project with the Boston Women's Workforce Council and the Greater Boston Chamber of Commerce to measure wage gaps across over 100 companies. His work contributed to the formation of the startup nthparty and has been cited in the White House’s National Strategy on Privacy-Preserving Data Sharing, the UN Handbook on Privacy-Preserving Computation, and the European Commission’s report on Technological Enablers for Privacy. He is the lead developer of the JIFF framework for secure multi-party computation on the web and has created tools like Carousels for resource estimation in secure programs. He leads the ETOS group and is affiliated with multiparty.org , an initiative focused on advancing privacy-preserving technologies through open-source tools and real-world applications.

• Security
• Embedded Systems Security
• Cyber-Physical Systems Security
• +۱۳ مورد دیگر

Francesco Regazzoni is a Senior Researcher at the Faculty of Informatics, Università della Svizzera italiana (USI), and affiliated with the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). His work bridges embedded systems, cybersecurity, and artificial intelligence, with a focus on securing hardware and cyber-physical systems. Research Interests: His expertise spans embedded and cyber-physical systems security, side-channel attacks, post-quantum cryptography, hardware trojans, random number generators, and the security of AI and approximate computing. He also contributes to hardware/software co-design and operating systems security. The analysis of his recent publications reveals a consistent focus on hardware and system-level security , particularly in resource-constrained environments like IoT and embedded devices. His work integrates machine learning for attack detection and applies formal methods to ensure trust in hardware. A growing emphasis is placed on securing AI systems from physical and adversarial threats. Scientific Contributions: Over 100 peer-reviewed publications One book and one patent Extensive international collaboration (Belgium, Netherlands, USA, Switzerland, Singapore) Advising and Grants: While specific advisees and grants are not listed, his leadership in funded research projects and involvement with ALaRI and IDSIA suggest active mentorship and project coordination. His work has been supported by industry (e.g., ST Microelectronics, HP), the Swiss National Foundation, and the European Union. Labs and Teams: He is part of the Graph Machine Learning Group (GMLG) at IDSIA, which evolved from the Advanced Learning and Research Institute (ALaRI). This group focuses on graph machine learning, reinforcement learning, and dynamical systems, particularly in non-stationary environments.

Stephen Siegelمشاهده پروفایل

دانشیار

• Formal methods for software verification
• Verification of parallel and scientific software
• Concurrency in software systems
• +۳ مورد دیگر

Stephen Siegel is an Associate Professor at the University of Delaware with a joint appointment in the Department of Computer and Information Sciences and the Department of Mathematical Sciences . Holding a PhD in Mathematics from the University of Chicago (1993), he transitioned from finite group theory research to formal methods in computer science, focusing on verification of parallel and scientific software. His research centers on the Verified Software Laboratory (VSL) and the CIVL Model Checker for HPC program verification. Recent work includes formal verification of PETSc components at CAV 2025 and collective contract frameworks for message-passing programs. Research Interests Formal methods for software verification Parallel and HPC software reliability Model checking techniques Application of mathematical logic to computing Academic Service Highlights Program Committee & Publication Chair, CAV 2025 Co-organizer, International Workshop on Verification of Scientific Software (VSS 2025) Chair, VerifyThis competition (2023) Editorial service at IEEE Transactions on Software Engineering (2015-2019) Teaching Portfolio CISC 404/604: Logic in Computer Science CISC 414/614: Formal Methods in Software Engineering CISC 372: Parallel Computing (MPI/OpenMP/CUDA instruction) Advanced Topics courses: Model Checking, Abstract Interpretation

Alan Huمشاهده پروفایل

استاد

• Formal Verification
• Algorithms
• Computer Architecture
• +۳ مورد دیگر

Alan Hu is a Professor in the Department of Computer Science at the University of British Columbia (UBC), part of the Faculty of Science. His research focuses on formal verification, algorithms, computer architecture, and electronic design automation. He teaches courses such as Intermediate Algorithm Design and Analysis (CPSC 320) and Introduction to Formal Verification and Analysis (CPSC 513). Dr. Hu has received notable awards, including the IEEE Council on Electronic Design Automation Outstanding Service Award and the IBM Faculty Award. His work emphasizes scalable verification techniques, SAT-based algorithms, and optimization in cloud computing and hardware systems. His research spans formal methods for hardware/software systems, including verification of embedded software, cache coherence, and network function virtualization. Notable contributions include advancements in SAT modulo theories, data race detection in heterogeneous systems, and cloud resource allocation frameworks like Cospot. Dr. Hu has been actively involved in teaching and curriculum development, consistently offering courses on algorithms, formal verification, and software design since 2000. His publications reflect a blend of theoretical foundations and practical applications in electronic design, cloud infrastructure, and verification tools. His scientific achievements include innovations in post-silicon validation, emulation-based coverage reduction, and formal analysis for debug trace optimization. He also contributes to the academic community through conference organization and editorial roles in formal verification and computer-aided design.

Philipp Wendlerمشاهده پروفایل

مدرس

• Software Verification
• Formal Methods
• Program Analysis
• +۵ مورد دیگر

Philipp Wendler is an academic lecturer in the Department of Computer Science at Ludwig-Maximilians-Universität München (LMU Munich). He is affiliated with the Software and Computational Systems Lab and actively involved in research, teaching, and open-source tool development. As an employee representative in the steering committee of the Institute of Informatics, he contributes to institutional governance. His research focuses on software verification, formal methods, and program analysis. Key projects include CPAchecker (a configurable verification framework) and BenchExec (a benchmarking tool). His work emphasizes practical applications in automated testing, energy-efficient algorithms, and reproducible benchmarking. Publications span topics like interpolation-based model checking, energy measurement tools, and strategies for software verification competitions. He has contributed to advancing predicate analysis, k-induction, and refinement selection techniques. Notable achievements include leading the development of CPAchecker and BenchExec, which are widely used in academic and industrial verification efforts. His research addresses challenges in scalable verification, flaky test analysis, and energy-aware computing.

Grumberg Ornaمشاهده پروفایل

استاد

• Model checking
• Automated verification of hardware and software systems
• Abstraction, refinement, and counterexamples
• +۶ مورد دیگر

Orna Grumberg is a Professor at the Computer Science Department of the Technion-Israel Institute of Technology. She holds the Leumi Chair in Science since 2011 and has been a full professor since 2005. Her work focuses on model checking and automated verification of hardware and software systems. Leumi Chair in Science (2011–present) Full Professor, Technion (2005–present) Steering Committee, CAV Conference (2010–present) Editorial Board, Journal on Formal Methods in System Design (2003–present) Dr. Grumberg’s research interests span automated verification, abstraction-refinement techniques, compositional and distributed model checking, and their application to security vulnerabilities and temporal logics. She is a co-author of the seminal book Model Checking , which serves as a foundational reference in the field. Her recent work explores security in network protocols via parameterized systems, SAT-based approaches for hardware verification, and interpolation-based model checking. These contributions integrate abstraction refinement, lazy abstraction, and reachability analysis. Collaboration with IBM on UML verification Collaboration with Rafael on security vulnerabilities in protocols Dr. Grumberg has mentored students who now lead verification teams at Intel, IBM, and Israeli universities. She previously served as Associate Dean for Graduate Studies at the Technion.

• Formal Methods
• Formal Verification
• Binary Decision Diagrams
• +۷ مورد دیگر

Paolo Enrico Camurati is a Full Professor in the Department of Control and Computer Engineering (DAUIN) at the Polytechnic University of Turin, where he contributes to research and teaching in formal methods and hardware verification. He is a member of the Formal Methods (FM) research group and has been actively involved in PhD supervision in the Computer and Systems Engineering program. His research interests include formal verification, binary decision diagrams, SAT solvers, electronic CAD, and the formal verification of hardware design correctness. These areas align with theoretical computer science and cyber-physical systems, contributing to advancements in reliable computing systems. Recent publications (2022–2024) show a strong focus on model checking techniques, interpolation-based learning, and optimization of binary decision diagrams for machine learning applications, indicating active and impactful research in formal methods and EDA. He has taught core computer engineering courses such as Specification and Simulation of Digital Systems , Algorithms and Data Structures , and Programming Techniques at both bachelor's and master's levels, supporting quality education in computing disciplines. He has no listed scientific awards in the provided material. Prof. Camurati advises PhD students in the Computer and Systems Engineering program and has taught extensively across multiple academic years. While specific grants are not mentioned, his ongoing research output suggests active funding and project involvement. He is a key member of the FM - Formal Methods Group (DAUIN), which drives research in formal verification and automated reasoning. The FM - Formal Methods Group (DAUIN) serves as his primary research lab, focusing on theoretical and applied aspects of formal verification, model checking, and decision diagram technologies.

Stefano Querمشاهده پروفایل

دانشیار

• Computer Science
• Electrical Engineering
• Formal Methods
• +۷ مورد دیگر

Stefano Quer is an Associate Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He holds a PhD in Electronic Engineering from the same institution and has been affiliated with DAUIN since 1996. Researcher (1996-2000) Associate Professor (2000-present) Visiting Faculty at UC Berkeley (1994-1995) Research Interests His work spans Formal Verification BDD/SAT Techniques Embedded Systems Hardware/Software Co-Verification Parallel Computing with applications in VLSI CAD, industrial IoT, and energy-efficient systems. Recent articles focus on GPU-accelerated graph algorithms, wireless sensor calibration, and AI-driven test optimization. Scientific Awards Best Paper Award, IEEE EURO-DAC'94 Academic Contributions Supervised PhD students Lorenzo Cardone and Andrea Calabrese Member of DATE, ICSOFT Technical Program Committees Topical Advisor for Sensors MDPI 60+ publications in IEEE/ACM venues