جست‌وجوی استاد و پژوهشگر

Sarah E. Chasinsمشاهده پروفایل

استادیار

• Programming Languages
• Human-Computer Interaction
• Program Synthesis
• +۳ مورد دیگر

Sarah E. Chasins is an Assistant Professor in the Electrical Engineering and Computer Sciences (EECS) department at the University of California, Berkeley, with research spanning programming languages and human-computer interaction. She leads the PLAIT Lab (Programming Languages for Approachable and Inclusive Tools) and serves as a faculty affiliate at the Berkeley Institute for Data Science (BIDS). Her work bridges computer science with social sciences, climate reporting, legal systems, and biological research through extensive collaborations. Dr. Chasins' research focuses on democratizing programming for non-traditional programmers including scientists, social scientists, journalists, and data scientists. Her work emphasizes creating approachable programming tools that help practitioners reach correct programs while understanding, extending, and trusting those programs. She specifically investigates program synthesis, programming tools for scientific domains, and human-centered programming language design. Her research mission aims to make programming a path to a more informed and evidence-driven society rather than just a way to get wrong answers faster. Her recent publications demonstrate a clear trajectory toward making programming more accessible and understandable. The work spans code search techniques, program synthesis approaches, refactoring tools, and studies of how domain experts interact with programming languages. A consistent theme across her research is placing human needs at the center of programming language design and implementation. Dr. Chasins actively mentors PhD students including Justin Lubin, Eric Rawn, Parker Ziegler, Sarah "Slim" Lim, Hellina Hailu Nigatu, David Minh-Duy Cao, and Marlena Preigh. She has previously advised numerous master's and undergraduate students who have gone on to work in both academia and industry. Her teaching includes core courses like CS164 (Programming Languages and Compilers) and specialized courses like CS294-184 (Building User-Centered Programming Tools) and CS39-001 (Technology, Society, and Power). She maintains an active service record in the programming languages community, having served on program committees for major conferences including PLDI, POPL, OOPSLA, and SPLASH. Notably, she co-chaired the Student Research Competition at PLDI 2020 and 2021 and has been involved in organizing workshops focused on programming languages and human-computer interaction.

Sotiris Christodoulouمشاهده پروفایل

دانشیار

• Web Engineering
• Web Application Performance Optimization
• Web Code Quality
• +۷ مورد دیگر

Sotiris Christodoulou is an Associate Professor at the Department of Electrical and Computer Engineering within the College of Engineering at the University of Peloponnese. He also serves as a research associate at the 'Diofantos' Institute of Computer Technology and Publishing. His academic career spans multiple institutions where he has taught graduate and undergraduate courses across seven different universities since 2004. Dr. Christodoulou earned his B.A. in Computer Engineering and Informatics from the University of Patras in 1994 and completed his PhD in Web Engineering from the same institution in 2004. His educational background established the foundation for his extensive research career focused on web technologies and applications. His primary research interests include Web Engineering, Web Application Performance Optimization, Web Code Quality, Semantic Web technologies, Hypermedia Systems, and emerging Web 2.0 and Web 3.0 technologies. His work extends to Virtual Interactive Environments, 3D and Augmented Reality applications, and Spatial Hypertext systems. Christodoulou's research bridges theoretical web engineering principles with practical applications in cultural heritage, education, and urban infrastructure systems. His research output comprises over 45 publications in international journals, book chapters, and conferences, accumulating more than 450 citations. He has participated in over 23 European and National Research and Development Projects focused on web software technology, hypermedia applications, and 3D educational and cultural applications. Professional member of ACM Professional member of IEEE Member of organizing committees for over 15 international scientific conferences Reviewer for recognized international journals (ACM, IEEE, etc.) Christodoulou has extensive teaching experience across seven universities, specializing in programming languages, web software engineering, software quality, and data management. His research projects typically combine applied research with cutting-edge technology implementation for real-world problems in large organizational information systems. He maintains regular office hours at Building K, Office K2.02 at the University of Peloponnese, with appointments available on Mondays and Thursdays.

Ioannis Stamelosمشاهده پروفایل

استاد

• Software Engineering
• Open Source Software
• Software Effort and Quality Estimation
• +۷ مورد دیگر

Ioannis Stamelos is a Professor of Software Engineering at the School of Informatics, Aristotle University of Thessaloniki (since 2015, research/teaching staff since 1997). He serves as Director of the Postgraduate Master Course in Interactive Hardware & Software Technologies. Major Research Areas: Open Source Software, Software Effort/Quality Estimation, Agile Methods, Enterprise Information Systems Key Projects: Deep Blue/AUTH Research Hub (2018-2022), BlockAdemic (blockchain-based micro-credentials), European Commission Open Source Policy Studies Research Trends from recent publications include: Process mining in library information systems Reusability metrics for software assets Bayesian networks in software project management Impact of design patterns on gaming software defects Technical debt assessment via structural metrics Blockchain applications in supply chain management Scientific Awards: Best Paper Award at IEEE DEST’09 Best Student Paper Award at ICSR 2012 Best Paper Award at QUATIC2012 Education & Leadership: PhD in Computer Science (1988), Diploma in Electrical Engineering (1983). Led numerous EU-funded projects (IST, ERASMUS, FP7) and national initiatives (ΓΓΕΤ, ΕΠΕΑΕΚ). Supervised PhD/MSc students in software reuse, OSS quality, and agile practices.

Diego Garbervetskyمشاهده پروفایل

دانشیار

• Static Analysis
• Dynamic Analysis
• Reverse Engineering
• +۷ مورد دیگر

Diego Garbervetsky is an Associate Professor at the Computer Science Department, School of Sciences, University of Buenos Aires, and a Researcher at ICC/CONICET. He also serves as Director of the Institute of Research in Computer Sciences (ICC). His academic career spans software engineering, programming languages, and formal methods with a focus on program analysis and verification. His research interests include: Static and dynamic program analysis Reverse engineering and compiler optimizations Program understanding and validation Testing and verification of programs featuring rich protocols Automatic symbolic resource analysis (gas consumption, dynamic memory, energy, etc.) Garbervetsky's recent work focuses on smart contract analysis and verification, particularly for Solidity on Ethereum blockchain. His research bridges theoretical program analysis with practical applications in security-critical domains. He has developed several tools including Contractor for behavior validation, JConsume2 for heap memory analysis, and BudaPest for automated software verification. His scientific contributions have been presented at top-tier conferences including ICSE, FSE, ISSTA, and PLDI. Garbervetsky has served on numerous program committees for major software engineering conferences and has advised multiple PhD and undergraduate students through their research.

Konstantinos Limniotisمشاهده پروفایل

مدرس

• Cryptography
• Boolean Functions
• Network Security
• +۵ مورد دیگر

Konstantinos Limniotis is an ICT Specialist at the Hellenic Data Protection Authority since 2009 and an active academic teaching at multiple Greek and Cypriot universities. He is currently teaching 'Network and Telecommunications Systems Security' at the University of Athens, 'Cryptography' and 'Security risk management' at the Open University of Cyprus, and has previously taught at the University of Peloponnese, Harokopio University of Athens, and Technological Educational Institutes. Since 2022, he is a member of ENISA's Ad Hoc Working Group on Data Protection Engineering. Dr. Limniotis received his B.Sc. in computer science (1999), M.Sc. in communications systems and networks (2002), and Ph.D. in 'Signal Processing Techniques in Cryptography' (2007) from the Department of Informatics and Telecommunications at the National and Kapodistrian University of Athens, under the supervision of Professor N. Kalouptsidis. His research focuses on the intersection of cryptography, security, and data protection. Dr. Limniotis has made significant contributions to cryptographic Boolean functions, particularly in algebraic immunity properties, and has extended his expertise to practical applications in data protection and privacy. His work bridges theoretical cryptography with real-world applications in personal data protection, particularly in the context of GDPR compliance. Recent research directions include post-quantum cryptography, blockchain security, and privacy-enhancing technologies for emerging applications like AI systems and IoT ecosystems. His publications demonstrate a clear trajectory from theoretical cryptographic research to applied security and privacy solutions that address contemporary regulatory and technological challenges. Dr. Limniotis has received multiple 'Excellence in Teaching' Awards from the Open University of Cyprus (2019-2023), recognizing his contributions to cybersecurity education. His teaching spans graduate programs in Computer and Network Security, Telecommunications Systems, and Data Science. As an active contributor to data protection policy, Dr. Limniotis has participated in multiple ENISA reports on pseudonymization techniques, data protection engineering, and personal data sharing. His work with the Hellenic Data Protection Authority since 2009 demonstrates a strong commitment to bridging academic research with practical data protection implementation.

Ioannis Vlahavasمشاهده پروفایل

استاد

• Logic Programming
• Knowledge representation and Reasoning
• Automated Planning
• +۳ مورد دیگر

Ioannis Vlahavas is a Professor in the School of Informatics at Aristotle University of Thessaloniki since 2003, where he directs the Intelligent Systems Lab. He has held significant leadership roles including Chair of the School of Informatics (2003-2005, 2013-2017) and Dean of the School of Science and Technology at the International Hellenic University (2007-2016). His career spans over three decades with continuous contributions to artificial intelligence research and education. Education: Ph.D. in Computer Science, Aristotle University of Thessaloniki (1988) B.Sc. in Physics, Aristotle University of Thessaloniki (1982) Professor Vlahavas's research focuses on foundational AI areas including Logic Programming, Knowledge Representation and Reasoning, Automated Planning, and Machine Learning. His work bridges theoretical frameworks with practical applications in autonomous systems, healthcare diagnostics, and financial modeling. He has pioneered methodologies in reinforcement learning and multi-agent systems, with particular emphasis on personality emulation in gamified environments and transformer-based architectures for complex real-world problems. His recent publications reveal a strong trajectory toward deep reinforcement learning, transformer optimization, and low-resource language processing. Key application domains include autonomous driving (5 of 15 recent papers), biomedical text mining (particularly drug-drug interaction extraction), and personality modeling in gaming environments. There is notable cross-pollination between finance (portfolio theory applications, cryptocurrency trading) and AI methodology development. Scientific Awards: EurAI Fellow (2017) Professor Vlahavas has mentored numerous graduate students through PhD candidate programs and research projects. His leadership extends to organizing major international conferences including the 24th IEEE International Conference on Tools with AI (2012) and the 9th Hellenic Conference on Artificial Intelligence (2016). He serves on editorial boards and has guest-edited special journal issues on AI applications. He directs the Intelligent Systems Lab at Aristotle University, which operates as a multidisciplinary research hub focusing on machine learning, natural language processing, and intelligent system applications across healthcare, transportation, and finance sectors. The lab maintains strong industry connections including RealMINT, the university spin-off where he serves as CEO.

Dimitrios D. Piromalisمشاهده پروفایل

دانشیار

• Electronic Embedded Systems
• Autonomous Vehicles
• Internet of Things (IoT)
• +۷ مورد دیگر

Dimitrios D. Piromalis is an Associate Professor at the University of West Attica , specifically within the Department of Industrial Design and Production Engineering . He leads the Research Lab of Electronic Automation, Telematics and Cyber-Physical Systems (EATCPS) , focusing on electronic embedded systems for applications in autonomous vehicles, IoT, and cyber-physical systems. With over 120 publications and extensive industry collaboration spanning 25 years, his work bridges academic research and practical engineering solutions. Education : BSc, MSc, and PhD in Electrical and Electronics Engineering. Research Focus : Electronic embedded systems, autonomous vehicles, IoT, cyber-physical systems, digital twins, 3D/4D printing, energy management, and smart agriculture. Recent publications highlight trends in TinyML for smart cities, predictive maintenance integration, hybrid energy storage for EVs, and digital twin applications across agriculture and automotive sectors. His work also extends to emergency communication systems, biomedical sensors, and blockchain-enabled energy gateways. Industry Collaboration : Field Application Engineer and Technical Consultant for multinational semiconductor companies. Teaching : Platforms for AI and Python programming, autonomous vehicles and drones.

Weihang Wangمشاهده پروفایل

استادیار

• Software Engineering
• Software Security
• Computer Systems
• +۶ مورد دیگر

Weihang Wang is a WiSE Gabilan Assistant Professor in the Department of Computer Science at the University of Southern California. His research focuses on building testing and analysis techniques to improve the reliability, security, and efficiency of complex software systems, with particular expertise in WebAssembly technologies. Wang received his Ph.D. in Computer Science from Purdue University in 2018. His educational background has provided a strong foundation for his research in software engineering and security, leading to numerous publications and awards in the field. His research spans multiple critical areas including WebAssembly analysis , software security , and program analysis . Wang's work addresses fundamental challenges in detecting and mitigating vulnerabilities in modern web applications and systems. His research group develops innovative approaches to static and dynamic analysis, bug detection, and security testing, with a strong emphasis on practical applications and real-world impact. Recent projects include developing frameworks for Spring analysis, WebAssembly function identification, and business flow tampering detection. Wang's publication record shows a clear trajectory of increasing impact in WebAssembly research, with multiple papers at top-tier conferences like WWW, ICSE, and FSE. His work spans from foundational analysis techniques to practical tools that address security and performance challenges in web technologies, demonstrating both theoretical depth and practical applicability. His scientific achievements have been recognized with prestigious awards including: N2Women Rising Stars in Networking and Communications (2024) University at Buffalo Exceptional Scholar - Young Investigator Award (2022) NSF CAREER Award (2021) Facebook Testing and Verification Research Award (2019) Mozilla Research Award (2019) Maurice H. Halstead Memorial Research Award (2018) Best Poster Award at ACSAC'22 Wang has successfully advised numerous graduate and undergraduate students, many of whom have published first-author papers at top conferences and secured positions at leading technology companies. He actively serves the research community through program committee roles at major software engineering and security conferences. His work has been supported by competitive grants from NSF, Facebook, and Mozilla, demonstrating the significance and potential impact of his research directions. At USC, Wang leads a vibrant research group focused on software engineering, security, and systems. The group is currently working on cutting-edge projects related to static/dynamic bug detection, program analysis for WebAssembly, attack investigation and detection, compiler testing, and performance profiling of modern web applications.

Sara Achourمشاهده پروفایل

استادیار

• Compilers
• Programming Languages
• Program Analysis
• +۵ مورد دیگر

Sara Achour is an Assistant Professor jointly appointed in both the Computer Science and Electrical Engineering Departments at Stanford University's School of Engineering. Her work bridges computer science and electrical engineering, focusing on enabling end-users to develop computations for emerging computing platforms with analog behaviors. Dr. Achour received her PhD in Computer Science from the Massachusetts Institute of Technology in 2021. Her academic journey led her to Stanford where she currently teaches courses including Introduction to Essential Software Systems and Tools (CS 104), Software Engineering (CS 295), and Software Techniques for Emerging Hardware Platforms (CS 349H/EE 349). Her research program centers on developing new programming languages, compilers, and runtime systems that address the challenges of emerging computing platforms. She specializes in creating tools that help developers harness the potential of analog and non-traditional hardware systems. Her work spans quantum computing, analog computing paradigms, hyperdimensional computing, and memory systems, with a particular emphasis on compiler techniques and hardware-aware optimization. Analysis of her recent publications reveals a strong focus on bridging the gap between software and emerging hardware platforms. Her work spans quantum computing (qubit/qutrit circuits), analog computing paradigms, hyperdimensional computing, and novel memory systems. A recurring theme is developing compiler techniques that optimize for specific hardware characteristics while maintaining programmer productivity. Dr. Achour actively mentors students across multiple levels of their academic careers. She serves as a Doctoral Dissertation Advisor, Co-Advisor, Reader, and Master's Program Advisor for numerous students working on cutting-edge research in compilers and emerging hardware. Her teaching portfolio includes both foundational courses like Introduction to Essential Software Systems and specialized advanced courses focused on emerging hardware platforms. She appears to be building a research group focused on programming languages and compilers for non-traditional computing architectures, with students working across quantum computing, analog systems, and memory technologies.

Hui Liمشاهده پروفایل

دانشیار

• Information Retrieval
• Data Mining
• Data Management
• +۸ مورد دیگر

Hui Li is an Associate Professor in the Department of Computer Science and Technology at the School of Informatics, Xiamen University. He is affiliated with the Media Analytics & Computing Laboratory (MAC Lab) and holds a Ph.D. in Computer Science from the University of Hong Kong. Ph.D., Computer Science, University of Hong Kong His research centers on Information Retrieval, Data Mining, and Data Management, with a strong emphasis on Recommender Systems. Key areas include shilling attacks and defenses, bias analysis and debiasing, large language model-based recommendation, generative information retrieval, code retrieval, and multi-modal large language models. His work bridges theoretical innovation with practical applications in real-world platforms. His recent publications span top-tier journals and conferences such as IEEE TKDE, TNNLS, TOIS, KDD, SIGIR, AAAI, ACL, and ICLR. The publications demonstrate a consistent focus on robustness, fairness, and efficiency in recommender systems, increasingly integrating large language models and graph-based methods. Themes include adversarial attacks, self-supervised learning, and data augmentation using LLMs. Hui Li actively supervises graduate students, many of whom have published in CCF-A and CCF-B ranked venues. Notable students include Zhang Sheng, Liu Hao, and Li Lianyun. He has contributed to open science by releasing datasets like the Dianping datasets for sequential and social recommendation research. His work has practical implications in e-commerce, social platforms, and software engineering tools. He collaborates with industry partners such as Alibaba, Tencent, and Pinduoduo, where several of his students have been placed. His research is supported by publications in high-impact journals and participation in leading AI conferences.

Chao Pengمشاهده پروفایل

مدرس پاره‌وقت

• Software Testing
• Program Analysis
• Programming Languages
• +۵ مورد دیگر

Chao Peng is a Principal Research Scientist at ByteDance where he leads the Trae Research team (ByteDance Software Engineering Lab), conducting cutting-edge research on AI agents for software engineering. He also serves as a Part-time Postgraduate Student Mentor at Fudan University's School of Computer Science, bridging industry research with academic mentorship. PhD in Informatics (2021), University of Edinburgh, UK MSc in High Performance Computing and Data Science (2017), University of Edinburgh, UK BEng in Computer Science and Technology (2016), Xuzhou University of Technology, China Dr. Peng's research focuses on the intersection of software testing, program analysis, and large language models. His work explores how AI agents can revolutionize software engineering practices, with particular emphasis on automated bug detection, code generation, and testing frameworks. He has pioneered approaches for evaluating LLM performance in software engineering contexts and developing agent-based systems that enhance developer productivity while maintaining code quality and security. His recent publications demonstrate a clear trend toward integrating large language models with traditional software engineering practices. The research spans code generation evaluation, security vulnerability detection, automated bug reproduction, and issue localization. These works collectively advance the field of AI-assisted software development by addressing practical challenges in reliability, security, and efficiency of AI-generated code. Distinguished Reviewer for FSE'25 School of Informatics Scholarship (fully-funded PhD scholarship) Outstanding Graduate Scholarship at Xuzhou University of Technology Multiple China National Scholarships Honours Spot Bonus at ByteDance Certificate of Achievement for HPCAC Student Cluster Competition Dr. Peng actively mentors students through his role at Fudan University and previously at the University of Edinburgh, where he served as sub-supervisor for MSc projects and teaching assistant for software testing courses. His research has attracted significant industry attention, leading to multiple collaborations between ByteDance and academic institutions. He frequently serves on program committees for major software engineering conferences including ASE, FSE, and ICSE, demonstrating his leadership in the field. As leader of the Trae Research team at ByteDance Software Engineering Lab, Dr. Peng oversees research on AI agents for software engineering, including the application and evaluation of AI agents and training LLMs for agent-based systems. The lab's work focuses on practical systems that predict, detect, diagnose, and fix bugs across various software systems, with particular emphasis on real-world applications and measurable impact on developer productivity.

Shachar Itzhakyمشاهده پروفایل

دانشیار

• Program Synthesis
• Automated Reasoning
• Functional Programming
• +۵ مورد دیگر

Shachar Itzhaky is an Associate Professor in the Department of Computer Science at Technion - Israel Institute of Technology, Haifa. His research spans multiple areas of programming languages, formal methods, and software engineering, with a focus on making program development and verification more accessible and efficient. He has served on program committees for numerous prestigious conferences including PLDI, POPL, SPLASH, and ICFP. Dr. Itzhaky's research interests center around program synthesis, automated reasoning, and formal verification. His work in program synthesis explores techniques for automatically generating programs from high-level specifications, with applications in end-user programming and software development. In automated reasoning, he has made significant contributions to e-graph based reasoning, invariant inference, and property-directed verification. His research in formal methods focuses on practical applications for program verification, particularly for data structures and security properties. An analysis of his recent publications reveals a strong focus on leveraging advanced formal techniques for practical program understanding and generation. His work consistently bridges theoretical foundations with practical applications, particularly in program synthesis, verification, and end-user programming tools. The trend shows increasing integration of machine learning techniques with traditional formal methods, as well as expanding applications to security and privacy domains. ACM SIGPLAN John C. Reynolds Doctoral Dissertation Award Dr. Itzhaky has been actively involved in the programming languages research community, serving on numerous program committees and contributing to the advancement of formal methods and program synthesis. His work has practical implications for software development tools, security analysis, and end-user programming environments. While specific grant information isn't detailed in the provided text, his extensive publication record in top-tier venues suggests successful funding for his research endeavors. His work on projects like Object Spreadsheets and Lifty demonstrates a commitment to creating practical tools that address real-world programming challenges. Dr. Itzhaky's research is conducted within the vibrant programming languages and formal methods group at Technion's Computer Science department. His work intersects with multiple research threads including program synthesis, verification, and security, suggesting collaboration across these areas within the department. His tools like EPR-based Verification, PDR∀, and VeriCon represent significant technical contributions that likely form the basis of ongoing research projects with students and collaborators.

Adam Chlipalaمشاهده پروفایل

استاد

• Programming Languages
• Formal Methods
• Computer Systems
• +۵ مورد دیگر

Adam Chlipala is a Professor at the Massachusetts Institute of Technology working at the intersection of programming languages, formal methods, and computer systems. His research focuses on building practical verified systems with end-to-end machine-checked proofs, particularly using the Coq proof assistant. His educational background includes a Computer Science undergraduate degree from Carnegie Mellon University (2003) and a PhD in Computer Science from the University of California, Berkeley (2007). Following a postdoctoral position at Harvard University through 2011, he joined MIT as faculty. Chlipala's research spans multiple domains with strong emphasis on dependent types , verified compilation , and hardware-software co-verification . His work consistently bridges theoretical foundations with practical implementation, as evidenced by his development of the Ur/Web programming language and his focus on creating clean-slate hardware-software stacks with formal guarantees. Key research thrusts include cryptographic constant-time verification, side-channel security, and verified tensor compilation. His recent publications (2020-2025) reveal a clear trajectory toward increasingly complex verified systems, with growing emphasis on hardware-software integration, cryptographic implementations, and performance-critical applications. The work consistently leverages Coq for machine-checked proofs while addressing real-world constraints like timing channels and hardware interfaces. Chlipala is the author of the influential textbook Certified Programming with Dependent Types , which serves as a primary educational resource for Coq at numerous institutions worldwide. His professional activities include significant service to the PL community through program committees for major conferences including PLDI, POPL, ICFP, and CPP. He leads research initiatives connecting hardware and software verification, most notably through the DeepSpec project which aims to build fully verified computing stacks. His current work focuses on practical applications of dependent types for business applications through Ur/Web and verified cryptographic implementations.

Nadia Polikarpovaمشاهده پروفایل

دانشیار

• Program Synthesis
• Program Verification
• Type Systems
• +۲ مورد دیگر

Nadia Polikarpova is an Associate Professor in the Computer Science and Engineering Department at the University of California, San Diego. She leads the Programming Systems group and serves as a member of IFIP Working Group 2.8 on Functional Programming since 2022. Her academic journey includes a PhD from ETH Zurich (Switzerland) under Bertrand Meyer's supervision in 2014, followed by postdoctoral work at MIT CSAIL with Armando Solar-Lezama. Her research interests center around program synthesis, program verification, and type systems, with a focus on building practical tools that enhance software security and reliability. Polikarpova's work bridges theoretical foundations with real-world applications, particularly in the emerging area of AI-assisted programming. Her recent publications demonstrate a strong trajectory in program synthesis techniques, with increasing integration of machine learning approaches. The research spans from foundational type-driven synthesis methods to practical applications for validating AI-generated code and synthesizing heap-manipulating programs. Her work frequently appears in top-tier programming languages venues including PLDI, POPL, ICFP, and OOPSLA. 2020 Sloan Fellow 2020 Intel Rising Stars Award 2020 NSF CAREER Award Distinguished paper awards at PLDI'21, ICFP'20, and POPL'19 Best paper award at FM'15 Polikarpova actively mentors PhD students and has advised numerous graduates who now work at Microsoft Research, University of Michigan, and various tech companies. She teaches core programming languages courses including CSE 130 and specialized graduate courses on program synthesis (CSE 291). Her service to the community includes program committee roles for major conferences and co-chairing the Haskell conference in 2022.