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Timothy M. Jones is a Professor of Computer Architecture and Compilation at the University of Cambridge Computer Laboratory, where he leads research in systems-level computing. He is also a Fellow at Gonville and Caius College, contributing to academic leadership and student mentorship within the collegiate system. His primary affiliation with the Computer Laboratory positions him at the forefront of systems research within the university. Dr. Jones's research focuses on extracting various forms of parallelism (thread-level, data-level, memory-level) to enhance computational performance while addressing energy efficiency and reliability challenges. His work spans compiler design, binary translation, and microarchitecture optimization, with specific interest areas including: Compiler technologies for functional and parallel programming Hardware reliability and fault tolerance mechanisms Binary analysis and instrumentation frameworks Memory system optimization and virtual memory management Security enhancements through binary modification Runtime systems for heterogeneous architectures Analysis of his recent publications reveals strong emphasis on systems-level innovation, particularly in fault tolerance techniques, binary analysis tools, memory optimization, and parallel execution frameworks. His work consistently bridges theoretical computer science with practical hardware implementation challenges. Dr. Jones maintains active participation in the academic community through conference leadership roles, including serving as Program Co-Chair for CGO 2026 and committee positions at premier venues including ISMM, CGO, and ECOOP. He contributes to open-source academic resources through GitHub and maintains professional engagement via Twitter.

• Compilers
• Computer Architecture
• Binary Modification
• +3 more

Christos Makris is an Associate Professor in the Department of Computer Engineering and Informatics at the University of Patras, Greece. His academic career spans over two decades with significant contributions to computer science, particularly in data structures, algorithms, and information systems. He maintains active research collaborations and supervises graduate students in his areas of expertise. Dr. Makris's research spans several key areas in computer science with a strong focus on efficient data organization and processing. His work encompasses Data Structures , Information Retrieval , Data Mining , String Management and Processing Algorithms , Computational Geometry , Internet Technologies , Bioinformatics , and Multimedia Databases . His interdisciplinary approach bridges theoretical computer science with practical applications across various domains including web technologies, bioinformatics, and emergency response systems. Analysis of Dr. Makris's publication record reveals a consistent research trajectory focused on efficient algorithms for information management. His work demonstrates evolution from foundational data structure research in the 1990s to more applied work in web technologies, social media analysis, and machine learning applications in recent years. A notable pattern is his ability to adapt core algorithmic techniques to emerging application domains while maintaining theoretical rigor. Dr. Makris maintains an impressive scholarly record with over 3,000 citations, an h-index of 29, and an i10-index of 71 according to Google Scholar metrics. These indicators reflect the significant impact of his research within the computer science community. As an active faculty member, Dr. Makris maintains regular office hours on Tuesdays from 18:00-20:00 and Thursdays from 12:00-14:00. He is accessible via email at makri@ceid.upatras.gr or makri@upatras.gr for academic inquiries and student supervision.

• Data Structures
• Information Retrieval
• Data Mining
• +5 more

Ntzoufras Ioannis is a Professor in the Department of Statistics at the Athens University of Economics and Business (AUEB), School of Information Sciences and Technology, where he has served continuously since 2004 (promoted to Professor in 2015). Previously, he held teaching positions at the University of the Aegean (2000-2004) and completed military service (1999-2000). Education B.Sc. in Statistics and Insurance Science (1994) M.Sc. in Statistics with Application in Medicine, University of Southampton (1995, with distinction) Ph.D. in Statistics, Athens University of Economics and Business (1999) Research Focus His work centers on Bayesian and computational statistics , specializing in categorical data analysis, statistical modeling, and variable selection methodology. He develops sophisticated models for applications in medical research (clinical trials, risk estimation), psychometrics (latent variable models), and sports analytics (football/basketball modeling), with emphasis on computational efficiency and real-world implementation. Publication Trends Recent publications (2023-2025) reveal three dominant trends: (1) Advanced Bayesian variable selection methods for high-dimensional data, (2) Sports analytics applications in football (goal modeling, competitive balance) and basketball (in-play performance), and (3) Development of specialized R packages (ssifs, PEPBVS) for statistical computation. His work consistently bridges theoretical innovation with practical domain applications. Scientific Awards Lefkopouleion Prize for Greece's best statistics thesis (1999-2000) PROSE Award Honorable Mention for 'Bayesian Modeling Using WinBUGS' (2010) Academic Leadership He has supervised graduate students across AUEB's Statistics, Business Analytics, and Data Science programs, and taught postgraduate courses at the University of Athens (Biostatistics), University of the Aegean (Business Administration), and Italian institutions (University of Pavia, Universita Cattolica, University of Bicocca-Milan). As General Secretary of the Greek Statistical Institute (2006-2007), he advanced national statistical initiatives. Research Community He founded and maintains grstats (http://grstats.forumotion.net/), Greece's primary online statistics community, facilitating collaboration among 1,200+ statisticians and data scientists through forums, workshops, and resource sharing.

• Bayesian Statistics
• Computational Statistics
• Categorical Data Analysis
• +6 more

Scott Mahlke is a Professor and Associate Chair in the Electrical Engineering and Computer Science Department at the University of Michigan. He is affiliated with the Advanced Computer Architecture Laboratory and the Software Systems Laboratory, where he leads the Compilers Creating Custom Processors (CCCP) research group. His research focuses on compilers, computer architecture, and high-level synthesis, with particular emphasis on designing next-generation computer systems that overcome challenges in performance, power consumption, and reliability. His work bridges the gap between hardware and software through innovative compiler technology that enables customized processors and accelerators. Mahlke's publications demonstrate a strong focus on compiler techniques for exploiting instruction-level parallelism, memory system optimization, and application-specific processor design. His research spans from fundamental compiler algorithms to practical implementations in both general-purpose and embedded systems. National Science Foundation CAREER Award (2003) Morris Wellman Faculty Development Assistant Professor (2004) 2006 ISCA Most Influential Paper Award Multiple best paper awards at major architecture conferences As an advisor, Mahlke has chaired numerous Ph.D. dissertations and actively mentors graduate students in the CCCP group. His research is generously funded by the National Science Foundation, Gigascale Systems Research Center, ARM Ltd., Samsung Advanced Institute of Technology, and other major organizations. The CCCP group maintains strong industry partnerships that facilitate the transfer of research innovations to practical applications.

• Compilers
• Computer Architecture
• High-level Synthesis
• +5 more

Maria Virvou serves as Professor and Chair of the Department of Informatics at the University of Piraeus, where she also directs the Graduate Program in Informatics and leads the Research Laboratory 'Software Technology'. She holds significant institutional leadership roles including membership in the University Senate and has chaired the Department of Informatics for multiple terms. As Editor-in-Chief of Springer book series 'Learning and Analytics in Intelligent Systems' and 'Artificial Intelligence-Enhanced Software and Systems Engineering', she maintains substantial academic influence across international scholarly platforms. Dr. Virvou earned her PhD in Computer Science and Artificial Intelligence from the University of Sussex with a scholarship from the State Scholarships Foundation, a Master of Science in Computer Science from University College London, and her undergraduate degree from the Department of Mathematics at the National and Kapodistrian University of Athens. Her educational background in both mathematics and computer science has provided a strong foundation for her interdisciplinary research approach. Professor Virvou's research spans Software Technology, Artificial Intelligence, Educational Software and Games, User Modeling, and Human-Computer Interaction. She has pioneered work in personalized interactive software systems, applying fuzzy logic and machine learning techniques to create adaptive educational environments. Her recent work demonstrates a strategic expansion into AI applications for healthcare, with significant contributions to medical diagnostics using large language models and multimodal AI systems. She has also made notable advances in smart tourism applications through personalization techniques. With over 400 publications to her name, Professor Virvou's scholarly output shows a clear progression from foundational work in user modeling toward increasingly sophisticated AI applications across multiple domains. Her publication trends reveal a strategic focus on explainable AI, multimodal systems, and practical implementations that bridge theoretical advances with real-world applications, particularly in healthcare and education sectors. Ranked #1 worldwide in 'User Modelling' publications (147,450 total publications) according to Scopus Ranked #1 worldwide in 'Educational Software' publications according to both Scopus and Microsoft Academic Search Recognized among the top 2% of most influential Artificial Intelligence scientists worldwide by Stanford University General Co-Chair at the 14th IISA Conference 2023 Invited Keynote Speaker at the 35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023) As Director of the Research Laboratory 'Software Technology', Professor Virvou has built a robust research team focused on AI applications across multiple domains. She co-founded and co-chairs the IEEE Intelligent Information Systems and Applications international conference series, creating a significant platform for scholarly exchange. Her leadership extends to editorial roles with major academic publishers and active participation in international research collaborations that have secured substantial funding for innovative projects in AI and software engineering.

• Software Technology
• Artificial Intelligence
• Educational Software
• +5 more

Jovan Stojkovic is an incoming Assistant Professor at the Department of Computer Science at the University of Texas at Austin, set to join in Fall 2026. Prior to his appointment at UT Austin, he will spend a year at Meta working with the AI and Systems Co-design group. His research focuses on cloud computing and datacenters, with particular emphasis on cloud-native workloads and machine learning inference. Education: PhD in Computer Science from the University of Illinois at Urbana-Champaign, advised by Professor Josep Torrellas Undergraduate studies at the School of Electrical Engineering, University of Belgrade, Serbia, where he was recognized as the best student of the Computer Engineering and Information Theory Department every year from 2017-2020 Research Interests: Jovan's research focuses on cloud computing and datacenters , with two primary domains: Cloud-native workloads , such as microservices and serverless computing. He investigates how to co-design novel hardware platforms and software systems that deliver orders-of-magnitude improvements in performance, energy efficiency, and resource utilization for these emerging workloads. Machine Learning (ML) inference , particularly large language models (LLMs). His work addresses the challenges of ML inference through smart scheduling, workload placement, and system-level configuration tuning to reduce energy, power, and thermal overheads while maintaining performance and accuracy guarantees. Publication Trends: Jovan's publications demonstrate a strong focus on optimizing cloud infrastructure for emerging workloads. His research spans across serverless computing, microservices, and large language model inference. A clear trend emerges in his work: addressing the performance, energy efficiency, and resource utilization challenges of modern cloud workloads through innovative hardware-software co-design approaches. His most recent work shows increasing focus on LLM inference optimization, particularly in the areas of thermal management, power efficiency, and scheduling for many-adapter environments. Awards and Honors: HPCA Best Paper Award (2025) IEEE MICRO Top Picks Honorable Mention (2024) 6 patents with IBM and Microsoft on: Serverless systems, Processor overclocking in the cloud, and Energy-efficient LLM inference W. J. Poppelbaum Memorial Award (2025) for hardware and architecture innovation Mavis Future Faculty Fellowship (2024–2025) Invited to present at 11th Heidelberg Laureate Forum (2024) Kenichi Miura Award (2022) for excellence in High Performance Computing Multiple student travel grants to ISCA, MICRO, ASPLOS, and HPCA Advising and Grants: Jovan is actively seeking prospective PhD students for his research group at UT Austin. His research has been supported through collaborations with major tech companies including IBM, Microsoft, and Meta. His six patents with IBM and Microsoft demonstrate the practical impact of his research in serverless systems, processor overclocking, and energy-efficient LLM inference. His work on serverless computing (MXFaaS, EcoFaaS) and LLM inference optimization has received significant recognition in top-tier computer architecture conferences. Research Groups: During his PhD at UIUC, Jovan worked with Professor Josep Torrellas on cloud infrastructure research. He has collaborated extensively with researchers at IBM Research (particularly Hubertus Franke) and Microsoft (particularly Íñigo Goiri and Ricardo Bianchini). His upcoming position at UT Austin will establish his independent research group focused on cloud computing and datacenter systems. His year at Meta working with the AI and Systems Co-design group will further strengthen his expertise in AI infrastructure.

• Cloud Computing
• Datacenters
• Cloud-Native Workloads
• +7 more

John Regehr is a Professor at the School of Computing, University of Utah, specializing in compilers, software testing, and formal verification. His research develops tools to improve software correctness and efficiency, including Csmith (random C program generator) and C-Reduce (test-case reducer). His group focuses on compiler validation, fuzzing techniques, and superoptimization, primarily targeting the LLVM infrastructure. Research interests span compilers, testing methodologies, formal verification, embedded systems, and program analysis. Recent work emphasizes practical tools backed by formal methods to detect and prevent software errors. Publications demonstrate strong trends in compiler verification and testing, with consistent focus on LLVM optimization correctness, translation validation, and automated bug detection through fuzzing and synthesis techniques. Scientific awards include: PLDI 2015 Distinguished Paper Award ICST 2014 Best Paper Award ACM SIGSOFT Distinguished Paper Award Leads a research group developing tools like Souper (superoptimizer) and Alive2 (translation validator). Maintains active academic service through program committees (PLDI, CGO, OOPSLA) and contributes to open-source compiler infrastructure.

• Compilers
• Software Testing
• Formal Verification
• +3 more

Brandon Lucia is a Full Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. He leads the abstract research group focusing on the intersection of computer architecture, systems, and programming languages. His work bridges theoretical foundations with practical implementations in energy-constrained environments. Lucia's research centers on intermittent computing systems and edge computing in extreme environments. His work on energy-harvesting systems has established fundamental principles for batteryless computing, while his orbital edge computing research pioneers computational intelligence for nanosatellite constellations. These research thrusts address critical challenges in reliability, efficiency, and programmability for systems operating under severe power constraints. His publication record shows a clear evolution from foundational work on intermittent computing models to sophisticated applications in space computing and edge intelligence. Recent publications demonstrate increasing integration of dataflow architectures with energy-harvesting constraints, particularly in satellite constellations where computational resources must be managed across distributed, power-constrained platforms operating in extreme environments. NSF CAREER Award (2017) IEEE TCCA Young Computer Architect Award (2019) Sloan Foundation Fellowship (2021) ASPLOS Best Paper Awards (2018, 2020) OOPSLA Distinguished Paper and Artifact Awards (2015) Lucia actively mentors numerous PhD students including Brad Denby, Zhuo Cheng, and Emily Ruppel, many of whom contribute significantly to his research program. His abstract research group maintains strong industry connections while pursuing fundamental advances in computing systems. The group has developed multiple open-source tools including Legerdemain for program analysis and MultiCacheSim for cache coherence simulation. His laboratory work spans from theoretical foundations of intermittent computing to practical implementations in space systems. Current projects include computational nanosatellite constellations, energy-minimal dataflow architectures, and secure edge computing systems that operate reliably despite frequent power failures.

• Intermittent Computing
• Energy-harvesting Systems
• Concurrency
• +7 more

Heather Miller is a tenure-track Assistant Professor in the Software and Societal Systems Department within Carnegie Mellon University's School of Computer Science. Her academic journey includes prior roles as an Assistant Clinical Professor at Northeastern University's College of Computer and Information Science and as Executive Director of the Scala Center at EPFL. Miller's research centers on distributed and concurrent computation through the lens of programming languages, with particular emphasis on data-centric systems, big data processing, and edge computing. A defining theme throughout her work is composability - enabling construction of complex distributed systems through composition of components that are correct by construction. Her projects span distributable closures, flexible serialization techniques, futures and promises for asynchronous programming, and deterministic concurrent dataflow models. Her recent publications demonstrate strong trends in applying programming language theory to practical distributed systems challenges, with increasing focus on WebAssembly instrumentation, microservice resilience, and language model pipelines. This evolution reflects her commitment to bridging theoretical foundations with real-world system requirements. Dahl-Nygaard Junior Prize (2023) Mentorship forms a significant component of Miller's academic work. She actively supervises multiple PhD, MS, and undergraduate researchers at CMU, including Christopher Meiklejohn, Matthew Weidner, Huairui Qui, Ria Pradeep, and Luke Dramko. Her service contributions span numerous top-tier conferences including PLDI, SPLASH, ECOOP, and ICSE where she has served as committee member, chair, and keynote speaker. Miller co-founded the Curry On conference to foster industry-academia dialogue, hosting successful editions in Prague, Rome, Barcelona, Amsterdam, and London. She leads research groups focused on distributed programming models and maintains strong industry connections through Two Sigma, where she holds an affiliation. Her work consistently emphasizes practical open-source implementations, primarily within the Scala ecosystem where she's been a core contributor since 2011.

• Distributed Systems
• Concurrent Programming
• Programming Languages
• +4 more

Evangelos Papapetrou is an Associate Professor in the Department of Computer Science and Engineering at the University of Ioannina, Greece. He holds a Diploma (1998) and PhD (2003) in Electrical and Computer Engineering from Aristotle University of Thessaloniki. His research focuses on wireless and mobile networks, including mobile ad-hoc networks, opportunistic networks, satellite networks, quality of service (QoS), and network coding. He has contributed to over 50 peer-reviewed publications and actively participates in EU/nationally funded projects. Research interests include: Wireless/Mobile Network Architectures Opportunistic and Social Mobile Networks Satellite Communication Systems Network Coding Techniques Routing Protocol Design His work emphasizes practical implementations of network protocols, with recent trends focusing on ultra-reliable low-latency communication, energy-efficient broadcasting, and protocol optimizations for 5G/IoT environments. He has developed simulation tools like Adyton for opportunistic networks and contributed to privacy-preserving routing solutions. Teaching responsibilities include courses on Computer Networks I and Wireless Networks (2024/25). He maintains active IEEE/ACM memberships and serves on conference review committees.

• Wireless Networks
• Mobile Networks
• Satellite Networks
• +5 more

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.

• Web Engineering
• Web Application Performance Optimization
• Web Code Quality
• +7 more

John Paparrizos is an Assistant Professor of Computer Science and Engineering at The Ohio State University's College of Engineering, where he directs The DATUM Lab (Data Analytics, Understanding, Mining, and Management Lab). He maintains an adjunct affiliation with the School of Informatics at Aristotle University of Thessaloniki. His research spans databases, data science, machine learning, and artificial intelligence , with focus areas including: Time-series analysis (clustering, anomaly detection) Scalable data mining for structured/unstructured data Adaptive algorithms for resource-constrained environments Foundational technologies for data-intensive applications His work addresses real-world challenges across relational, time-series, multimedia, text, graph, web, and IoT data domains. Notable recognition includes: 2025 ACM SIGMOD Test-of-Time Award for k-Shape time-series clustering 2023 IEEE TCDE Rising Star Award ACM SIGMOD Research Highlight Award NetApp Faculty Award His research has been featured in New York Times (front page), Washington Post , Forbes , and adopted by Fortune 500 companies (Exelon, Nokia) and the European Space Agency. He actively serves on program committees for premier conferences including ACM SIGMOD, VLDB, IEEE ICDE, ACM SIGKDD, and NeurIPS. His open-source tools have exceeded 100,000 downloads and are integrated into academic curricula at Brown, Columbia, Purdue, and University of Chicago.

• Databases
• Data Science
• Machine Learning
• +5 more

Panagiotis Hadjidoukas is an Associate Professor and Head of the Laboratory for Computing at the Computer Engineering and Informatics Department, University of Patras, within the School of Engineering. His work focuses on high-performance computing systems and parallel programming models. His research spans parallel and distributed computing , runtime support for parallel programming models , and automation of AI/ML workloads . Key contributions include developing the torc runtime system for task parallelism and pioneering work in extreme-scale scientific simulations. His interests bridge theoretical computer science with practical applications in scientific computing and AI acceleration. Notable achievements include the ACM Gordon Bell Prize Winner (2013) for 11 PFLOP/s cloud cavitation simulations and Finalist (2015) for in-silico lab-on-a-chip microfluidics. His software tools ( torc_lite , torcpy ) enable efficient parallelism across diverse architectures. Doctor of Philosophy (2003), University of Patras Master of Science (2001), University of Patras Diploma in Computer Engineering (1998), University of Patras As Head of the Laboratory for Computing, he leads infrastructure development while maintaining active research collaborations with IBM Research and ETH Zurich. His teaching portfolio includes graduate courses on high-performance computing for data sciences and parallel processing principles.

• Parallel Computing
• Distributed Systems
• High Performance Computing
• +3 more

Dimitrios Apostolopoulos serves as Assistant Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), within the Division of Information Transmission Systems and Material Technology. His academic foundation was built at NTUA where he earned both Diploma (2004) and Ph.D. (2009) degrees, followed by an MBA from Hellenic Open University. His educational qualifications include: Diploma in Electrical and Computer Engineering, NTUA (2004) Ph.D. in Electrical and Computer Engineering, NTUA (2009) MBA, Hellenic Open University Prof. Apostolopoulos specializes in optical communication systems, optical wireless technologies, and converged optical-wireless networks, with particular expertise in photonic integrated circuits for telecom/datacom/sensing applications and optical computing for AI. His research directly addresses next-generation network challenges through photonic innovation, bridging theoretical frameworks with practical engineering solutions for 5G/B5G/6G systems. Analysis of his 2024-2025 publications reveals dominant themes in 6G hybrid transport architectures (fiber/FSO/mmWave), silicon photonics for aerospace environmental sensing, and integrated optical components for Lidar/gas detection systems. This work demonstrates consistent progression from fundamental photonic research to real-world deployment scenarios. His scientific recognition includes: Dimitris N. Chorafas Foundation Award (2009) for doctoral contributions to all-optical broadband communications Prof. Apostolopoulos actively leads over 15 European/national research projects while serving on technical committees for ECOC, IEEE GLOBECOM, and N&N conferences. As co-chair of EuCNC/6G Summit's Wireless/Optical/Satellite Networks track, he shapes next-gen network standards. His teaching portfolio spans undergraduate telecommunications courses from circuit analysis to optical network design. He maintains active collaboration within photonic research teams through projects like Int5Gent and Int5gent, focusing on integrated solutions for communications infrastructure and sensing applications across aerospace and environmental monitoring domains.

• Optical Communication Systems
• Optical Wireless Technologies
• Converged Optical-Wireless Networks
• +2 more

Michael D. Bond is a Professor in the Department of Computer Science & Engineering at Ohio State University's College of Engineering. He leads the Programming Languages and Software Systems (PLaSS) Research Group, which focuses on designing program analyses and software and hardware systems that enhance computing reliability, scalability, and security. His academic service includes general chair for PLDI 2027, program committee membership for multiple top conferences, and committee roles in SIGPLAN Research Highlights (2024-2027). Professor Bond's research spans programming languages, systems, and security, with particular expertise in memory management, concurrency, hardware transactional memory, information flow control, and predictive race detection. His work bridges theoretical foundations with practical implementations, as evidenced by numerous open-source projects accompanying his publications. The PLaSS group has made significant contributions to understanding and improving memory models, developing efficient garbage collection techniques for modern architectures, and creating novel approaches to secure programming in languages like Rust. Analysis of his recent publications reveals a clear trajectory toward addressing security and reliability challenges in modern computing systems, particularly through language-based approaches. His work increasingly focuses on Rust programming language security mechanisms, memory disaggregation for datacenters, and advanced techniques for detecting and preventing concurrency bugs. The research demonstrates strong continuity in exploring memory models and concurrency while adapting to emerging hardware trends and security challenges. Outstanding Teaching Award, Department of Computer Science and Engineering, Ohio State University (2018) Lumley Research Award, College of Engineering, Ohio State University (2016) OOPSLA 2015 Distinguished Paper and Artifact Awards NSF CAREER Award ACM SIGPLAN Outstanding Doctoral Dissertation Award Intel PhD Fellowship Professor Bond actively mentors several PhD students including Chujun Geng, Vincent Beardsley, Chris Xiong, Victor Chen, and Noah Charlton, with external co-advisee Zixian Cai at Australian National University. His research is currently supported by multiple NSF grants including SaTC-2348754 (2024-2027), CyberCorps-2336531 (2024-2029), and CSR-2106117 (2021-2025), reflecting sustained funding for his work in information flow control, security, and systems research. The PLaSS Research Group maintains a strong presence in both academic and industrial communities, with graduated PhD students securing positions at major technology companies like Google, Amazon Web Services, and Huawei, as well as academic positions at institutions like UIUC and IIT Kanpur. The group's work combines theoretical rigor with practical implementation, consistently producing open-source artifacts that enable reproducibility and further research in the systems and programming languages community.

• Programming Languages
• Systems
• Security
• +6 more