جستجوی استاد راهنمای دانشگاهی

Albert Chengمشاهده پروفایل

استاد

• Real-Time Systems
• Cyber-Physical Systems
• Internet of Things (IoT)
• +۳ مورد دیگر

Professor Albert Cheng is a faculty member in the Department of Computer Science at the University of Houston. His research focuses on real-time systems, cyber-physical systems, smart cities, and embedded systems with societal impacts. He has authored over 270 publications and a textbook on real-time systems. Cheng holds roles as an Associate Editor for the IEEE Transactions on Knowledge and Data Engineering and ACM Computing Surveys. His research interests span real-time scheduling, machine learning applications, and systems optimization. Recent work includes vehicular traffic modeling for epidemiological risk reduction, quantum computing response time analysis, and satellite mission planning. Awards include Fulbright Specialist, Distinguished ACM membership, and IEEE Senior Member status. Cheng’s articles demonstrate expertise in real-time scheduling algorithms, cyber-physical systems development, and smart city infrastructure. His contributions bridge theoretical computer science with practical implementations in transportation, healthcare, and aerospace domains. Ongoing efforts include fault-tolerant systems, energy-efficient scheduling, and CPS education initiatives. Awards: Fulbright Specialist, ACM Distinguished Member, IEEE Senior Member, Institute of Physics Fellow Labs/Teams: Hewlett Packard Enterprise Data Science Institute (HPE DSI), Research Computing Data Core (RCDC)

Hakan Aydinمشاهده پروفایل

استاد

• Real-Time Embedded Systems
• Sustainable Computing
• Fault Tolerance
• +۴ مورد دیگر

Hakan Aydin is a Professor and Director of the PhD Program in the Department of Computer Science at George Mason University's Volgenau School of Engineering. He has been teaching at George Mason University since 2001 and has established himself as a leading researcher in real-time embedded systems and energy-aware computing. Education: PhD in Computer Science from the University of Pittsburgh (2001) Hakan Aydin's research primarily focuses on sustainable computing, real-time embedded systems, fault tolerance, Internet-of-Things, and cyber-physical systems. His work bridges theoretical foundations with practical implementations, particularly in energy management for real-time systems. He has developed innovative techniques for reliability-aware power management, dynamic voltage scaling, and energy harvesting in wireless sensor networks. His research has significant implications for extending battery life in mobile devices, improving reliability in safety-critical applications, and enabling sustainable computing practices. Aydin's publications reveal a consistent research trajectory centered around energy efficiency and reliability in real-time systems. His work spans theoretical algorithm development, system-level implementation, and experimental validation. A notable trend is the evolution from single-processor systems to multicore and heterogeneous architectures, reflecting industry trends. His recent work increasingly addresses security aspects of real-time systems and the integration of IoT technologies. Scientific Awards: National Science Foundation CAREER Award (2006) George Mason University Computer Science Department Teaching Award (2006, 2009) Best Paper Award at IEEE Green and Sustainable Computing Conference (IGSC'20) Best Student Paper Award at IEEE International Conference on Embedded Software and Systems (ICESS'15) Best Paper Award at IEEE International Conference on Embedded Computing (EmbeddedCom'14) Best Paper Award at International Workshop on Highly-Reliable Power-Efficient Embedded Designs (HARSH'13) Best Paper Award at ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWIM'11) Hakan Aydin has advised seven PhD students to completion, including Vinay Devadas (2011), Baoxian Zhao (2012), Bo Zhang (2012), Mohammad Atiqul Haque (2016), Maryam Bandari (2016), Arda Gumusalan (2019), and Abhishek Roy (2021). His research has been generously supported by the National Science Foundation through multiple grants, including CSR: Small: Collaborative Research: Towards Reliability-Centric Real-time Computing on Heterogeneous Chip Multiprocessor Systems (2014-2017), CSR: Small: Energy Harvesting for Performance Sensitive Wireless Sensor Networks (2011-2015), and CSR: Small: Collaborative Research: Generalized Reliability-Aware Power Management for Real-Time Embedded Systems (2010-2014). Prof. Aydin has held significant leadership roles in the academic community, serving as the Technical Program Committee Chair of the IEEE RTAS 2011 and General Chair of IEEE RTAS 2012. He is also a member of the Editorial Board of Journal of Real-Time Systems (Springer). His work has established foundational principles in reliability-aware energy management for real-time systems, influencing both academic research and industrial practices in embedded computing.

Alaa Alameldeenمشاهده پروفایل

دانشیار

• Computer Architecture
• Memory Systems
• Hardware Security
• +۵ مورد دیگر

Alaa Alameldeen is an Associate Professor in the School of Computing Science at Simon Fraser University (SFU), part of the Faculty of Applied Sciences. Previously, he worked as a Research Scientist at Intel Labs (2006–2020) and held an Adjunct Faculty position at Portland State University (2008–2018). He earned a PhD in Computer Sciences from the University of Wisconsin-Madison (2006), and earlier degrees from Alexandria University, Egypt. His research focuses on computer architecture, including memory systems (processing-in-memory, cache/memory compression, security), energy-efficient architectures, and hardware-software co-design for machine learning. He advises PhD and MSc students in these areas and teaches advanced computing science courses. Key contributions include innovations in memory hierarchies, cache compression techniques, and mitigating hardware vulnerabilities. His work has been published in top conferences (e.g., ISCA, MICRO, HPCA) and patented in areas like near-memory processing and error correction. Alameldeen currently leads a research group exploring secure and high-performance memory architectures. He has supervised multiple graduate students, with many progressing to roles at leading tech companies and academic institutions.

Abdullah Muzahidمشاهده پروفایل

دانشیار

• Computer Architecture
• Systems
• Artificial Intelligence
• +۵ مورد دیگر

Abdullah Muzahid is an Associate Professor in the Department of Computer Science and Engineering at Texas A&M University (since August 2024), previously serving as an Assistant Professor there since August 2018. Prior, he held an Assistant Professor role at the University of Texas at San Antonio (2012-2018). He earned his Ph.D. from the University of Illinois at Urbana-Champaign (2012), focusing on architectural support for debugging concurrency bugs under Prof. Josep Torrellas. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign (2012) M.S., Computer Science, University of Illinois at Urbana-Champaign (2009) B.S., Computer Science and Engineering, Bangladesh University of Engineering and Technology (2005) Research Interests: His work spans Computer Architecture , Systems , and Artificial Intelligence , with focus on multiprocessor architecture, parallel programming, debugging, and applying machine learning to system optimization. Recent projects include cache indexing via entropy estimation, DNN training acceleration, and hardware-software co-design for security. Awards: NSF CAREER Award (2017) Excellence in Research Award (UTSA, 2015 & 2017) W. J. Poppelbaum Award (UIUC, 2012) Intel Ph.D. Fellowship (2011) Grants & Advising: He leads NSF-funded projects on robust deep learning and stream processing systems. Advised 5 PhD graduates and currently mentors 4 PhD students. Served on program committees for ISCA, HPCA, MICRO, and as NSF panelist. Labs/Teams: Active in Texas A&M’s Computer Architecture group, collaborating on machine programming, hardware security, and AI-driven systems optimization.

Mendel Rosenblumمشاهده پروفایل

استاد

• System Software
• Distributed Systems
• Computer Architecture
• +۴ مورد دیگر

Mendel Rosenblum is the Cheriton Family Professor and holds dual appointments as Professor in the Departments of Computer Science and Electrical Engineering at Stanford University. He is a co-founder of VMware Inc. and served as its Chief Scientist for its first decade, playing a pivotal role in designing foundational virtualization technologies. Rosenblum's research focuses on system software, distributed systems, and computer architecture, with notable contributions to virtualization, data center networks, and operating systems. He leads the Platform Lab at Stanford, exploring next-generation data center technologies and high-performance computing systems. Administrative Role: Faculty Director of Stanford Computer Forum (2012–present) Education: PhD (UC Berkeley, 1992), MS (UC Berkeley, 1989), BA (University of Virginia, 1984) His research interests span disk storage management, computer simulation, scalable operating systems, and security. Recent work emphasizes deployable consensus algorithms, programmable smartNICs, and self-programming networks. Rosenblum has authored over 80 publications and holds multiple patents in virtualization and system software. Awards & Recognition: ACM System Software Award (2009) IEEE Computer Entrepreneur Award (2011) ACM Thacker Breakthrough in Computing Award (2018) Member, National Academy of Engineering (2013) He advises PhD and Master's students, including current advisees Sina Jandaghi Semnani and Zixi Liu. Rosenblum teaches advanced courses on web applications, distributed systems, and independent research projects.

Cong Liuمشاهده پروفایل

دانشیار

• Real-Time Systems
• Embedded Systems
• Cyber-Physical Systems
• +۳ مورد دیگر

Cong Liu is an Associate Professor of Computer Science at The University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. He joined UT Dallas in 2012 as an Assistant Professor and was promoted to his current rank. His research focuses on real-time and embedded systems, cyber-physical systems, and energy-efficient heterogeneous computing. Liu earned his Ph.D. in Computer Science from the University of North Carolina at Chapel Hill (2013), M.S. from Auburn University (2007), and B.E. from Wuhan University of Technology (2005). His research interests include real-time operating systems, cluster/cloud computing, and autonomous systems. He received the NSF CAREER Award in 2017 to develop algorithmic solutions for real-time data processing in autonomous vehicles and robotics. His work emphasizes GPU-accelerated embedded systems that enable autonomous decision-making in resource-constrained environments. Liu has held roles such as TPC member for IEEE RTAS and reviewer for multiple journals/conferences, including IEEE Transactions on Computers and Journal of Parallel and Distributed Computing. His publications address critical challenges in real-time scheduling, heterogeneous computing, and energy efficiency. He leads research on data-induced challenges in embedded systems, aiming to make autonomous driving systems predictable and controllable. Liu’s contributions bridge theoretical foundations with practical implementations in automotive and robotics domains.

Andrea Bastoniمشاهده پروفایل

پژوهشگر ارشد

• Real-Time Systems
• Cyber-Physical Systems
• Operating System Design
• +۵ مورد دیگر

Dr. Andrea Bastoni is a Postdoctoral Researcher and Research Fellow at the Chair of Cyber-Physical Systems in Production Engineering at Technical University of Munich (TUM), Faculty of Mechanical Engineering. He is also the CTO and co-founder of Minerva Systems , developing operating system solutions for AI-ready embedded applications. His expertise spans real-time operating systems, cyber-physical systems, and predictable system design for heterogeneous platforms. His research focuses on enhancing predictability of memory hierarchies in complex SoCs through techniques like memory bandwidth regulation and cache partitioning. This work has industrial applications in safety-critical domains such as avionics and railways, where he contributes to certifiable hypervisors and operating systems. As former Software Architect of the PikeOS hypervisor at SYSGO GmbH (2012-2020), he specialized in DO-178C, IEC 61508, and EN 50128 standards. His academic background includes a Ph.D. in Computer Engineering from the University of Rome Tor Vergata (2007-2011), where he developed LITMUS^RT as part of UNC's Real-Time Systems Group during a visiting researcher period (2009-2010). His publications reflect ongoing work on Multicore Real-Time Scheduling , Mixed-Criticality Task Isolation, and Arm DynamIQ shared unit analysis. He actively participates in program committees for conferences like RTSS, DSN, and DATE.

Rachid Guerraouiمشاهده پروفایل

استاد

• Distributed Computing
• Concurrent Computing
• Byzantine Fault Tolerance
• +۷ مورد دیگر

Rachid Guerraoui is a Full Professor at the École polytechnique fédérale de Lausanne (EPFL) where he leads the Distributed Computing Laboratory (DCL) within the School of Computer and Communication Sciences. He holds appointments in multiple departments including IC-SSC and IC-SIN for teaching, and serves on the IC Academic Evaluation Committee. A Moroccan/Swiss/French researcher, Guerraoui has previously been affiliated with Commissariat à l'Energie Atomique in Saclay, Hewlett-Packard Labs in Palo Alto, the Massachusetts Institute of Technology in Boston, and Collège de France in Paris. Guerraoui's research focuses on distributed and concurrent computing across various scales, from multiprocessors to wide-area networks. His work spans Byzantine fault tolerance, distributed machine learning, blockchain technologies, transactional memory, and consensus algorithms. His recent publications reveal a strong emphasis on Byzantine-resistant machine learning, decentralized learning systems, and the theoretical foundations of distributed consensus. The research demonstrates significant contributions to making distributed systems more robust, efficient, and secure against adversarial conditions. Guerraoui has received numerous prestigious awards including ACM Fellow (2012), Professor at College de France (2018), Nygaard-Dahl Award (2024), and Barroso Award (2025). His work has earned multiple best paper awards at top conferences including DISC, ICDCS, IPDPS, and ACM Middleware. He serves as Associate Editor of the Journal of the ACM (2010-2025) and has chaired program committees for major conferences such as PODC, DISC, and Middleware. As an educator, Guerraoui supervises numerous doctoral students and has mentored many successful researchers who now work at leading institutions and companies including Meta, Oracle Labs, Chainlink Labs, and Protocol Labs. He teaches courses on Distributed Algorithms and Concurrent Algorithms at EPFL, emphasizing both theoretical foundations and practical implementations. His educational initiatives include Wandida, a library of scientific e-synopses, and Zettabytes, projects aimed at making computer science accessible to broader audiences.

Elina Rönnbergمشاهده پروفایل

استاد

• Discrete Optimisation
• Mathematical Optimisation
• Scheduling
• +۱۸ مورد دیگر

Elina Rönnberg is a Professor and Deputy Head of Department at the Department of Mathematics, Linköping University, where she leads research in discrete optimisation and intelligent decision-making. Her work bridges theoretical method development and real-world applications in sectors such as healthcare, aviation, mining, and transportation. She is actively involved in the Wallenberg AI, Autonomous Systems and Software Program (WASP) and has collaborated with industry leaders like Saab and Scania. Her research focuses on advanced optimisation techniques including Dantzig-Wolfe decomposition, Lagrangian relaxation, column generation, branch-and-price, and logic-based Benders decomposition. She also explores hybrid methods combining mathematical programming with constraint programming and machine learning. Applications span nurse rostering, electric vehicle routing, aircraft arrival scheduling, and underground mine planning. Recent publications highlight a strong trend toward integrating AI and machine learning—particularly graph neural networks—with classical optimisation frameworks to accelerate solution methods. Her work emphasizes practical impact, robustness, and scalability in solving complex scheduling and resource allocation problems. Nurse Rostering with Strategic Planning of Skills for Sick-Leave Robustness (2024) Pricing for the EVRPTW with Piecewise Linear Charging (2024) Speeding Up Logic-Based Benders Decomposition with Graph Neural Networks (2024) Elina supervises several PhD students and has co-supervised doctoral research at international institutions including Makarere University (Uganda) and the University of Exeter (UK). She has contributed to applied projects through student theses in collaboration with Scania and Saab, focusing on electric vehicle routing and search-and-rescue optimisation. She previously served as a Specialist in Optimisation at Saab Aeronautics (2014–2020) and co-founded Schemagi, a scheduling tool aimed at improving quality in healthcare. She teaches courses such as Introduction to Optimization (TAOP07) and Project - Applied Mathematics (TATA62). Her research group, 'Mathematics and algorithms for intelligent decision-making,' operates within the Division of Applied Mathematics (TIMA) at the Department of Mathematics. The team develops decision support tools that enhance efficiency and sustainability in complex systems, particularly under the growing demands of electrification and digitalisation in transport and logistics.

Manolis G.H. Katevenisمشاهده پروفایل

استاد

• Computer Architecture
• VLSI Systems
• Interconnection Network Architecture
• +۴ مورد دیگر

Manolis G.H. Katevenis is a Professor at the Department of Computer Science, University of Crete, and Deputy Director and Head of the Computer Architecture and VLSI Systems (CARV) Laboratory at the Institute of Computer Science (ICS), Foundation for Research & Technology - Hellas (FORTH). He co-founded the European Research Center on Computer Architecture (EuReCCA) and is a founding partner of the European Network of Excellence on High-Performance and Embedded Architecture and Compilation (HiPEAC). PhD in Computer Science from University of California, Berkeley (1983) Co-founder of EuReCCA (2011) Contributed to RISC architecture (1980-1983), interconnection networks (1985-2011), and parallel computing (1993-2010) His research spans Scalable Multicore Systems , Interconnection Network Architecture , Packet Switch Design , Computer Architecture , and VLSI Systems . He has made foundational contributions to per-flow queueing, backpressure mechanisms, and wormhole IP over ATM, with applications in internet routers, data centers, and supercomputers. His publications focus on high-radix crossbar switches, flow control algorithms, and explicit interprocessor communication. Notable scientific awards include: ACM Doctoral Dissertation Award (1984) David J. Sakrison Memorial Prize (1983) IBM PhD Fellowship (1981-1983) Greek State Fellowship (1973-1978) He has supervised 40 graduate theses and participated in 22 R&D projects totaling €9M, including HiPEAC (coordinator of interconnection networks), SARC (FPGA prototype design), and ENCORE (cache-optimized remote DMA). His work has received over 2000 citations, with an h-index of 23.

John D. Kubiatowiczمشاهده پروفایل

استاد

• Computer Architecture
• Quantum Computing
• Distributed Systems
• +۷ مورد دیگر

Professor John D. Kubiatowicz is a faculty member at the University of California at Berkeley in the Department of Electrical Engineering and Computer Sciences since 1998. He holds a PhD in Electrical Engineering and Computer Science (minor in Physics) from MIT (1998), an M.S. in EECS (1993), and a double B.S. in Electrical Engineering and Physics (1987) from MIT. His research interests span Quantum Computing Architectures Distributed Systems and Storage Network Security and Peer-to-Peer Protocols Introspective and Manycore Operating Systems Edge and Fog Computing Hardware-Assisted Security He has pioneered systems like OceanStore , a global-scale distributed file system, and Tessellation , a manycore OS with continuous adaptation. The scientific awards he has received include Presidential Early Career Award (PECASE, 2000) Scientific American 50 (2002) Diane S. McEntyre Teaching Award (2003) IEEE ICRA Best Paper (2025) George M. Sprowls Award for MIT PhD thesis (1998) Okawa Research Grant (1998) Best Paper at International Conference on Supercomputing (1993) His recent publications focus on Quantum Circuit Design and Optimization Edge/Fog Computing Architectures Secure Runtime Systems Distributed Garbage Collection Manycore OS Innovations Hardware-Assisted Security Mechanisms He leads the Quantum Architecture Research Center and co-founded the SWARM Lab at Berkeley, advancing a vision of self-adapting, secure systems from the chip level to internet scale.

• Model-based Systems Engineering
• Safety-Critical Systems
• Systems Engineering
• +۳ مورد دیگر

Dr. Siyuan Ji is a Reader in Model-based Systems Engineering (MBSE) at Loughborough University, serving as Deputy Head of the Manufacturing, Systems & Management Academic Community and Deputy Director of the Doctoral Training Centre in MBSE. He previously held a Senior Lecturer position in Systems Engineering at the University of York, where he led the MSc Programme in Safety-Critical Systems Engineering. His academic journey includes a PhD and MSc in Physics from the University of Nottingham, followed by research roles in model-based systems engineering at Loughborough University. His research focuses on advancing model-based techniques for systems engineering, particularly in safety-critical systems, formal methods, and complex system design. He has contributed to areas such as hazard management (e.g., BSafeML framework), response time analysis in real-time systems, and model synchronization for requirements engineering. His work bridges theoretical foundations with practical applications in automotive systems, embedded software, and educational technology. Dr. Ji holds the title of Fellow of the Higher Education Academy and has published extensively on topics ranging from quantum technology reporting to conversational tutoring systems. His research emphasizes interdisciplinary collaboration, evident in projects like the EPSRC-funded analysis of vehicles as complex systems. He actively contributes to both academic and industrial advancements in systems engineering methodologies and education innovation. His professional roles include managing doctoral training programs, overseeing academic communities, and advancing systems engineering education. Collaborations span industry partnerships and international academic networks, reflecting his commitment to impactful research and training the next generation of systems engineers.

• Distributed Systems
• Embedded Systems
• Ubiquitous Computing
• +۳ مورد دیگر

NAKAJIMA, Tatsuo serves as a Professor at Waseda University's School of Fundamental Science and Engineering, Department of Computer Network Engineering. Holding a Doctor of Engineering from Keio University, he has been affiliated with Waseda since 1999 after positions at Japan Advanced Institute of Science and Technology (1993-1999), Cambridge University, and Carnegie Mellon University. His academic profile shows substantial research output with 433 papers and 3,338 citations on Scopus, and 7,604 citations with an h-index of 42 on Google Scholar. Dr. Nakajima's research focuses on Distributed Systems, Embedded Systems, and Ubiquitous Computing, with particular emphasis on virtualization architectures for embedded environments. His work bridges theoretical computer science with practical applications in information appliances, operating systems, and persuasive computing technologies. He has developed innovative systems including SPUMONE (a composition kernel for multi-OS environments), SIGMA System, and SPLiT (a performance optimization library for multicore processors). Analysis of his 15 most recent publications reveals a consistent research trajectory centered on enhancing reliability, security, and performance of embedded and pervasive computing systems. His work shows increasing integration of human factors, particularly in sustainable behavior applications through persuasive technology. The research spans from low-level system architecture to user-centered applications, demonstrating both technical depth and practical relevance. Nokia Research Center, Visiting Research Fellow (2005.04) Dr. Nakajima's research has produced numerous practical frameworks including SPUMONE for multi-OS environments, SPLiT for performance optimization, and persuasive applications like EcoIsland for sustainable behavior. His work on kernel monitoring, anomaly detection, and self-healing systems demonstrates strong focus on system dependability. Current research appears directed toward integrating human factors with embedded systems, particularly in environmental sustainability applications. His laboratory work centers around the SPUMONE project, a virtualization layer for multi-core embedded systems that enables multiple operating systems to coexist with minimal engineering cost. This research environment supports exploration of resource management, security monitoring, and performance optimization in embedded contexts. The work has practical applications in information appliances, smart homes, and pervasive computing environments.

Peter Suttonمشاهده پروفایل

دانشیار

• Engineering Education
• Embedded Computing Systems
• Reconfigurable Computing
• +۳ مورد دیگر

Associate Professor Peter Sutton is an academic at the University of Queensland (UQ), holding roles as Deputy Head of School (Teaching and Learning) and Associate Professor in the School of Electrical Engineering and Computer Science. His research focuses on Engineering Education, Embedded Systems, Reconfigurable Computing, and Electronic Design Automation. He has contributed to curriculum design, remote lab management during the pandemic, and hardware-software co-design for embedded systems. Sutton completed his undergraduate studies at UQ and earned advanced degrees at Carnegie Mellon University, with over three decades of experience in computer systems research and education. Education Bachelor of Science, University of Queensland Bachelor (Honours) of Engineering, University of Queensland Masters of Science (Coursework), Carnegie Mellon University Doctor of Philosophy, Carnegie Mellon University Research Interests Sutton’s work spans engineering pedagogy, embedded system design, and reconfigurable computing. Recent projects include adapting hands-on labs for remote learning during the pandemic and optimizing FPGA-based architectures for data compression and encryption. His contributions to cache optimization and multiprocessor systems highlight his expertise in hardware-software integration. Publications His 50+ publications cover topics like FPGA implementations of neural networks, code compression techniques for VLIW processors, and embedded system design tools. Notable contributions include frameworks for reconfigurable system-on-chip development and methods to enhance debugging practices in post-novice students. Labs & Teams He collaborates within UQ’s School of Electrical Engineering and Computer Science, contributing to research groups focused on embedded systems and engineering education innovation.

James H. Andersonمشاهده پروفایل

استاد

• Real-time systems
• Distributed computing
• Concurrent algorithms
• +۳ مورد دیگر

James H. Anderson is the Kenan Distinguished Professor and Department Chair in the Department of Computer Science at the University of North Carolina at Chapel Hill, where he has been a faculty member since 1993. A leading researcher in real-time systems and distributed computing, he previously served at the University of Maryland (1990-1993). His educational background includes: B.S. in Computer Science from Michigan State University (1982) M.S. in Computer Science from Purdue University (1983) Ph.D. in Computer Sciences from the University of Texas at Austin (1990) Anderson's research focuses on real-time systems, distributed and concurrent algorithms, multicore computing, and operating systems. His work addresses fundamental challenges in scheduling, resource management, and reliability in time-critical environments, with recent emphasis on GPU acceleration for AI workloads and heterogeneous platforms. He investigates novel approaches to budget enforcement, processing graph scheduling, and timing predictability in complex systems. Analysis of his recent publications reveals a strong trend toward applying real-time scheduling principles to GPU and heterogeneous computing architectures. Key research thrusts include enabling predictable AI acceleration, managing timing uncertainties in autonomous systems, and developing composable resource partitioning techniques for safety-critical applications. His distinguished honors include: U.S. Army Research Office Young Investigator Award (1995) Alfred P. Sloan Research Fellowship (1996) Seven Computer Science Student Association Teaching Awards (1995-2019) Fellowships from IEEE (2012), ACM (2013), AAAS (2020), and AAIA (2022) IEEE TCRTS Outstanding Technical Achievement and Leadership Award (2018) Anderson actively mentors through the TOPICS Club, a reading group for undergraduate students that he co-leads with Cynthia Sturton and Danielle Szafir. His professional leadership includes chairing IEEE TCRTS (2016-2017) and ACM SIGBED (2019-2021), plus service as program/general chair for major conferences including RTSS, PODC, ECRTS, and RTAS. He directs ongoing research initiatives in real-time systems through collaborative projects and the TOPICS Club, which provides undergraduates with hands-on research experience in cutting-edge computer science topics.