جست‌وجوی استاد و پژوهشگر

• Database Systems
• Distributed Systems
• Machine Learning Systems
• +۳ مورد دیگر

Tim Kraska is an Associate Professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) within the School of Engineering. His research spans foundational areas in modern data systems: Database Systems Distributed Systems Machine Learning Systems Learned Indexes Cloud Databases Dr. Kraska pioneers the integration of machine learning into core database components, developing "learned systems" that replace traditional algorithms with ML models for significant performance gains. His work on learned indexes redefined indexing paradigms, while recent research extends this approach to garbage collection, query optimization, and concurrency control. His publication trends reveal a strategic shift toward applying ML to low-level systems problems, particularly in memory management and runtime optimization as demonstrated by his PLDI 2020 paper on Learned Garbage Collection. Award highlights include: ACM SIGMOD Jim Gray Doctoral Dissertation Award VLDB Early Career Research Contribution Award Marie Curie Fellowship At MIT, he leads a research group focused on next-generation data systems, securing grants from NSF and industry partners to explore the theoretical and practical boundaries of learned components in database engines. His team collaborates extensively with industry research labs on real-world deployment challenges. As a core member of CSAIL's distributed systems group, he contributes to MIT's leadership in reimagining data infrastructure for the AI era through cross-lab initiatives on scalable machine learning systems.

Brandon Luciaمشاهده پروفایل

استاد

• Intermittent Computing
• Energy-harvesting Systems
• Concurrency
• +۷ مورد دیگر

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.

Christos Ouzounisمشاهده پروفایل

استاد

• Bioinformatics
• Digital Biology
• Biological Computation
• +۵ مورد دیگر

Christos Ouzounis is a Professor of Bioinformatics at the Department of Informatics, Aristotle University of Thessaloniki , with a career spanning institutions including the European Bioinformatics Institute , King's College London , and University of Toronto . His work bridges Computational Biology , Digital Biology , and Metagenomics , focusing on large-scale data analysis, machine learning applications, and functional annotation of proteins. Education : BSc in Biological Sciences (1986), MSc in Biological Computation (1987), and DPhil in Computational Chemistry (1993) Key Roles : Director of the Bioinformatics Centre at King's College London (2007-2010), Research Director at IDEP-EKETA (2014-2020) His research interests include low-complexity protein sequences , Covid-19 seasonality patterns linked to UV radiation, and metagenomic analysis of urban microbiomes in cultural heritage sites. Current projects involve machine learning models for microbial coexistence networks, ontological classification of biomedical literature, and bioinformatics tool development . Publications highlight trends in archaeal genomics , functional dark matter in metagenomics, and epidemiological modelling . Notable collaborations include work on BioTextQuest v2.0 for concept discovery and MjCyc for metabolic pathway analysis.

Vikram S. Adveمشاهده پروفایل

استاد

• Compilers
• Programming Languages
• Parallel Computing
• +۶ مورد دیگر

Vikram S. Adve is a Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. He co-founded and co-leads the Center for Digital Agriculture and directs the USDA-funded AIFARMS Institute , focusing on AI applications in sustainable agriculture. His research bridges compilers, parallel systems, and AI to address challenges in edge computing and digital farming. Research interests span compiler technologies (LLVM, HPVM), parallel programming models , software reliability , and AI-driven agriculture . Key projects include: CropWizard : Generative AI for agricultural decision-making. HPVM/ApproxHPVM : Compiler IR for edge devices. Hydride/MISAAL : Automated retargetable compiler construction. Recent publications (2018-2025) emphasize compiler optimizations, approximate computing, binary analysis, and AI for systems. Trends show convergence of compiler techniques , heterogeneous computing , and AI applications in agriculture and edge devices. Adve actively recruits students for projects funded by USDA, Intel, Amazon, and Illinois DPI. He leads the HPVM compiler team and digital agriculture initiatives , integrating cross-disciplinary research across CS, engineering, and agronomy.

Steve Blackburnمشاهده پروفایل

استاد

• Memory Management
• Garbage Collection
• Virtual Machine Design and Implementation
• +۷ مورد دیگر

Steve Blackburn is a research scientist at Google DeepMind and professor of computer science at the Australian National University in the College of Engineering and Computer Science. His primary research focus is on programming language implementation, with expertise spanning memory management, virtual machines, and performance analysis. He has served in significant leadership roles including Associate Dean for Diversity and Inclusion (2016-2019) and as Program Chair for PLDI 2015 and General Chair for PLDI 2023. Blackburn's research interests center on making software run faster and more power-efficiently on modern hardware. His primary areas include microarchitectural support for managed languages, fast and efficient garbage collection, and the design and implementation of virtual machines. He maintains a strong interest in sound methodology and infrastructure for successful research innovation. His work bridges theoretical computer science with practical systems implementation, with particular focus on memory management frameworks and performance benchmarking. His publication record reveals a consistent focus on memory management systems, with recent work exploring garbage collection in modern contexts including CRuby, Julia, mobile devices, and memory-disaggregated datacenters. His research shows an evolution from foundational garbage collection algorithms toward practical implementations addressing real-world constraints in contemporary programming languages and hardware platforms. A notable trend is his increasing focus on quantifying and understanding the true costs of garbage collection in production environments. Fellow of the ACM Blackburn has supervised numerous doctoral students including Zhen He, John Zigman, Robin Garner, Ting Cao, and currently advises Wenyu Zhao, Zixian Cai, and others. He has also served on multiple program committees for major conferences including PLDI, ASPLOS, ISMM, and OOPSLA, demonstrating his significant contributions to the programming languages and systems research community. His service includes editorial roles for ACM Transactions on Programming Language Applications and Systems from 2017-2020. He leads two major research infrastructure projects: the MMTk memory management framework and the DaCapo benchmark suite, both of which have become foundational tools for researchers in programming languages and systems. These projects reflect his commitment to shared research infrastructure and reproducible methodology in systems research.

Arthur Azevedo de Amorimمشاهده پروفایل

استادیار

• Programming Languages
• Formal Verification
• Security
• +۳ مورد دیگر

Arthur Azevedo de Amorim is an Assistant Professor in the Department of Computer Science at the Rochester Institute of Technology's College of Computing. His research focuses on making software more secure and reliable using techniques based on formal verification, programming languages, and type systems. Previously, he held postdoctoral positions at Boston University and Carnegie Mellon University after completing his Ph.D. at the University of Pennsylvania under Benjamin Pierce and co-advised by Cătălin Hrițcu. His educational background includes undergraduate studies in computer science and engineering at Unicamp and Polytechnique. He is also one of the authors of Software Foundations, an introductory textbook to the Coq proof assistant, and maintains an active blog about Coq. Dr. de Amorim's research spans several critical areas in programming languages and security. His work on cryptographic protocols leverages recent advances in program verification (particularly separation logic) to verify cryptographic protocols. His research on compartmentalization analyzes formal guarantees of techniques for limiting the scope of vulnerabilities in low-level languages like C and C++. These research areas reflect his commitment to bridging theoretical foundations with practical security applications. His recent publications demonstrate strong activity across multiple top-tier conferences including POPL, PLDI, CCS, and ICALP, with research spanning formal verification, secure compilation, differential privacy, and programming language theory. His work consistently combines theoretical rigor with practical applications in security and reliability. Dr. de Amorim has served on numerous program committees for major programming languages conferences including POPL, PLDI, ICFP, and CoqPL, demonstrating his active engagement with the research community. He has also contributed to important educational resources through his work on Software Foundations. He currently advises several graduate students at RIT working on various aspects of programming languages and security. His lab develops multiple open-source software projects including Cryptis (for verifying cryptographic protocols), Deriving (a Coq library for automating class instances), and Extructures (a Coq library of finite data structures).

Costas Vassilakisمشاهده پروفایل

استاد

• Information systems
• Semantic web technologies
• Service-oriented architectures
• +۴ مورد دیگر

Costas Vassilakis is a Professor in the Department of Informatics and Telecommunications at the University of Peloponnese, serving as Dean of the Faculty of Economics and Technology since 2019. He holds a PhD from the University of Athens (1995) and has held academic roles since 2005, including Associate Professor and Visiting positions. His research focuses on information systems, semantic web technologies, and cultural informatics, with contributions to projects like Virtual Museums and SmartGov. He leads initiatives in digital cultural heritage, cybersecurity, and smart agriculture. Notable projects include Experimedia Blue for personalized cultural experiences and Cyber-Trust for IoT security. Active in teaching, he has instructed courses on operating systems, software engineering, and real-time systems. He contributes to academic governance, including roles in the University Council and strategic planning units. His work bridges technology and cultural preservation, emphasizing interdisciplinary innovation. Education: PhD in Informatics, University of Athens (1995); MSc equivalent in Informatics, University of Athens (1990). Research Interests: Focuses on recommenders systems, collaborative filtering optimization, cybersecurity frameworks, and AI applications in agriculture. Active in cultural heritage digitization, museum technologies, and VR systems. Recent Projects: Includes TripMentor (tourism platform), PaloAnalytics (market analytics), and Rehabotics (rehabilitation robotics). Leads EN.I.R.I.S.S.T., a national infrastructure for maritime and logistics research. Awards: No explicit awards listed, but recognized through extensive project leadership and academic roles.

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.

• Personalized Software Technology
• Mobile Device Programming
• Web Programming
• +۴ مورد دیگر

Evangelos Sakkopoulos is an Associate Professor at the Department of Computer Science, University of Piraeus, specializing in Custom Software Technology. He holds a PhD from the Department of Computer Engineering and Informatics at the University of Patras. His research focuses on personalized software systems, mobile programming, web development, and data privacy solutions. He has contributed over 60 publications in international journals and conferences, with expertise in frequent itemset hiding algorithms, AI-driven e-learning systems, and smart home security technologies. Education: PhD in Computer Engineering and Informatics (University of Patras) Research interests include: Personalized Software Technology Mobile Device Programming Web Programming Data Privacy and Security Machine Learning Applications His work spans e-government systems, maritime surveillance technologies, and cultural heritage preservation through AI. Recent projects address challenges in digital identity management, EU policy compliance, and adaptive learning environments. Over 150 academic publications reflect his contributions to privacy-preserving data mining, smart home safety, and mobile healthcare systems.

Peter O'Hearnمشاهده پروفایل

استاد

• Separation Logic
• Program Verification
• Static Analysis
• +۵ مورد دیگر

Peter O'Hearn is a Professor of Computer Science at University College London and Research Scientist at Meta AI (FAIR), renowned for co-developing separation logic which bridges theoretical computer science and industrial-scale program analysis. His dual affiliation exemplifies the synergy between academic research and practical tool development that characterizes his career. His research interests focus on program verification , separation logic , static analysis , and his recent groundbreaking work on incorrectness logic as a complementary approach to traditional verification. O'Hearn pioneered the concept of local reasoning which enables modular verification of large codebases by focusing only on relevant memory regions, forming the theoretical foundation for Facebook Infer. His publications reveal a consistent trajectory from foundational theory to industrial application, with recent work emphasizing Scalable verification for million-line codebases Compositional reasoning for concurrent systems Practical deployment of formal methods in developer workflows Bug-oriented reasoning through incorrectness logic His research consistently addresses the tension between theoretical soundness and practical applicability in program analysis. Notable scientific awards include: 2021 IEEE Cybersecurity Award for Practice 2016 Gödel Prize for separation logic 2016 CAV Award for outstanding contributions POPL 2019 Most Influential Paper Award Fellow of the Royal Society (FRS) Fellow of the Royal Academy of Engineering (FREng) O'Hearn has made substantial contributions to industrial practice through Facebook Infer, which analyzes millions of lines of code daily across Meta's codebase. His work on continuous reasoning integrates formal verification into developer workflows, while his recent focus on incorrectness logic addresses the critical need for effective bug detection in large systems. He maintains active leadership in the programming languages community through conference organization and keynotes.

Metafas Dimitriosمشاهده پروفایل

مدرس

• Real-Time Software development
• System-On-a-Chip design
• DSP architectures
• +۴ مورد دیگر

Metafas Dimitrios is a Lecturer in the Department of Electrical and Electronic Engineering at the University of West Attica, School of Engineering. His office is located in Building Z, Room ZB201. He holds a Doctoral Degree from the University of Patras (1993) and an Electrical Engineering Diploma (1987). His research focuses on Real-Time Software, System-On-a-Chip design, DSP architectures, and applications of AI/Machine Learning in games and education. Teaches courses such as Introduction to Programming, Algorithms and Data Structures, and UML-based system design methodologies. Active in interdisciplinary research, including educational technology and embedded systems. Recent work emphasizes AI-driven educational tools and reinforcement learning applications in gaming. Earlier contributions span wireless communication systems, VLSI design, and hardware-software co-development.

Evangelos H. Papakitsosمشاهده پروفایل

مدرس

• Natural Language Processing
• Digital Humanities
• Systems Science
• +۶ مورد دیگر

Dr. Evangelos H. Papakitsos serves as a Lecturer in the Department of Industrial Design and Production Engineering at the University of West Attica. A physicist by training (National & Kapodistrian University of Athens, 1987), he holds advanced degrees in Information Systems (University of Liverpool, 1992) and Informatics (National & Kapodistrian University of Athens, 2000), with postdoctoral specialization in Semantic Lexical Databases. His academic journey spans four higher education institutions since 1993, including National Technical University of Athens and National & Kapodistrian University of Athens. His research spans interdisciplinary domains at the intersection of technology and humanities, with primary focus on Natural Language Processing , Digital Humanities , and Systems Science . Key research thrusts include computational linguistics for ancient scripts (particularly Linear A and Indus Valley), energy harvesting systems, environmental physics applications, and robotics for defense and environmental monitoring. His recent publications (2021-2025) demonstrate strong activity in nanotechnology applications for water purification, unmanned vehicle systems, and computational approaches to linguistic decipherment. Dr. Papakitsos has developed significant expertise in bridging engineering disciplines with humanities through his work on: Machine-readable dictionaries for ancient scripts Energy harvesting applications in civil infrastructure Computational analysis of historical linguistics Environmental monitoring robotics His laboratory work centers on Electronic Automation, Telematics and Cyberphysical Systems, reflecting his systems-oriented approach to complex interdisciplinary problems. Teaching responsibilities include undergraduate courses in General Physics, Optimization Methods, and Fluid Mechanics, plus postgraduate instruction in Automation Information Systems, Energy Management, and Unmanned Systems within the "Unmanned Autonomous and Remotely Piloted Systems" program. His educational background in career counseling informs interdisciplinary approaches to curriculum development, particularly evident in his work on the systemic evaluation of tourism marketing strategies during the pandemic.

Saksham Goelمشاهده پروفایل

استادیار

• Programming Languages
• Compilers
• Memory Management
• +۳ مورد دیگر

Saksham Goel serves as an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay, where he conducts research at the intersection of programming languages and systems engineering. His research focuses on advanced memory management techniques, with core expertise in: Garbage collection algorithms and optimizations Compiler design for memory safety Runtime systems for efficient resource utilization Program analysis for liveness domains Dr. Goel's work demonstrates significant contributions to memory management systems, particularly through his ISMM 2020 publication on finite liveness domains. His research addresses critical challenges in reducing memory overhead while maintaining performance in modern programming environments, with applications spanning cloud infrastructure and latency-sensitive applications. He actively participates in premier programming languages conferences including PLDI and its co-located events, contributing to the advancement of compiler technology and runtime systems through both theoretical frameworks and practical implementations.

David Greggمشاهده پروفایل

استاد

• Software performance optimization
• Embedded systems
• Accelerating deep neural networks on embedded systems
• +۱۲ مورد دیگر

David Gregg is a Professor in the Department of Computer Science at Trinity College Dublin's School of Computer Science and Statistics, where he serves as Global Director for Computer Science (since 2020) and previously as Head of the Discipline of Software and Systems (2018-2022). His research focuses on software performance optimization and embedded systems, with particular expertise in accelerating deep neural networks on resource-constrained platforms. He teaches Systems Programming (CS2014/5) and Concurrent Systems I (CS3014). Gregg's research spans multiple areas of computer systems including: Compiler optimization and program analysis Processor microarchitecture and parallelism (multi-core, vector, instruction-level) Computer arithmetic and domain-specific languages Low-energy embedded systems and FPGA implementations Deep neural network acceleration He has served on numerous program committees including PACT, PLDI, CC, and other major computer systems conferences, and has been on the Board of Distinguished Reviewers for ACM TACO multiple times. Professor Gregg has advised numerous PhD and MSc students, many of whom have gone on to prominent positions at companies like Intel-Movidius, Google, Amazon, and Synopsys. He leads the triNNity project which includes optimized libraries and compilers for implementing convolutional neural networks on CPUs.