جست‌وجوی استاد و پژوهشگر

Fan Laiمشاهده پروفایل

استادیار

• Machine Learning Systems
• Cloud Computing
• Networked Systems
• +۳ مورد دیگر

Dr. Fan Lai is an Assistant Professor at the Department of Computer Science, University of Illinois Urbana-Champaign (UIUC) , where he leads research at the intersection of Machine Learning, Systems, and Computer Networking . His work focuses on building practical systems for efficient GenAI applications across cloud and planetary scales, with real-world adoption by companies like Meta, LinkedIn, and Cisco . Education : Ph.D. in Computer Science from the University of Michigan (2023) Previous Roles : Systems Research@Google, Meta AI Research areas include: Cloud ML Systems (LLMs, Image/VideoGen, DLRMs) Collaborative Learning (Federated Learning, Edge-Cloud ML, Hyperscale Training) ML for Systems (Resource Management, Network Optimization) Recent publications span top conferences like SOSP'25, MICRO'25, MLSys'25, SIGMOD'25 , covering topics from LLM serving to distributed training compression . Awards include ACM SIGOPS Honorable Mention , David J. Kuck Dissertation Prize , and ML and Systems Rising Stars . Teaching includes CS 498: Machine Learning Systems and CS 598: Systems for GenAI . Actively mentoring PhD and MS students in ML systems research, with prior mentees transitioning to institutions like Princeton and UW .

• Distributed Machine Learning
• Cyber Security
• Edge Computing
• +۲ مورد دیگر

Zhengxin Yu is a Lecturer at Lancaster University , affiliated with the School of Computing and Communications . She obtained her Ph.D. in Computer Science from the University of Exeter (UK) in 2021. Current Position: Lecturer in Security and Protection Science Department: Computing and Communications Research Groups: Security Lancaster (Distributed Systems, Secure Machine Learning and Intelligence, Systems Security) Her research focuses on Distributed Machine Learning , Cyber Security , and Edge Computing . Key contributions include advancing federated learning frameworks, robust caching mechanisms in multi-edge systems, and privacy-preserving decentralized learning architectures. Recent publications (2022–2025) highlight her work in federated learning, edge computing, reinforcement learning, and adversarial defense. Trends include optimizing resource allocation in blockchain-enabled systems, modeling mobile edge computing performance, and enhancing resilience in distributed environments. PhD Students: Marta Adamska, Daria Smirnova, Yushi Wang Labs/Teams: Security Lancaster, with subgroups in Distributed Systems and Systems Security

Carrie Plummerمشاهده پروفایل

دانشیار

• Health Equity
• Social and Structural Drivers of Health
• Community Health
• +۱ مورد دیگر

Dr. Carrie Plummer is an Associate Professor at the Vanderbilt University School of Nursing (VUSN) since 2008. She holds a PhD from the University of Tennessee Health Sciences Center (UTHSC), an MSN from Vanderbilt, and a BA from Swarthmore College. Her research focuses on Health Equity, Social and Structural Drivers of Health, Community Health, and Interprofessional Education. She pioneered the 'Drug Disposal' event in Dickson, TN, addressing medication accumulation (CACHES) and its health impacts. Her clinical work includes geriatric inpatient care and community health initiatives. Dr. Plummer is active in organizations like ANA, TNA, and STTI, and serves on drug disposal coalitions. She has received numerous awards, including the 2022 Dean's Award for Clinical Excellence and the 2013 Julia Hereford Faculty Award. Her teaching emphasizes interprofessional collaboration and innovative simulations for prelicensure students.

Shawn Rossمشاهده پروفایل

استاد

• Digital Archaeology
• Pre-Classical Greece
• Oral Tradition as History
• +۳ مورد دیگر

Shawn Ross is a Professor of History and Archaeology at Macquarie University, serving as Director of Strategic Initiatives in Digitally Enabled Research. He holds a PhD from the University of Washington and has held academic roles at institutions including the University of New South Wales and William Paterson University. His research focuses on digital archaeology, pre-Classical Greece, Thracian archaeology, and IT applications in field research. Ross co-leads the Tundzha Regional Archaeology Project (TRAP) and directs the FAIMS project, developing digital infrastructure for archaeology. He has held leadership roles such as Deputy Head of School at UNSW and led Macquarie’s research data management initiatives. Ross also serves as Product Manager for the ARDC’s Research Activity Identifier (RAiD), managing national research infrastructure portfolios. Education: PhD in History, University of Washington (2001) MA in History, University of Washington (1996) BA in History, Whitman College (1993) Research Interests: Ross bridges archaeology and digital technology, emphasizing field data systems, Thracian and Greek studies, oral tradition analysis, and interdisciplinary collaboration. His work on the Tundzha Project examines Thracian societal evolution, while FAIMS advances open-source tools for field data capture. His ARDC roles focus on global research identifiers and infrastructure. Grants & Projects: Includes ARC-funded TRAP (2009–2011), FAIMS3 redevelopment ($150k), and leadership in the Perachora Peninsula Archaeological Project. Recent work involves machine learning applications in burial mound prediction and geospatial data crowdsourcing. Labs/Teams: Leads the Centre for Ancient Cultural Heritage and Environment (CACHE), FAIMS consortium, and collaborates internationally on archaeological surveys and digital infrastructure.

Santosh Pandeمشاهده پروفایل

استاد

• Compiler Analysis
• Software Optimization
• Hardware Security
• +۶ مورد دیگر

Santosh Pande is a Professor and Associate Chair for Graduate Studies at the School of Computer Science , Georgia Institute of Technology. He is affiliated with the Center for Experimental Research in Computer Systems (CERCS) and the Online Master of Science Computer Science (OMSCS) program. His research focuses on compiler analysis and optimizations, particularly in enhancing software properties through static and dynamic analysis. Key areas include hardware security (e.g., side-channel attacks on secure processors), real-time systems (converting interactive software behavior into quantifiable metrics), and parallel computing (optimizing SAT solvers and GPU scheduling). His work bridges compiler design with security, embedded systems, and machine learning, supported by grants from NSF, ONR, DARPA, and industry. Research Highlights: Side-channel attack mitigation on XOM secure processors Framework for soft real-time software analysis Compiler-guided security defenses (e.g., Pythia, Decker) High-performance RF emulation architectures His publications emphasize compiler-driven security, real-time computing, and algorithmic optimization. Over 100+ papers and open-source tools reflect his commitment to advancing compiler theory and practice. Current projects apply these techniques to machine learning algorithms, enhancing their efficiency and security.

Alexey Tumanovمشاهده پروفایل

استادیار

• Machine Learning
• Distributed Systems
• Resource Management
• +۴ مورد دیگر

Alexey Tumanov is an Assistant Professor in the School of Computer Science at Georgia Institute of Technology, part of the College of Computing. His research focuses on systems for machine learning, resource management, and scheduling in distributed environments. He holds a PhD from Carnegie Mellon University and conducted postdoctoral research at UC Berkeley under Ion Stoica. Previously, he worked at the University of Toronto and in industry on cloud computing and datacenter systems. Education: PhD in Computer Science, Carnegie Mellon University (2019) Postdoc, UC Berkeley RISELab (2019) MSc in Computer Science, University of Toronto (2012) BSc in Computer Science, University of Toronto (2010) Research Interests: Tumanov's work addresses challenges in distributed machine learning, including efficient resource management for inference and training pipelines, scheduling algorithms for soft-real-time systems, and federated learning. His lab (SAIL) develops systems like SARATHI-SERVE and RocketKV to optimize LLM inference and co-scheduling. He emphasizes practical deployments in healthcare (HOLMES) and cloud environments. Key Contributions: Ray distributed framework for AI (OSDI 2018) ESCHER scheduler for ephemeral cloud resources (SoCC 2022) InferLine ML pipeline orchestration (SoCC 2020) Awards: NSERC CGS-D3 Scholarship (2016) Best Paper at EuroSys 2016 (TetriSched) Google PhD Fellowship Nominee (2018) Lab & Teaching: Leads the Systems for Artificial Intelligence Lab (SAIL) at Georgia Tech. Teaches advanced courses on operating systems (CS3210) and systems for ML (CS8803-SMR). Supervises 15+ graduate students across PhD and MS programs.

• Distributed Systems
• Cloud Computing
• High-Performance Computing
• +۳ مورد دیگر

Thilo Kielmann is an Associate Professor at the Vrije Universiteit Amsterdam, holding positions in the Faculty of Science (Computer Systems department) and the Network Institute. His research focuses on distributed systems, cloud computing, and high-performance computing, with emphasis on resource management, data locality, and scalable infrastructure. He has authored 95+ research outputs and supervised 8 PhD theses. Education details are not explicitly listed, but his academic role implies advanced qualifications in computer science. His work contributes to UN Sustainable Development Goals through innovative computing solutions. Research interests include distributed file systems (e.g., MemEFS), resource disaggregation, energy-efficient scheduling (e-BaTS), and scalable VM management. His publications span conferences like HPDC and journals like Future Generation Computer Systems. No scientific awards are explicitly mentioned. He teaches four courses, including Computer Programming and Large Research Project in Computer Science. Labs/teams involvement is not detailed, but his research collaborations and conference roles (e.g., HPDC15 Chair) suggest active participation in academic networks.

Nikolaos Pappasمشاهده پروفایل

دانشیار

• Semantic Wireless Communications
• Age of Information
• Stochastic Modelling
• +۷ مورد دیگر

Nikolaos Pappas is an Associate Professor and Docent at Linköping University's Department of Computer and Information Science (IDA), within the Database and Information Techniques (ADIT) division. His research focuses on semantic wireless communications, age of information, stochastic modeling of communication networks, and wireless energy harvesting systems. He leads the Communications for Networked Intelligent Systems Group and serves as an editor for several IEEE journals, including the IEEE Transactions on Machine Learning in Communications and Networking. Education: B.Sc./M.Sc./Ph.D. in Computer Science and Mathematics from the University of Crete (2005–2012). Postdoctoral roles at Supélec (France) and Linköping University (2012–2016). Marie Curie Fellow (2014–2016). Research Interests: Includes semantic communication, tactile internet, IoT, queueing theory, and 6G network architectures. He is a voting member of the IEEE Tactile Internet Working Group and Principal Investigator for projects like 'Semantics-Empowered Communication for Networked Intelligent Systems' (Swedish Research Council, 2022–2025). Awards: Recognized in the Top 2% Scientists List (2020–2023) for Networking and Telecommunications. Leading Horizon Europe projects such as ROBUST-6G and ETHER, focusing on 6G security and hybrid terrestrial/satellite networks. Teaching: Courses on Age of Information, Statistical Learning, and Network Virtualization. Supervises a large team of PhD students and postdocs in ADIT.

• Computer Hardware Design
• Smart Cities
• Cybersecurity
• +۶ مورد دیگر

Dr. Issam Damaj is a Senior Lecturer in Computer Science at Cardiff Metropolitan University's Department of Applied Computing and Engineering. He holds a PhD from London South Bank University (2004), an MSc from the American University of Beirut (2001), and a BSc from Beirut Arab University (1999). His academic journey includes 17 years in professorial roles across universities in Lebanon, Kuwait, and Oman. Research & Expertise Fields of Interest: Hardware design, smart cities, cybersecurity, electric vehicles, and technical education. Key Projects: FPGA implementations of chaotic systems, vehicular network caching, and sustainable e-mobility infrastructure. Leadership Roles: ABET Program Evaluator, IEEE Senior Member, and founding counselor of the AUK IEEE Student Branch. Recent Research Trends His recent work spans intelligent systems for healthcare hygiene, cybersecurity in multinational operations, and FPGA-optimized algorithms. Themes include IoT-driven solutions, blockchain integration for recommendations, and sustainable energy systems. Recognition & Awards Recipient of multiple awards in mentoring, research, and academic distinction. Second Place in the Best Student Branch Award (2017, AUK IEEE). Collaborations & Impact Dr. Damaj collaborates with global institutions and industries to bridge academic research with real-world applications in engineering education and technology innovation.

Susan Eisenbachمشاهده پروفایل

استاد

• Smart Contracts
• Blockchain Technology
• Software Systems
• +۳ مورد دیگر

Susan Eisenbach served as a Professor and Head of the Department of Computing at Imperial College London from January 2010 to September 2016, followed by roles as Dean of Learning and Teaching and Director of Studies. Her research focuses on software systems, smart contracts for blockchain, and specification languages for large open systems. She retired in 2020 during the pandemic and received a notable farewell via email. Her academic leadership spans over three decades at Imperial, including contributions to curriculum development and pedagogical innovation. She has supervised numerous PhD and Master’s students, many funded by prestigious grants (e.g., EPSRC, Microsoft Research). Her awards include the Imperial College Teaching Fellow (2002) and recognition for the LEXIS exam invigilation system (Best Applied Paper, 2001). Publications highlight her work on formal verification, programming language design, and blockchain technologies. Her articles address topics like memory layout optimization, smart contract safety, and garbage collection algorithms. Eisenbach’s service includes roles on programme committees (ECOOP, OOPSLA) and external reviews for institutions like Trinity College Dublin and KTH. She contributed to ACM committees and IFIP working groups, emphasizing education and programming language standards.

• Computer Networks
• Network Security
• Multimedia Communication
• +۴ مورد دیگر

Christos Papadopoulos is a Professor and Sparks Family Chair of Excellence in Global Research Leadership in the Department of Computer Science at the University of Memphis. He joined the university in Fall 2020, coming from Colorado State University where he held a professorial position. His expertise spans computer networks, network security, multimedia communication, and distributed systems. He holds a DSc in Computer Science from Washington University in St. Louis (1999). Dr. Papadopoulos' research focuses on advancing secure and efficient network architectures, particularly in vehicular networks and Named Data Networking (NDN). He has led collaborative projects to create open platforms for sharing vehicle telematics data and improving cybersecurity in automotive systems. His work often bridges theoretical contributions with practical implementations, addressing challenges in data privacy, network scalability, and real-time communication. His recent publications reflect a strong emphasis on autonomous systems, cybersecurity datasets, and innovative applications of NDN in scientific data management. He has contributed to foundational work in internet measurement, traffic analysis, and privacy-preserving techniques for wide-area networks. Notable grants include collaborative NSF-funded initiatives on privacy in internet measurements, open telematics data platforms, and NDN-based solutions for big science projects. His research has implications for transportation safety, environmental monitoring, and secure communication protocols. Dr. Papadopoulos is actively involved in academic leadership, including editorial roles and conference organization. His interdisciplinary approach integrates computer science with environmental and automotive engineering, fostering cross-sector innovation.

• Machine Learning
• Deep Learning
• eHealth
• +۴ مورد دیگر

Dr. Gaetano Manzo is a Researcher at the HES-SO Valais-Wallis - School of Management , focusing on Machine Learning , eHealth , and Recommender Systems . He holds a BSc in Management Information Systems and leads research in agent-based systems for healthcare support, data-driven clinical decision frameworks, and vehicular networking optimization. His research interests include: Digital transformation in healthcare Explainable AI for medical decision support Personalized health-assistant chatbots Privacy-preserving data sharing Context-aware recommendation systems Key publication trends (2020-2025) show expertise in: Agent-based modeling for cancer survivor support Rule extraction from neural networks Floating content optimization in vehicular networks Weak supervision techniques for clinical datasets Multicultural streaming media recommendations He has contributed to projects like: The Ark (REPS-CITI Real Estate PaaS) Regional Development Axis (2019) for local innovation support

Nj Mukherjeeمشاهده پروفایل

پژوهشگر

• Systems
• Computer Science
• Operating Systems
• +۳ مورد دیگر

Nj Mukherjee is a Researcher in the Computer Science Department at Carnegie Mellon University, holding the role of Doctoral Research Assistant. Advised by Professor George Amvrosiadis, their work focuses on advancing systems research with an emphasis on memory management, file systems, and storage optimization. Key projects include innovations in TLB utilization via Mosaic Pages and SSD-optimized file systems like BetrFS. Contact details include office 6507 in the Gates and Hillman Centers and email nirjhar@cmu.edu . Research Interests Nj’s systems research explores cutting-edge challenges in memory hierarchy design, external-memory data structures, and storage efficiency. Their work spans theoretical algorithmic contributions (e.g., Affine/PDAM models) to practical system implementations addressing modern hardware constraints. Recent efforts include rethinking paging strategies for low-associativity caches and optimizing file system cloning through Copy-on-Abundant-Write mechanisms. Advising & Grants As a doctoral student, Nj collaborates closely with their advisor on foundational systems research. No specific grant funding details are disclosed in the provided information.

Larry Rudolphمشاهده پروفایل

استاد پژوهشی

• Mobile Computing
• Pervasive Computing
• Computer Networks
• +۷ مورد دیگر

Larry Rudolph is a Research Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds the role of Principal Research Scientist and has been a key contributor to projects like the Oxygen Research Group and the Computational Structures Group (CSG). His academic journey includes roles as a Full Professor at the Hebrew University of Jerusalem and postdoctoral research at the University of Toronto. Rudolph specializes in pervasive computing, mobile systems, and virtualization, with notable contributions to Bluetooth technology and location-aware computing. He has advised numerous students and pioneered courses such as MIT's 6.883 Pervasive Human-Centric & Mobile Computing. Education: PhD in Mathematics, Courant Institute, NYU (1977-1981) Postdoc in Computer Science, University of Toronto (1981-1982) Research Faculty, Carnegie-Mellon University (1982-1986) Full Professor, Hebrew University (1986-1997) Research Interests include mobile device virtualization, privacy in pervasive systems, and adaptive algorithms for personal data management. He co-founded Redigi, a marketplace for digital music resale, and led VMware's Mobile Virtualization Project. His work emphasizes experimental approaches to computer science, integrating hardware and software innovations. Notable Projects: Bluetooth Essentials for Programmers (book, 2007) Oxygen Research Group (2000-2005) Virtualization and pervasive computing systems Advising and Collaborations: Guided over 15 students to completion of Master’s and PhD theses Co-organizer of DOE Supercomputer Valuation and Workshop on Job Scheduling Contributions to CSAIL and NECSI (New England Complex Systems Institute) Labs/Teams: Active in CSAIL's Pervasive Computing initiatives and Oxygen sub-projects. Current focus includes mobile phone security, privacy-aware systems, and adaptive learning frameworks for personal data tagging.

Daniel Sanchezمشاهده پروفایل

استاد

• Computer Architecture
• Systems & Networking
• Parallel Computing
• +۵ مورد دیگر

Dr. Daniel Sanchez is a Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), where he leads the Computation Structures Group within the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on computer architecture, scalable systems, and memory hierarchies, with particular emphasis on multicore and many-core systems, quality-of-service guarantees, and runtime systems. Education: Ph.D. in Electrical Engineering, Stanford University (2012) M.S. in Electrical Engineering, Stanford University (2009) B.S. in Telecommunications Engineering, Technical University of Madrid (UPM) (2007) Research Interests: Dr. Sanchez’s work spans computer architecture innovations such as cache partitioning (KPart), software-defined caches (Jenga), and accelerators for sparse computing (Azul, Terminus). He designs systems that enhance performance, energy efficiency, and scalability in modern computing environments. His projects include the Swarm Architecture for ordered parallelism and architectures supporting fully homomorphic encryption. Articles Trends: Recent publications emphasize accelerators for sparse algorithms, cryptographic hardware (e.g., Fully Homomorphic Encryption), and high-performance computing. His work bridges hardware-software co-design to tackle challenges in irregular applications, memory hierarchies, and secure computing. Awards & Grants: No scientific awards explicitly listed, but his work has been recognized in top conferences (e.g., MICRO, ISCA). Advising & Teaching: He advises over 20 Ph.D. and master’s students, including current advisees Axel Feldmann and Hyun Ryong Lee. He teaches courses like 6.5900 Computer System Architecture and 6.191 Computation Structures at MIT. Labs & Teams: Leader of the Computation Structures Group at MIT CSAIL, collaborating with researchers like Joel Emer, Srini Devadas, and Armando Solar-Lezama. His team explores cutting-edge architectures and systems for next-generation computing.