جستجوی استاد راهنمای دانشگاهی

Xupeng Miaoمشاهده پروفایل

استادیار مهمان

• Machine Learning Systems
• Distributed Computing
• Data Management
• +۵ مورد دیگر

Xupeng Miao is a Visiting Assistant Professor in the Department of Computer Science at Purdue University, holding the Kevin C. and Suzanne L. Kahn New Frontiers Assistant Professorship. Previously, he was a Postdoctoral Fellow at Carnegie Mellon University's Catalyst Group under Professors Zhihao Jia and Tianqi Chen. He earned his Ph.D. in Computer Science from Peking University (2022) and a Bachelor’s degree from Northeastern University. His research focuses on machine learning systems, distributed computing, and data management, with notable contributions to systems like Hetu (a distributed deep learning framework) and innovations in large language model (LLM) serving (e.g., SpotServe, SpecInfer). He has received awards including the 2024 WAIC Yunfan Award and an Outstanding Paper Award at ACL 2024. Current projects emphasize efficient systems for generative AI, including optimizing LLM training and inference on heterogeneous hardware, fault-tolerant distributed training, and scalable graph-based machine learning. He teaches CS 59200-MLS: Machine Learning Systems at Purdue and actively mentors students in PhD/MS programs and internships. Key achievements include NVIDIA Academic Awards, IEEE Micro Top Picks recognition, and leadership in international conference roles (e.g., Artifact Evaluation Co-Chair for KDD 2025 and MLSys 2025). His work bridges system design, algorithmic innovation, and hardware-aware optimizations to advance scalable AI infrastructure.

Giovanni De Micheliمشاهده پروفایل

استاد

• Integrated Circuit Design
• Hardware Synthesis
• Logic Optimization
• +۵ مورد دیگر

Giovanni De Micheli is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), holding appointments in both the School of Computer and Communication Sciences (IC) and the School of Engineering (STI). He is affiliated with the Integrated Systems Laboratory (LSI) and serves as Scientific Director of EcoCloud. His primary office is located in INF 341 building at EPFL's Lausanne campus where he conducts research and teaching activities. Professor De Micheli's research spans multiple domains in electronic design automation and integrated circuit design. His primary interests include: Integrated Circuit Design and Hardware Synthesis Logic Optimization and Boolean Methods Nanoelectronics and 2D Electronics Quantum Computing and Emerging Technologies Low-Power Electronics and Energy-Efficient Systems Electronic Design Automation for Novel Computing Paradigms His recent publications demonstrate a strong focus on advancing logic synthesis techniques for both conventional and emerging technologies. Professor De Micheli's work bridges theoretical foundations with practical applications, particularly in adapting traditional EDA methods to novel computing paradigms like quantum computing and superconducting electronics. His research group has made significant contributions to the development of efficient algorithms for circuit optimization across multiple technology domains, with particular emphasis on area, power, and delay optimization while maintaining functional correctness. Professor De Micheli has supervised numerous doctoral students throughout his career at EPFL, mentoring over 40 PhD candidates whose research spans various aspects of electronic design automation, circuit design, and emerging technologies. His students have gone on to make significant contributions in both academia and industry. As Scientific Director of EcoCloud, Professor De Micheli leads research initiatives focused on energy-efficient computing systems and sustainable cloud infrastructure. His laboratory, the Integrated Systems Laboratory, serves as a hub for interdisciplinary research connecting computer science, electrical engineering, and materials science, with particular focus on next-generation computing technologies.

Sujaya Maiyyaمشاهده پروفایل

استادیار

• Distributed Systems
• Database Systems
• Data Privacy
• +۳ مورد دیگر

Sujaya Maiyya is an Assistant Professor at the Cheriton School of Computer Science, University of Waterloo. Prior to this, she completed a postdoc at Cornell University and earned her PhD from the University of California, Santa Barbara. Her research focuses on distributed systems, databases, and privacy/security, particularly in designing secure and efficient data management systems. She leads projects on oblivious databases, trusted execution environments (TEEs), and scalable privacy-preserving systems. Education: PhD in Computer Science, University of California, Santa Barbara (2018) MSc in Computer Science, University of California, Santa Barbara (2017) BE in Information Science, PESIT Bangalore (2014) Research Interests: Distributed systems, database privacy, oblivious datastores, genomics data security, and secure computation using TEEs. Her work emphasizes practical solutions for privacy-preserving storage and query processing, including tunable-privacy mechanisms and fault-tolerant ORAM systems. Awards and Grants: CFI/ORF Infrastructure Grant (2024-2029) NCC Research Awards (2024-2028) NSERC Discovery Grant (2023-2027) MIT EECS Rising Stars (2021) Teaching: Courses include CS348 (Introduction to Databases) and CS848 (Privacy Enhancing Data Systems). She emphasizes foundational concepts and system internals in database design and secure systems. Professional Service: Chair of Ontario Database Day (2024), PC member for SIGMOD, EDBT, VLDB, and ICDE. Frequent reviewer for journals like TKDE and DKE.

• Distributed Computing
• Wireless Networks
• Distributed Systems
• +۴ مورد دیگر

Prof. Roger Wattenhofer is a Full Professor at the Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland, and Deputy head of the Computer Engineering and Networks Lab. He holds a doctorate in Computer Science from ETH Zurich (1998) and has held positions at Brown University and Microsoft Research before returning to ETH. His research focuses on distributed computing, wireless networks, and algorithmic systems design, with contributions to Byzantine agreement protocols, blockchain technologies, and neural network architectures. He teaches courses such as Distributed Systems and Computational Thinking. Education: Ph.D. in Computer Science (ETH Zurich, 1998). Research interests include distributed systems, network algorithms, and the intersection of machine learning with distributed computing. His work spans both theoretical foundations and practical implementations, addressing challenges in fault tolerance, consensus mechanisms, and algorithmic efficiency. Recent publications explore topics like adversarial robustness in voting systems, privacy in reinforcement learning, and generative music models. He actively contributes to open-source frameworks and benchmarks for neural algorithmic reasoning.

Anoosheh Heidarzadehمشاهده پروفایل

استادیار

• Information and coding theory
• Private and secure computing
• Fault-tolerant distributed computing
• +۳ مورد دیگر

Anoosheh Heidarzadeh is an Assistant Professor in the Department of Electrical and Computer Engineering at Santa Clara University's School of Engineering. He holds a Ph.D. in Electrical and Computer Engineering from Carleton University (2012) and previously served as a Visiting Assistant Professor at Texas A&M University (2018-2022) and Associate Research Scientist at the same institution (2015-2017). His postdoctoral research was conducted at the California Institute of Technology (2013-2014). His research focuses on: Information and coding theory : Fundamental limits of data transmission and storage systems Private and secure computing : Protocols for confidential data processing in networked environments Fault-tolerant distributed systems : Resilient computation frameworks for large-scale applications Distributed machine learning : Scalable algorithms for collaborative learning architectures Recent publications (2021-2022) demonstrate strong emphasis on privacy-preserving computation (covering 73% of articles) and distributed coding techniques (67% of articles), with innovations in private information retrieval, matrix operations, and group testing methodologies. Theoretical contributions dominate (87%), while 13% address applied challenges like COVID-19 screening.

Andrew Childsمشاهده پروفایل

استاد

• Quantum Algorithms
• Quantum Information Processing
• Quantum Simulation
• +۲ مورد دیگر

Andrew Childs is a Professor at the University of Maryland, affiliated with the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS). He serves as Director of the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation (RQS) and is a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). His research focuses on quantum algorithms for simulating physical systems, algebraic problems, and quantum walk protocols, with applications in quantum computing and computational complexity. University of Maryland Institute for Advanced Computer Studies (UMIACS) Joint Center for Quantum Information and Computer Science (QuICS) NSF Quantum Leap Challenge Institute for Robust Quantum Simulation Childs' research spans quantum simulation, quantum Fourier transform, phase estimation, and Hamiltonian dynamics. He has developed techniques to reduce quantum computational resources for simulating quantum systems and explored limitations of quantum computers through hidden subgroup problems and non-unitary dynamics. His publications cover diverse areas including quantum walk optimization, Hamiltonian simulation methods, and applications to cryptography and condensed matter physics. Recent works address spatial search algorithms, product formulas for commutators, and quantum routing protocols. As an educator, Childs has taught courses on quantum algorithms and information processing at both the University of Maryland and University of Waterloo, with lecture notes and materials spanning multiple years. Contact: amchilds@umd.edu | Office: ATL 3359 | Affiliated with University of Maryland's quantum research institutes.

Charalampos Papamanthouمشاهده پروفایل

دانشیار

• Computer Security
• Applied Cryptography
• Verifiable Computations
• +۵ مورد دیگر

Charalampos Papamanthou is an Associate Professor of Computer Science at Yale University, where he also serves as Co-director of the Yale Applied Cryptography Laboratory and a member of the Yale Institute for Foundations of Data Science. He holds affiliations with the Yale Center for Algorithms, Data, and Market Design. Additionally, he is Chief Scientist at Lagrange Labs. His research focuses on computer security and applied cryptography, particularly verifiable and privacy-preserving computations, leakage-abuse attacks on searchable encryption, and scalable blockchains/cryptocurrencies. He has advised numerous students and postdocs, and his work is supported by NSF, Protocol Labs, and JP Morgan. Research Interests: His primary areas include cryptographic protocols, privacy-preserving systems, blockchain infrastructure, secure cloud computing, and distributed consensus mechanisms. He has pioneered advancements in zero-knowledge proofs, private information retrieval, and dynamic searchable encryption. Awards: He has received prestigious awards such as the CCS Test-of-Time Award (2022), JP Morgan Faculty Research Award (2022), and NSF CAREER Award (2017). His contributions span over 140 publications in top venues like CRYPTO, CCS, and SODA. Teaching: He has taught advanced courses in cryptography, algorithms, and computer systems security at Yale and previously at the University of Maryland and Brown University. Recently, he chairs Yale’s PhD admissions in Computer Science. Labs & Teams: Leads the Yale Applied Cryptography Lab, focusing on real-world applications of cryptographic research. Collaborates with industry partners like Lagrange Labs to develop privacy-preserving technologies.

Khuzaima Daudjeeمشاهده پروفایل

استاد

• Distributed Systems
• Database Management
• Cloud Computing
• +۳ مورد دیگر

Khuzaima Daudjee is a Professor and David R. Cheriton Faculty Fellow in the Cheriton School of Computer Science at the University of Waterloo. His research focuses on systems-oriented problems at the intersection of systems and data management, particularly building large-scale systems, storage infrastructure in the cloud, and modern hardware applications. He leads projects in distributed database systems, elastic scaling, and resource optimization. His recent work includes Caerus (geo-replicated transactions), Tiresias (predictive storage), and MorphoSys (automatic physical design metamorphosis). Daudjee has chaired major conferences including ICDE 2026 and serves on editorial boards for VLDB, SIGMOD, and IEEE TKDE journals. His awards include ACM Distinguished Scientist and multiple best paper awards. Educational initiatives include developing distributed systems teaching materials and supervising graduate students across database and distributed systems domains. His industry collaborations involve cloud infrastructure optimization and scalable data processing frameworks.

Liang Chengمشاهده پروفایل

استاد

• Cyber-Physical Systems (CPS)
• Internet of Things (IoT)
• AI/ML Applications
• +۷ مورد دیگر

Dr. Liang Cheng is the Department Chair and Professor in the Department of Electrical Engineering and Computer Science at the University of Toledo. He leads a department with ~700 students across CS, CSE, and EE programs. His research focuses on Cyber-Physical Systems (CPS), IoT, AI/ML, and intelligent infrastructure, supported by over $30M in funding from NSF, DOE, DOT, and industry. Notable projects include CPS Breakthrough initiatives and underground sensing systems. He co-edited a multidisciplinary book on Underground Sensing and contributed to smart grid cybersecurity. Dr. Cheng has held leadership roles at Lehigh University, shaping faculty governance and equity policies. His 100+ publications span networking, real-time systems, and sensor networks. He advises on funded projects totaling $30M+ and has pioneered pedagogical approaches in computer science education. Research Interests: Cyber-Physical Systems (CPS): Focuses on autonomous drones, energy systems, and real-time infrastructure Networking: Expertise in TSN, DTN, and wireless protocols Cybersecurity: SCADA systems, PLC attack detection, and blockchain energy modeling Underground Sensing: Geo-sensing via wireless signals and subsurface tomography Grants & Projects: Over 20 sponsored projects including NSF CPS Breakthrough (2018-2023), ABB smart grid projects, and DARPA-funded EDIFY systems. Key contributions include reconfigurable wireless architectures and network calculus tools for real-time systems. Teaching: Courses span senior design, compiler design, parallel computing, and wireless sensor networks. Developed pedagogical patterns for non-CS programming education. Awards: Recognized for leadership in academic governance and interdisciplinary research collaboration.

Raffaello D'Andreaمشاهده پروفایل

استاد

• Robotics
• Control Systems
• Aerospace Engineering
• +۵ مورد دیگر

Prof. Raffaello D'Andrea is a Full Professor at ETH Zürich's Department of Mechanical and Process Engineering, affiliated with the Institute for Dynamic Systems and Control. His research focuses on bridging digital and physical worlds through robotics, control systems, and autonomous systems. He has pioneered work in aerial robotics, swarm systems, tactile sensing, and soft robotics. His philosophy emphasizes solving 'easy' problems with scalable, robust solutions, prioritizing simplicity and replicability. Key research areas include UAV navigation, distributed control, tactile sensor design, and fault-tolerant systems. He has founded multiple organizations and led roles as CTO/CEO, emphasizing cross-disciplinary innovation. His work has commercial applications in logistics, healthcare, and automation, driven by a belief in technology's role in improving human life. Notable projects include the Cubli robotic cube, aerial vehicle swarms, and optical tactile sensors for robotics. His lab emphasizes collaboration and team leadership, aiming to translate theoretical insights into practical, scalable technologies. Scientific awards: None explicitly listed in the provided texts. Advising and grants: No students listed in the provided texts; grants information not detailed. Labs/Teams: Leads research at ETH Zurich's Institute for Dynamic Systems and Control, collaborating with industry and academic partners globally.

Mo Addaمشاهده پروفایل

مدرس ارشد

• Network Security
• Distributed Systems
• Wireless Networks
• +۵ مورد دیگر

Dr. Mo Adda is a Principal Lecturer at the University of Portsmouth's School of Computing, part of the Faculty of Technology. He holds a PhD in Distributed Systems and Parallel Processing from the University of Surrey. His research focuses on network security, distributed systems, wireless networks, and cybercrime prevention. He leads projects in the Centre for Cybercrime and Economic Crime, exploring fault management in networks, blockchain applications, and IoT forensics. With 16 supervised theses, he advises on topics like energy-efficient cloud systems and machine learning for environmental modeling. His work bridges academia and industry, addressing challenges in software-defined networks, traffic control, and secure data sharing in social networks. Education: PhD in Distributed Systems (University of Surrey) Affiliations: Centre of Excellence in Defence, Risk & Resilience; Portsmouth Centre for Advanced Materials and Manufacturing Research Interests Dr. Adda's research spans: Network security and fault detection mechanisms Blockchain applications in IoT and forensics Energy-efficient cloud data center optimization Machine learning for climate modeling Self-organizing network protocols Grants & Collaborations His projects include collaborations with industry partners on secure data leakage detection in cloud systems and resilient wireless protocols for harsh environments. He has pioneered fault classification systems using clustering algorithms and fuzzy logic. Labs & Teams He contributes to the Centre for Cybercrime and Economic Crime, focusing on digital forensics and network intrusion analysis. His team develops frameworks for privacy management in social networks and proactive routing in software-defined networks.

Daniel Abadiمشاهده پروفایل

استاد

• Database System Architecture
• Distributed Database Systems
• Scalable Transaction Processing
• +۳ مورد دیگر

Daniel Abadi is the Darnell-Kanal Professor of Computer Science at the University of Maryland, College Park, with an appointment in the University of Maryland Institute for Advanced Computer Studies. He leads the Data Systems Lab at Maryland (DSLAM) and has made significant contributions to database system architecture and implementation, particularly in scalable and distributed systems. Prof. Abadi's research focuses on database system architecture, especially at the intersection with scalable and distributed systems. He is best-known for the development of the storage and query execution engines of the C-Store (column-oriented database) prototype, which was commercialized by Vertica and eventually acquired by Hewlett-Packard, and for his HadoopDB research on fault tolerant scalable analytical database systems which was commercialized by Hadapt and acquired by Teradata. His current work includes deterministic distributed systems like Calvin and SLOG, which provide strictly serializable, low-latency, geographically replicated database transactions. Analysis of his recent publications reveals a strong focus on modern database challenges including transaction processing, distributed systems architecture, data mesh concepts, schema evolution, and IoT data management. His work consistently addresses the tension between consistency, availability, and performance in distributed database systems, with recent emphasis on moving beyond traditional two-phase commit protocols and exploring novel approaches to data architecture like data mesh. ACM Fellow Sloan Research Fellowship Churchill Scholarship NSF CAREER Award VLDB Best Paper Award Two VLDB Test of Time Awards (for C-Store and HadoopDB) 2008 SIGMOD Jim Gray Doctoral Dissertation Award 2013-2014 Yale Provost's Teaching Prize 2013 VLDB Early Career Researcher Award PhD dissertation advisor for Alexander Thomson and Jose Falerio, whose dissertations won SIGMOD Jim Gray Doctoral Dissertation Awards in 2015 and 2020 respectively Prof. Abadi has advised multiple PhD students, including Alexander Thomson and Jose Falerio, both of whom received the prestigious SIGMOD Jim Gray Doctoral Dissertation Award. His research has been supported by numerous grants including NSF funding for projects like SLOG. He maintains an active presence in the database community through his widely-read blog DBMS Musings and through service on program committees for major conferences including SIGMOD, VLDB, and CIDR. He leads the DSLAM research group at the University of Maryland, which focuses on cutting-edge database system research with strong industry connections and practical impact.

George Danezisمشاهده پروفایل

استاد

• Systems Security
• Privacy
• Anonymous Communications
• +۸ مورد دیگر

George Danezis is a Professor of Security and Privacy Engineering at University College London (UCL), affiliated with the Information Security Group. He is also a faculty fellow at the Turing Institute and has held part-time roles since 2018 to focus on commercialization. His research spans systems security, privacy, anonymous communications, and blockchain technologies. Danezis co-founded Chainspace (acquired by Facebook in 2019) and Mysten Labs, where he serves as Chief Scientist. He holds a PhD from the University of Cambridge (2004) and has held positions at Microsoft Research, K.U.Leuven, and the University of Cambridge. Education: PhD (Computer Laboratory, University of Cambridge, 2004), B.A. (Hons) in Computer Science (Queens' College, Cambridge, 2000). Research interests include blockchain consensus, decentralized systems, privacy-preserving technologies, and machine learning applications in security. He has advised numerous doctoral students and led projects funded by EU Horizon 2020, EPSRC, and industry partnerships. His work emphasizes practical solutions for privacy, such as Loopix (anonymity system), Narwhal/Tusk (blockchain consensus), and Coconut (privacy credentials). Danezis has received awards for best papers (PET 2002/2018), is a Fellow of the British Computing Society, and advises organizations like Privacy International and DeepMind. Publications focus on blockchain, anonymity, and privacy, with over 100 peer-reviewed papers. Grants include leadership in projects like DECODE (EU), PANORAMIX, and Glass Houses. Teaching includes courses on computer security and privacy technologies at UCL.

Mohsen Ghafouriمشاهده پروفایل

دانشیار

• Smart Grid Security
• Cyber-Physical Systems Security
• Wide Area Monitoring Systems (WAMS)
• +۵ مورد دیگر

Mohsen Ghafouri is an Associate Professor at the Concordia Institute for Information Systems Engineering (Concordia University). His research focuses on cybersecurity, smart grids, and cyber-physical systems with emphasis on securing energy infrastructure against cyber-attacks. Key areas include detection and mitigation of false data injection attacks, grid resilience against load-altering threats, and secure transactive energy markets. Research interests include wide-area monitoring systems (WAMS), microgrid control, and integration of renewable energy sources. He has developed frameworks for real-time anomaly detection in power systems, blockchain-based security solutions, and machine learning approaches for cyber threat identification. His work addresses vulnerabilities in smart grid components like IEC 61850 substations and EV ecosystems. Recent publications (2024-2025) highlight advancements in securing FACTS controllers, EV charging systems, and distributed energy resources. He has proposed novel mitigation strategies using reinforcement learning, graph neural networks, and federated learning. No scientific awards or grant details are provided in the source text. No advising relationships or lab affiliations are explicitly stated.

Jungsang Kimمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Information Science
• Trapped Ion Quantum Systems
• +۵ مورد دیگر

Jungsang Kim is the Schiciano Family Distinguished Professor of Electrical and Computer Engineering and Professor of Physics at Duke University. He serves as Associate Director of the Duke Quantum Center and leads the Multifunctional Integrated Systems Technology group. Quantum Computing with Trapped Ions Quantum Information Science Photonic Device Development Quantum Communication Networks His research focuses on scalable quantum information processors using trapped atomic ions and advanced photonic technologies. Key innovations include microfabricated ion traps, optical MEMS, and cryogenic systems for quantum integration. Recent publications highlight trapped ion quantum simulation, high-fidelity gate design, and photonic error mitigation. His group develops practical quantum hardware and co-founded IonQ, the first publicly traded pure-play quantum computing company. Fellow, American Physics Society (2021) Stansell Family Distinguished Research Award (2016) Fellow, National Academy of Inventors Fellow, Optica (formerly OSA) Kim's work bridges quantum physics and engineering, with over 80 patents and leadership in Duke's quantum computing initiatives. He recently stepped down as IonQ's CTO while maintaining active research and strategic roles at Duke.