جستجوی استاد راهنمای دانشگاهی

Shweta Shindeمشاهده پروفایل

استادیار

• Trusted Computing
• System Security
• Hardware Security
• +۴ مورد دیگر

Shweta Shinde is an Assistant Professor in the Department of Computer Science at ETH Zurich where she leads the Secure & Trustworthy Systems (SECTRS) research group. She is also a member of the Institute of Information Security and the ZISC Center at ETH Zurich. Her work bridges theoretical foundations with practical implementations in hardware and system security. Dr. Shinde's research focuses on the intersection of trusted computing, system security, and program analysis. Her group investigates both foundational aspects of security to protect phones, servers, and accelerators, as well as practical aspects of realizing these solutions through large-scale system building. Her work spans hardware security primitives, trusted execution environments, confidential computing, and secure system design across multiple platforms including mobile devices, cloud infrastructure, and blockchain systems. Her publication record demonstrates significant impact in the field, with numerous papers in top security venues including IEEE S&P, USENIX Security, CCS, and NDSS. Her research has uncovered critical vulnerabilities in major hardware security technologies like Intel SGX and AMD SEV-SNP while also proposing novel frameworks for building more secure systems. The work spans multiple domains including hardware security, cloud security, mobile security, and blockchain security, with a consistent thread of identifying and addressing fundamental security challenges in trusted computing. Among her notable achievements are multiple best paper awards including at SysTEX 2025 and nominations at DATE 2025, a Distinguished Paper Award at IEEE S&P 2024, and recognition as a Most Innovative Research Pwnie Award Nominee in 2024. Her work on WeSee received particular attention for breaking AMD SEV-SNP through novel interrupt-based attacks. Dr. Shinde actively mentors PhD students including Mark Kuhne, Supraja Sridhara, Mélisande Zonta-Roudes, Benedict Schlüter, Andrin Bertschi, and others. She teaches courses on Systems Security, Information Security Lab, Seminar on Systems Security, and Current Topics in Information Security at ETH Zurich. Her service to the community includes extensive program committee work for major security conferences including Oakland (S&P), NDSS, USENIX Security, and CCS, where she has served as track co-chair and program co-chair for several workshops.

Benjamin Carrison-Schaferمشاهده پروفایل

دانشیار

• Reconfigurable Computing
• FPGAs
• Electronic Design Automation
• +۷ مورد دیگر

Benjamin Carrison-Schafer is an Associate Professor and Assistant Dean for Graduate Student Success at the Department of Electrical and Computer Engineering, Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. He leads the Design Automation and Reconfigurable Computing Laboratory (DARClab), focusing on systems, high-level design, and programming methodologies for VLSI computing systems and FPGAs. Education: MBA from McGill University, Canada (2012) PhD in Electrical and Electronic Engineering from University of Birmingham, UK (2003) Research Interests: His work spans modeling, analysis, synthesis, optimization, and implementation of VLSI systems. Current projects include: Approximate Computing, High-Level Synthesis Design Space Exploration, Hardware Security, Behavioral MPSoC Optimization, and Automatic Fault-Tolerant System Generation. His research blends theory and practice, using analytical and experimental techniques to solve real-world problems. Publication Trends: Recent publications demonstrate strong focus on hardware security, FPGA optimization, and automated design methodologies. Key themes include High-Level Synthesis innovations, hardware acceleration techniques, and cross-disciplinary applications of reconfigurable computing. His work frequently addresses challenges in hardware trustworthiness, energy efficiency, and design automation scalability. Professional Activities: Associate Editor: IEEE Transactions on Sustainable Computing (2022-present) Conference Chair: ICCD 2024, DCAS 2024 Program Committee: ASP-DAC, DATE, FCCM, GLSVLSI Advising & Labs: Supervises multiple PhD and Master's students at DARClab. Current research includes domain-specific architecture design, hardware security, sustainable computing, and ML for VLSI design. The lab collaborates with industry partners like Renesas Electronics and develops commercial tools through spin-off company highX Technologies.

Arkaprava Basuمشاهده پروفایل

دانشیار

• Computer Architecture
• Graphics Processing Units (GPUs)
• Memory Management
• +۳ مورد دیگر

Dr. Arkaprava Basu is an Associate Professor at the Indian Institute of Science (IISc), Bangalore. He received the ACM India Early Career Researcher (ECR) Award 2024 for his innovative contributions to efficient memory management in GPUs and CPUs through cross-stack software-hardware research. Affiliation: Indian Institute of Science (2018–present) Prior Roles: Full-time Research Staff at AMD Research (Austin, USA, 2014–2018) Education: PhD in Computer Science from University of Wisconsin-Madison (2013) His research focuses on optimizing AI hardware systems by integrating compiler, runtime, and OS design with hardware architecture. Collaborations include long-term consultancy with tech giants, emphasizing practical implementations of his theoretical work. Recognitions: ACM India ECR Award (2024) for "creative and impactful contributions toward efficient memory management for GPUs and CPUs"

Nate Fosterمشاهده پروفایل

استاد

• Programming Languages
• Networking
• Databases
• +۵ مورد دیگر

Nate Foster is a Professor of Computer Science at Cornell University and currently serves as the Associate Dean for Research in the Ann S. Bowers College of Computing and Information Science. He is also a Visiting Researcher at Jane Street and served as a Visiting Professor at École Polytechnique Fédérale de Lausanne during the 2023-24 academic year. His research uses ideas from programming languages to solve problems in networking, databases, and security. BA in Computer Science, Williams College (2001) MPhil in History and Philosophy of Science, University of Cambridge (2008, all work completed in 2003) PhD in Computer and Information Science, University of Pennsylvania (2009) Foster's research focuses on developing languages and tools that make it easy for programmers to build secure and reliable systems. His current work centers on the design and implementation of languages and tools for programmable networks, particularly using the P4 language. His past work includes bidirectional languages (also known as 'lenses'), database query languages, data provenance, type systems, mechanized proof, and formal semantics. His research group at Cornell has made significant contributions to network verification, software-defined networking, and formal foundations for programmable data planes. Analysis of Foster's recent publications reveals a strong focus on network verification and programming language foundations for networking. His work consistently applies formal methods to practical networking problems, with a particular emphasis on the NetKAT and P4 languages. Over the past five years, his research has evolved toward more complex network verification techniques, including infinite state verification, active learning of network models, and dependently-typed approaches to network programming. His work bridges theoretical computer science with practical networking systems, making formal methods accessible to network engineers. ACM Fellow (2025) ACM SIGPLAN Robin Milner Award (2023) ACM SIGCOMM Rising Star Award (2018) NSF CAREER Award (2013) Alfred P. Sloan Fellowship (2012) Multiple distinguished paper awards across top conferences including POPL, PLDI, and SIGCOMM Foster has advised numerous PhD and Master's students who have gone on to prominent positions in both industry and academia, with many continuing work in programming languages and networking. He has led multiple significant research grants including an NSF CAREER Award and has been involved in the P4 Language Consortium, serving as Chair of the P4 Language Governing Board. His work has been supported by various organizations including NSF, DARPA, and industry partners like Intel and Jane Street. Foster is also active in the programming languages research community, serving on numerous program committees and as Vice Chair of DARPA's Information Science and Technology (ISAT) study group. Foster leads a vibrant research group at Cornell focused on programming languages for networks, with collaborators from academia and industry. His group has developed several influential tools and frameworks including NetKAT, Petr4, and KATch. They maintain strong connections with the P4 community and work closely with industry partners to ensure their research has practical impact on real-world networking systems.

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.

• Database Management Systems
• Self-Driving Database Architectures
• Transaction Processing Systems
• +۴ مورد دیگر

Andy Pavlo is an Associate Professor with Indefinite Tenure in the Computer Science Department at Carnegie Mellon University's School of Computer Science. He is an active member of the CMU Database Group and the Parallel Data Laboratory, where he leads research in database management systems with a focus on self-driving architectures, transaction processing, and large-scale analytics. His work bridges academic research and industry applications through projects like NoisePage, OtterTune (which he co-founded and served as CEO before it ceased operations), and Peloton. Dr. Pavlo's research interests span database management systems with particular emphasis on autonomous database architectures that can self-tune and optimize without human intervention. His work explores transaction processing systems that can handle high-throughput workloads while maintaining consistency, and large-scale data analytics techniques that efficiently process massive datasets. He has made significant contributions to query optimization, database extensibility, and automatic database tuning using machine learning techniques. His recent work on database extensibility revealed critical issues in PostgreSQL's extension ecosystem, showing that approximately 16% of extensions are incompatible with at least one other extension due to API violations and memory errors. His research output demonstrates a consistent focus on practical database systems challenges, with recent publications examining database extensibility, user-defined function optimization, and the cyclical nature of database research. The articles show a strong trend toward making database systems more autonomous, with increasing integration of machine learning techniques for automatic tuning and optimization. His work often combines deep theoretical analysis with practical implementation in open-source systems. Dijkstra Award 2024 for contributions to database systems research Dr. Pavlo actively mentors graduate students, with current advisees including Wan Shen Lim, William Zhang, and Sam Arch (co-advised with Todd Mowry). His former students have gone on to successful careers in both industry and academia. He has secured significant research funding through CMU's affiliate program with major database companies including ClickHouse, DataStax, dbt, Firebolt, MotherDuck, RelationalAI, SingleStore, Spiral, PingCAP/TiDB, Yellowbrick, and Yugabyte. His research is supported by these industry partnerships and likely includes NSF funding given his active participation in the database research community. At CMU, Dr. Pavlo leads the Database Group and organizes several seminar series including "SQL or Death," "Database Building Blocks," and "ML⇄DB Technical Talks." These seminars bring together researchers and practitioners to discuss cutting-edge developments in database systems. He also runs a summer research internship program that has attracted students for multiple consecutive years, indicating a strong research group with ongoing projects and funding.

Michael Baldeaمشاهده پروفایل

دانشیار

• Process Systems Engineering
• Energy Systems
• Nonlinear Optimization
• +۳ مورد دیگر

Michael Baldea is an Associate Professor in the Department of Chemical Engineering at the University of Texas at Austin . He holds a Ph.D. in Chemical Engineering from the University of Minnesota (2006), with prior degrees from 'Babeş-Bolyai' University in Romania (M.Sc. 2001, Diploma 2000). His research group develops theoretical and computational methods for Process and Energy Systems Engineering , focusing on integrated decision-making, performance optimization, and process intensification with industrial validation. Education: Ph.D., Chemical Engineering, University of Minnesota (2006) M.Sc., Interface Process Engineering, 'Babeş-Bolyai' University (2001) Diploma, Chemical Engineering, 'Babeş-Bolyai' University (2000) Research Thrusts: Integrated decision-making in chemical/energy supply chains Process performance monitoring and optimization Process integration and intensification Key applications include grid-responsive chemical plants, intensified distillation/column designs, and renewable energy integration for building systems. Scientific Awards: Frank A. Liddell, Jr. Fellowship NSF CAREER Award (2015-2020) Moncrief Grand Challenges Faculty Award (2014) AIChE Outstanding Young Researcher Award (2017) Implementation : His group has translated research into commercial tools through partnerships with industrial test beds and is working to integrate methods into commercial simulators. They explore predictive approaches for building energy management and strategic capital investment analysis in next-generation energy systems.

Bernhard J. Bergerمشاهده پروفایل

مدرس

• Software Security
• Static Code Analysis
• Machine Learning
• +۴ مورد دیگر

Bernhard J. Berger is a Lecturer in the Department of Computer Engineering at the Institute of Embedded Systems, Hamburg University of Technology (TUHH). His research focuses on software security, static code analysis, machine learning, optimization, and research data management. He has held significant roles such as Program Committee member for ICPC 2025 and MSR 2025, and has received awards including the Best Reviewer Award (ICPC 2023) and Best Engineering Paper Award (SCAM 2019). His work spans interdisciplinary applications including maritime systems security, GPU-accelerated AI, and evolutionary algorithms. Recent studies emphasize AI-driven security tools (e.g., ML-SAST) and domain-specific language approaches to optimization (EvoAl). He has contributed to over 30 peer-reviewed publications, with notable work in IEEE Transactions on Software Engineering and Science of Computer Programming. Berger collaborates closely with industry through DAAD review committees and serves on artifact evaluation boards for ISSTA and ARES conferences. Education: Doctoral Thesis (2022), Diploma in Computer Science (2007) Key Projects: ArchSec tool suite, Threat Modeling Frameworks, Bauhaus static analysis methodology Lab Affiliation: Embedded Systems Design Group His advisory roles include Deputy of TUHH's Election Verification Committee and Session Chair at IEEE Congress on Evolutionary Computation 2023. Current research trends integrate machine learning with static analysis for automated vulnerability detection, while also exploring explainable AI techniques for neural network optimization.

• Reconfigurable Computing
• FPGA Architectures
• Computer Security
• +۶ مورد دیگر

André DeHon is the Oliver C. Boileau Jr. and Nan Eleze Boileau Professor of Electrical Engineering at the University of Pennsylvania, affiliated with Electrical and Systems Engineering (ESE) and Computer and Information Science (CIS). He chairs the Computer Engineering (CMPE) program and directs the CyberSavvy Security Center. His research focuses on reconfigurable computing, FPGA architectures, computer security, and energy-efficient hardware design. He holds a Ph.D. and M.S. from MIT and a B.S. from MIT's Lincoln School. Research interests include reconfigurable computing, FPGA interconnect, hardware security, and fault-tolerant systems. Notable achievements include the SEVER & PROTECT DARPA award and IEEE/ACM Fellowships. Recent work addresses fast FPGA compilation (HiPR, PLD), security through compartmentalization (μSCOPE, SCALPEL), and partial reconfiguration techniques. Teaching includes courses on hardware security, system-on-chip architecture, and digital audio basics. Over 200 publications span FPGA design, network-on-chip optimization, and molecular-scale computing. His labs (Implementation of Computation Group) explore physical implementation of computations through hardware-software co-design.

Deian Stefanمشاهده پروفایل

دانشیار

• security
• programming languages
• systems
• +۷ مورد دیگر

Deian Stefan is an Associate Professor at the University of California San Diego (UCSD) in the Department of Computer Science and Engineering . His research spans security , programming languages , and systems , with a focus on building principled and practical secure systems. He has served as a co-founder and Chief Scientist at Intrinsic (acquired by VMWare) and contributed to standards bodies like the W3C WebAppSec and Node.js Security Working Groups . His research interests include: Secure Systems : Web frameworks, browser designs, sandboxing, runtime systems Language-Based Security : Constant-time programming, memory safety, information flow control Verification : Security verification, static/symbolic analysis tools WebAssembly and JavaScript JITs security Deian Stefan has received multiple scientific awards , including several Distinguished Paper Awards at venues like POPL, ICFP, and USENIX Security, as well as the IEEE Cybersecurity Award for Practice (2022) and CSAW 2020 First Place for Applied Research. He has taught courses on Computer Security (CSE 127, CSE 227) and advanced topics in Building Secure Systems (CSE 291) using Rust, WebAssembly, and blockchain security. His work has been supported by collaborations with industry and academia, including projects like RLBox and COWL .

Ben Fischمشاهده پروفایل

استادیار

• Cryptography
• Distributed Systems
• Blockchain Technology
• +۵ مورد دیگر

Ben Fisch is an Assistant Professor of Computer Science at Yale University's School of Engineering & Applied Science. He is also the co-founder of Espresso Systems, a company focused on blockchain infrastructure. His research focuses on privacy and verifiability in decentralized systems like Bitcoin and Ethereum, with applications in digital finance and healthcare. Dr. Fisch received his B.A. from the University of Pennsylvania and completed his Ph.D. at Stanford University, where he worked with Dan Boneh in the applied cryptography research group. His educational background provided the foundation for his work at the intersection of cryptography, distributed systems, and economics. His research centers on leveraging cryptographic tools such as succinct non-interactive zero-knowledge proofs (zk-SNARKs), private information retrieval, and homomorphic encryption to address challenges in verifiable computation, verifiable storage, and verifiable fairness. He has made significant contributions to verifiable delay functions (VDFs) and proofs of replication, which have been adopted by major blockchain projects including Ethereum 2.0, Chia, and Filecoin. His work on Filecoin's Proofs of Replication has helped the network reach over 1.5 exabytes of storage capacity. His publication record shows a clear trend toward increasingly sophisticated cryptographic protocols for blockchain applications, with recent work focusing on data availability for Bitcoin rollups, efficient folding schemes for pairing-based arguments, and privacy pools with proof-carrying disclosures. His research bridges theoretical cryptography with practical implementations that have real-world impact in decentralized systems. His notable recognition includes: Best Paper Finalist at ACM CCS 2017 for 'Iron: Functional Encryption using Intel SGX' Dr. Fisch's research has led to significant technology transfer, most notably with his work on Verifiable Delay Functions (VDFs) sparking a multimillion dollar industry initiative through the VDF Alliance. His research on Proofs of Replication forms the basis of Filecoin's incentive layer and consensus protocol. His newer SNARK system Basefold is being used by several commercial products. He maintains active collaborations across academia and industry, with publications spanning top conferences in cryptography and security. As co-founder of Espresso Systems, Dr. Fisch leads a team developing next-generation blockchain infrastructure, particularly focusing on sequencing layers for rollups. His work bridges academic research with practical implementation, ensuring that theoretical advances in cryptography find real-world applications in decentralized systems.

Benedikt Bünzمشاهده پروفایل

استادیار

• Applied Cryptography
• Blockchain Technology
• Consensus Algorithms
• +۴ مورد دیگر

Benedikt Bünz is an Assistant Professor of Computer Science at New York University's Courant Institute of Mathematical Sciences. He is also a co-founder and chief scientist of Espresso Systems, where he applies his research expertise to real-world blockchain solutions. His academic work bridges theoretical cryptography with practical blockchain implementations, focusing on enhancing privacy, security, and usability of decentralized systems. Dr. Bünz's research centers around applied cryptography, consensus mechanisms, and game theory as they relate to cryptocurrencies. His work spans zero-knowledge proofs, verifiable delay functions, secure multi-party computation, and privacy-preserving protocols. He has made significant contributions to Bulletproofs, a zero-knowledge proof system deployed on blockchains like Monero, and pioneered research in verifiable delay functions which are now part of Ethereum 2.0's design. His recent work focuses on recursive proof systems, accumulation schemes, and efficient verification techniques for blockchain scalability. His publication record shows a consistent progression from foundational cryptographic primitives to practical blockchain implementations. Recent work demonstrates increasing sophistication in recursive proof systems (ProtoStar, HyperPlonk), novel accumulation techniques (ARC, DewTwo), and foundational work on randomness generation (VDFs). His research consistently bridges theoretical cryptography with real-world blockchain applications, resulting in protocols that are both theoretically sound and practically implementable across multiple blockchain platforms. Dr. Bünz actively contributes to the academic community through teaching and mentorship. He teaches courses on cryptography of blockchains and computer security at NYU, providing students with hands-on experience in blockchain security and cryptographic protocols. His industry engagement through Espresso Systems demonstrates his commitment to translating academic research into practical solutions for the blockchain ecosystem.

• Reconfigurable Computing
• Field-Programmable Gate Arrays (FPGA)
• High-Level Synthesis
• +۳ مورد دیگر

Paolo Ienne is a Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL), where he leads the Processor Architecture Laboratory (LAP) within the School of Computer and Communication Sciences. His research focuses on advancing reconfigurable computing systems through innovative FPGA architectures and high-level synthesis methodologies. His primary research domains include reconfigurable computing, FPGA architecture design, dynamically scheduled dataflow circuits, and hardware acceleration techniques. Recent work emphasizes memory system optimization for FPGAs, formal verification of circuit transformations, and rapid C-to-hardware compilation flows. He has pioneered approaches for handling thousands of outstanding memory misses in FPGA accelerators and developed novel techniques for switch-block exploration without explicit pattern enumeration. Analysis of his 2023-2025 publications reveals a strong trend toward practical FPGA deployment challenges, with increasing focus on HBM integration, virtual memory systems for PCIe-attached devices, and formally verified circuit transformations. His work consistently targets real-world bottlenecks in high-level synthesis toolchains while maintaining theoretical rigor in dataflow architecture design. Professor Ienne's laboratory receives support from the Swiss National Science Foundation and industry partners including Huawei, enabling cutting-edge research in FPGA-based acceleration. His collaborative network spans major semiconductor companies and academic institutions worldwide, with frequent co-authorship on conference proceedings and journal publications in IEEE and ACM venues.

Daniel Gottesmanمشاهده پروفایل

استاد

• Quantum Computing
• Algorithms and Theory
• Quantum Error Correction
• +۳ مورد دیگر

Daniel Gottesman is the Brin Family Endowed Professor in Theoretical Computer Science at the University of Maryland, affiliated with the Department of Computer Science, Institute for Advanced Computer Studies (UMIACS), and the Joint Center for Quantum Information and Computer Science (QuICS). He holds a Ph.D. in Physics from Caltech (1997) and has held positions at institutions like the Perimeter Institute and Quantum Benchmark. His research focuses on quantum computing, quantum error correction, and fault-tolerant systems, with contributions to stabilizer codes and quantum teleportation-based gates. Education: Bachelor's in Physics, Harvard University (1992) Ph.D. in Physics, California Institute of Technology (1997) Research Interests: Quantum error correction and fault-tolerant architectures Quantum cryptography and secure communication protocols Quantum complexity theory and algorithm design Applications of stabilizer codes and topological quantum computing Scientific Awards: Fellow of the American Physical Society CIFAR Senior Fellow in Quantum Information Science Three U.S. Patents (e.g., quantum key distribution systems) Advising & Grants: Supervised over 30 students/postdocs and served on numerous thesis committees. Active in securing funding for quantum research through endowed professorships and industry partnerships (e.g., Quantum Benchmark). Labs/Teams: Member of QuICS and UMIACS, collaborating on quantum hardware-software integration and error correction challenges.

• Secure Decentralized Systems
• Blockchain Technology
• Systems Security
• +۳ مورد دیگر

Prof. Bryan Ford leads the Decentralized/Distributed Systems (DEDIS) lab at EPFL. He focuses on secure decentralized systems, including blockchain technology, privacy, and systems security. He earned his Ph.D. from MIT and held faculty positions at Yale University and EPFL. His work spans distributed consensus protocols, peer-to-peer networking, and privacy-preserving systems. Key projects include QuePaxa (timeout-free consensus), UIA (global connectivity for mobile devices), and MedCo (secure healthcare data sharing). He advises numerous PhD students and contributes to open-source projects like Bitcoin collective signing and privacy networks like Riffle. Education: Ph.D., MIT; Postdoctoral work at Yale Research interests include blockchain scalability, consensus algorithms, and cryptographic privacy. His lab develops systems like TRIP for coercion-resistant voting and F3B to mitigate blockchain front-running. His work on NAT traversal and peer-to-peer protocols (e.g., STUN/ICE) remains foundational in network architecture. He emphasizes practical, auditable security solutions such as CertiKOS and atomic cross-chain transactions (Atom). Notable contributions: CoSi (collective signing), OmniLedger (sharded blockchain), and privacy-preserving protocols like PURBs (Protected Unsealable Recursive Boxes). His lab collaborates with Swiss Post to audit e-voting systems and designs democratic cryptocurrencies like PoPCoin.