جست‌وجوی استاد و پژوهشگر

Jia Zhangمشاهده پروفایل

استاد

• Machine Learning
• Natural Language Processing
• Information Retrieval
• +۱۰ مورد دیگر

Dr. Jia Zhang is the Inaugural Robert H. Dedman Jr. Endowed Department Chair and Professor of Computer Science at Southern Methodist University (SMU Lyle School of Engineering). She holds the Cruse C. and Marjorie F. Calahan Centennial Chair in Engineering and has a courtesy appointment in the Department of Operations Research and Engineering Management. Her research focuses on applying machine learning, natural language processing, and information retrieval to data science infrastructure, particularly scientific workflows, provenance mining, software discovery, knowledge graphs, cloud computing, immune AI, and applications in earth science and healthcare. Education: Ph.D. in Computer Science, University of Illinois at Chicago M.S. in Computer Science, Nanjing University B.S. in Computer Science, Nanjing University Dr. Zhang's work emphasizes data science infrastructure and machine learning for scientific workflows and knowledge graphs. Her recent publications highlight deep learning , graph neural networks , and optimization algorithms in cloud computing, cybersecurity, and environmental applications. Key trends include spatiotemporal modeling , hybrid neural architectures , and AI-driven service ecosystems . Scientific Awards: Best Paper Awards IEEE SCC (2011, 2017) Best Student Paper Awards IEEE ICWS (2014, 2018), IEEE ICCC (2018) Distinguished Paper Award ICSOC (2023) First Outstanding Service Award IEEE Technical Committee on Services Computing (2016) She has secured over $5 million in federal grants (as PI) and $11 million as PI/Co-PI from NSF, NASA, NIH, UTSW, Ericsson, SAP, and Google. Her lab (Caruth Hall 308) actively recruits research assistants. She previously served as a faculty member at Carnegie Mellon University, Northern Illinois University, and Nanjing University, and worked in industry as a software architect.

Vishal Sharmaمشاهده پروفایل

مدرس ارشد

• Cyber-Physical Systems (CPS)
• 5G and Beyond Security
• Internet of Things (IoT)
• +۴ مورد دیگر

Dr. Vishal Sharma is a Senior Lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. His research focuses on Cyber-Physical Systems (CPS), 5G/6G Security, Unmanned Aerial Vehicles (UAVs), Blockchain, and Digital Twins. He has held roles at institutions like Singapore University of Technology and Design (SUTD) and Soonchunhyang University, South Korea. Notable achievements include Best Paper Awards at ICCMIT 2017, IEEE SITE 2024, and HUCAPP/VISIGRAPP 2025. He leads the Innovation-by-Design Lab and is a Fellow of the Higher Education Academy (FHEA). Research Interests: Cyber Defence, UAV Security, Secure Computing, Network Security, and Sustainable Edge Computing. He has collaborated on projects like RapidRANDefender (QRICSec) and Traceable Procurement for Net-Zero Processes. Awards include the Royal Society International Exchanges Committee appointment (2025) and QUB's Individual Performance Award (2024). Grants and Projects: Principal Investigator for projects such as Exploring Operational Capabilities of Arm Morello for UAV Security (2023) and TUDOR: Ubiquitous 3D Open Resilient Network (2023). Active in editorial roles for IEEE Communications Magazine and IET Networks. His work aligns with UN Sustainable Development Goals (SDGs) related to climate action and innovation. Publications span 150+ articles in top journals/conferences, with a focus on secure communication, edge computing, and UAV networks. Supervises PhD students in cyber defence, AI security, and distributed ledger technologies.

Gerald Reinerمشاهده پروفایل

استاد

• Circular Supply Chains
• Operations Management for Base of the Pyramid
• Humanitarian Logistics Operations
• +۷ مورد دیگر

Gerald Reiner serves as Head of the Institute for Production Management at the Vienna University of Economics and Business (WU), within the Department of Information Systems and Operations Management. He holds a Magister Degree, doctorate, and Habilitation in Business Administration from WU. His academic career includes positions as full professor in Production Management and Logistics at the University of Neuchatel (Switzerland, 2007-2014) and Universitaet Klagenfurt (Austria, 2014-2018), where he also served as head of the department of Operations, Energy, and Environmental Management. Dr. Reiner has held visiting professorships at Aston Business School (UK), HEC Lausanne (Switzerland), University of Bergamo, and Università Cattolica del Sacro Cuore in Milan (Italy). His research spans several critical areas including Industry 4.0 implementation, integrated capacity and inventory management, humanitarian logistics operations, circular supply chains, and operations management for base of the pyramid contexts. His work particularly focuses on practical applications addressing food waste reduction, sustainable manufacturing, and blockchain technology in supply chains. His publication portfolio demonstrates a clear evolution toward digital transformation in operations, with recent focus on hydrogen production systems, AI integration in manufacturing, and blockchain applications for food supply chain transparency. The research shows increasing emphasis on sustainability integration within traditional operations management frameworks, particularly addressing European manufacturing challenges and food system inefficiencies. Publication Excellence Award 2021 (2023) Researcher of the month (January 2023) Highly Commended paper in the 2017 Emerald Literati Network Awards for Excellence ISIR Service Award (2014) Emerald Outstanding Paper Award (2013) Dr. Reiner coordinates multiple significant international research projects including EU-project 'Keeping Jobs in EU', EU/Ecsel-project 'Power Semiconductor and Electronics Manufacturing 4.0', 'Integrated Development 4.0', and 'Artificial Intelligence in Manufacturing leading to Sustainability and Industry 5.0'. His current projects focus on FOODIS (cross-border ecosystem for innovation in food supply chains), Circular Design implementation, and blockchain applications for banana supply chains. He actively supervises research teams working on food waste reduction, sustainable packaging systems, and AI applications in operations management.

• Conceptual Modeling
• Business Process Management
• Digital Transformation
• +۵ مورد دیگر

Yves Wautelet serves as an Associate Professor at the Faculty of Economics and Business at KU Leuven, where he conducts research in conceptual modeling, business process management, and digital transformation. His work addresses critical challenges at the intersection of information systems engineering and business strategy, with particular focus on sustainability-driven modeling approaches and IT governance frameworks. His primary research interests include: Conceptual modeling methodologies and frameworks Business process management and information systems design Digital transformation strategies and implementation IT governance and business-IT alignment Sustainability-driven modeling for circular economy Agile software development practices and methods Requirements engineering with user stories Wautelet's recent publication record demonstrates significant scholarly productivity with numerous 2024-2025 publications spanning conceptual modeling frameworks for sustainability (Circulise), tools for identifying ambiguity in user stories (AmbiTRUS), and approaches to align strategic and operational agility. His work bridges theoretical foundations with practical applications across diverse domains including healthcare, circular economy, software development, and organizational transformation. His research consistently applies model-driven approaches to solve complex real-world problems, often integrating sustainability considerations into information systems engineering. As a promotor and co-promotor, Wautelet currently supervises multiple doctoral research projects including: Automatic generation of conceptual models from textual descriptions (2024-2028) Sustainability-Driven Modeling Assistant for Twin Transition in Vietnam (2024-2028) Home Care Business Process Management using Distributed Ledger Technologies (2024-2028) Teaching Modeling Skills in BPMN formalism (2021-2025) His research is conducted through the Information Systems Engineering Research Group (LIRIS) at KU Leuven's Brussels campus, where he contributes to advancing model-driven approaches for addressing contemporary business and technological challenges.

• Network Security
• Privacy-Preserving Technologies
• Machine Learning for Networking
• +۵ مورد دیگر

Ke Xu is a Professor in the Department of Computer Science at Tsinghua University's School of Information Science and Technology. With extensive research contributions in network security, privacy-preserving technologies, and machine learning applications for networking, Professor Xu has established himself as a leading researcher in computer science. Professor Xu's research interests span network security, privacy-preserving technologies, machine learning for networking, federated learning, internet protocols, encrypted traffic analysis, blockchain applications, and AI in networking. His work bridges theoretical foundations with practical implementations, focusing on real-world security challenges and network optimization problems. He has developed novel frameworks for secure network operations, privacy-preserving data sharing, and efficient AI deployment in distributed environments. Professor Xu's publication record shows a clear trend toward integrating artificial intelligence with traditional networking challenges. His recent work explores federated learning security, encrypted traffic analysis using deep learning, and novel approaches to network security that leverage machine learning techniques. The interdisciplinary nature of his research spans computer networking, security, privacy, and artificial intelligence. Professor Xu has received recognition for his contributions to network security and privacy-preserving technologies through publications in top-tier venues including IEEE journals, ACM conferences, and security symposia. His work has appeared in IEEE Transactions on Dependable and Secure Computing, IEEE/ACM Transactions on Networking, and security conferences like CCS and NDSS. Professor Xu actively collaborates with researchers across institutions, supervising students and junior researchers in exploring cutting-edge problems in network security and AI. His research has been supported by significant grants focusing on network security, privacy, and intelligent networking infrastructure. He leads projects that address fundamental challenges in secure communication, privacy-preserving data analysis, and intelligent network management. Professor Xu is involved with research laboratories focusing on network security and intelligent systems at Tsinghua University. His team works on developing practical security solutions, privacy frameworks, and AI-enhanced networking protocols that address real-world challenges in today's increasingly connected world.

• High Performance Computing
• Numerical Algorithms and Software
• High Performance Big Data Analytics
• +۴ مورد دیگر

Panruo Wu is an Associate Professor in the Department of Computer Science at the University of Houston (UH). He joined UH in 2018 as an Assistant Professor, transitioning to his current rank. His research focuses on high-performance computing, numerical algorithms, parallel and distributed systems, and fault tolerance. He holds a Ph.D. in Computer Science from the University of California, Riverside (2016), advised by Zizhong Chen, and a B.S. in Mathematics from the University of Science and Technology of China (USTC). Research Interests: His work spans high-performance computing, numerical linear algebra, GPU acceleration, fault-tolerant systems, and scalable machine learning. Key projects include LATER (Linear Algebra on Tensor Cores), LibKernel (a scalable kernel machine framework), and Wukong (a serverless parallel computing framework). He emphasizes energy-efficient and hardware-aware algorithms. Publications: Dr. Wu's recent work includes advancements in QR factorization using tensor cores, symmetric eigenvalue decomposition optimizations, and fault-tolerant algorithms for heterogeneous systems. His research often addresses computational challenges in big data and exascale computing. Awards & Grants: Received NSF Grant No. 2146509. His work on high-accuracy matrix computations was a Best Paper Nominee at HPDC'20. He has authored over 30 peer-reviewed publications in top venues like SC, ICS, and IEEE TPDS. Students & Advising: Advises PhD students including Shaoshuai Zhang, Ruchi Shah, Benjamin Carver, and Ao Wang. His students have contributed to projects like LibKernel and fault-tolerant linear algebra libraries. Labs & Collaborations: Leads research in UH's high-performance computing group, collaborating with institutions like Jack Dongarra's Innovative Computing Lab (University of Tennessee) and industry partners on exascale computing initiatives.

Ian D'Souzaمشاهده پروفایل

استاد بالینی

• Behavioral Finance
• Experimental Finance
• Blockchain
• +۱۳ مورد دیگر

Ian D'Souza is a Clinical Professor of Finance at the Leonard N. Stern School of Business, New York University, where he has been teaching since 2006. His expertise lies at the intersection of finance, technology, and behavioral economics, with a strong focus on blockchain, DeFi, and experimental finance. He is also an Associate Editor for the Journal of ESG and Impact Investing and a founding member of the NYU Stern Family Office Council. His research explores innovative finance topics such as the use of alternative datasets—including satellite imagery, weather patterns, sentiment analysis, and distributed ledger forensics—in understanding market behavior, tail risks, and the interplay between human cognition and artificial intelligence. His work emphasizes non-normal return distributions, liquidity frictions, and network obsolescence. Professor D'Souza has received multiple teaching accolades, including the Stern MBA Professor of the Year, and was named a Favorite MBA Professor nationally by Poets & Quants. His insights have been cited by the District Court of New York, the White House OMB, and the FCC, and he frequently presents to corporate boards and media outlets. Stern MBA Professor of the Year Recognized as a Favorite MBA Professor across America (Poets & Quants magazine) He advises several family offices, managed funds, and endowments on traditional and emerging asset classes, including climate finance and infrastructure. His leadership extends to past roles as CIO at TMT-focused funds and M&A/bankruptcy expert at Rothschild Inc. He has led international teams across Australia, Asia, Europe, North America, and Africa and has served on corporate boards. He is actively involved in academic and professional communities through the NYU Stern Family Office Council and editorial work, and his research continues to influence both policy and investment practice.

Henry F. (Hank) Korthمشاهده پروفایل

استاد

• Database Systems
• Blockchain Systems
• Distributed Systems
• +۷ مورد دیگر

Henry F. (Hank) Korth is a Professor of Computer Science and Engineering at Lehigh University, with a courtesy appointment in the Department of Decision and Technology Analytics in the College of Business. He serves as Director of the Blockchain Lab in the Center for Financial Services and Co-Director of the Computer Science and Business Program. Korth is a Fellow of the ACM and IEEE, and a recipient of the VLDB 10-Year Award and Bell Labs President's Silver Award for contributions to database technologies. PhD in Computer Science from Princeton University MA, MSE in Computer Science from Princeton University BA in Mathematics from Williams College Korth's research spans database systems, blockchain systems, distributed systems, and real-time systems. He has pioneered transaction management in parallel and distributed systems, query processing, and the impact of modern computing architectures on database performance. His recent work focuses on blockchain applications in enterprise databases, including acceleration of zero-knowledge proofs, benchmarking frameworks, central-bank digital currencies, and private-yet-provable accounting systems. His contributions are rooted in both theoretical advancements and practical implementations, such as the QTM™ aggregation engine and the DataBlitz™ main-memory storage manager. Scientific awards include: ACM Fellow IEEE Fellow 10-Year Award at the VLDB Conference Bell Labs President's Silver Award Korth actively supervises research within the Blockchain Lab and is affiliated with the Scalable Software Systems Research Group at Lehigh. His scholarly output reflects a deep engagement with blockchain benchmarking, concurrency control, verifiable databases, and the evolution of database systems in response to technological shifts.

Mohsen Lesaniمشاهده پروفایل

دانشیار

• Reliability of software systems
• Security of software systems
• Concurrent systems
• +۱۲ مورد دیگر

Mohsen Lesani is an Associate Professor in the Computer Science and Engineering Department at the University of California, Santa Cruz's Baskin School of Engineering. His research focuses on reliability and security of software systems, particularly concurrent and distributed systems, with recent emphasis on secure replicated systems and distributed machine learning. Dr. Lesani received his PhD from UCLA, MS in artificial intelligence from Sharif University of Technology, and BS in software engineering from University of Tehran. He was previously a postdoc at MIT. His educational background provides a strong foundation for his interdisciplinary research spanning programming languages, distributed systems, and security. His research interests center on creating reliable and secure distributed systems. Current projects include resilient and secure distributed systems, heterogeneous and reconfigurable secure distributed systems, automatic analysis and synthesis of replicated objects, verification of distributed systems, data analytics, secure exchange across blockchains, machine learning for performance models, domain-specific languages and type systems, and automatic fence insertion for concurrent systems. His work bridges theoretical foundations with practical implementations to address real-world challenges in distributed computing. Lesani's research has been recognized with several prestigious awards including the NSF CAREER award in 2020 and DARPA YFA award in 2022. His work has also received the SIGPLAN Research Highlight in 2019, a distinguished paper award at OOPSLA 2018, and a best paper award at ISSRE 2015. These accolades reflect the impact and quality of his contributions to the field. He actively mentors PhD students in the Safe and Secure Software (S3) lab, including Xiao Li, Eric Chan, Javad Saber-Latibari, and Tejas Mane. His research has been supported by multiple NSF grants, demonstrating sustained funding for his innovative work. Lesani serves on program committees for major conferences including POPL, PLDI, OOPSLA, and DISC, contributing to the academic community. Lesani leads the Safe and Secure Software (S3) lab at UC Santa Cruz, where his team works on cutting-edge research in distributed systems, programming languages, and security. The lab fosters a collaborative environment where theoretical insights are translated into practical systems that address real-world challenges in reliability and security of distributed applications.

Fan Zhangمشاهده پروفایل

استادیار

• Computer Security
• Applied Cryptography
• Decentralized Systems
• +۴ مورد دیگر

Fan Zhang is an Assistant Professor in the Department of Computer Science at Yale University. He holds a Ph.D. from Cornell University, advised by Ari Juels, and a B.S. from Tsinghua University. His research focuses on computer security, applied cryptography, decentralized systems, blockchains, and trusted execution environments (TEEs). He leads the Decentralized Systems Group at Yale and is affiliated with the IC3, CDCC, and CADMY centers. He teaches courses on blockchain and real-world cryptography. Key research interests include blockchain decentralization, privacy-preserving protocols, and secure distributed systems. Notable contributions include the Town Crier oracle system (acquired by Chainlink), the DECO TLS protocol, and foundational work on transaction order fairness and MEV mitigation. Awards include the Ethereum Foundation Academic Grant (2022) and the IBM PhD Fellowship (2018-2020). His work has been published in top venues like CCS, S&P, CRYPTO, and USENIX Security.

Victoria Lemieuxمشاهده پروفایل

استاد

• Blockchain Technology
• Trustworthy Records
• Records and Information Management
• +۸ مورد دیگر

Victoria Lemieux is a Professor at the University of British Columbia (UBC) Faculty of Arts, School of Information, and Cluster Lead for Blockchain@UBC, Canada’s largest research cluster focused on blockchain technology. Her research centers on risks to trustworthy records in blockchain systems and their impact on transparency, financial stability, and human rights. She has pioneered Canada’s first research-oriented graduate blockchain training program and organized multiple interdisciplinary summer institutes. Education: Ph.D. in Archival Studies from University College London (2002), Certified Information Systems Security Professional (CISSP, 2005). Affiliated with UBC’s Peter Wall Institute for Advanced Studies, Sauder School of Business, and Institute for Computers, Information and Cognitive Systems (ICICS). Research interests span blockchain technology , trustworthy records , risk management , information governance , and visual analytics , with recent work addressing healthcare data frameworks, Web3 AI integration, and socio-cultural dynamics of decentralized systems. She has published extensively on blockchain applications in archives, land transactions, and privacy-preserving technologies. Scientific Awards : 2015 Emmett Leahy Award 2015 World Bank Big Data Innovation Award 2016 Emerald Literati Award 2016 Emerald Literati Outstanding Paper Award Supervision: Currently accepts doctoral students in Computational Archival Science and blockchain-related archival research. Affiliated with the Blockchain@UBC cluster and multidisciplinary research teams exploring decentralized systems for social good.

Duc (David) Tranمشاهده پروفایل

دانشیار

• Network Computing
• Machine Learning
• Blockchain Technology
• +۳ مورد دیگر

Dr. Duc (David) Tran is a tenured Associate Professor in the Department of Computer Science at the University of Massachusetts at Boston. He directs the Network Computing Laboratory and focuses on network computing, with current projects in blockchain technology, decentralized learning, and edge computing. His research on peer-to-peer and decentralized networks has been widely cited. National Science Foundation funding recipient Best Theory Paper Award at IEEE MASS (2014) Best Paper Award at ICCCN (2008) IEEE Outstanding Graduate Student Award (2002) His research combines machine learning and decentralized techniques to optimize networked applications. Recent publications highlight blockchain for federated learning, edge computing, and automated market-making algorithms. He has also published cross-disciplinary work in medical imaging (2021) and obstetrics (2025). Dr. Tran actively contributes to academic service as an editor for Elsevier Ad Hoc Networks Journal, Springer Journal on Computational Social Networks, and Taylor Francis Journal on Parallel, Emergent, and Distributed Systems. He has served as TPC Chair for WiMAN, Guest-Editor for Pervasive Computing and Communications, and keynote speaker at WiMAN 2013.

Cecilia Boschiniمشاهده پروفایل

پژوهشگر

• Cryptography
• Post-Quantum Cryptography
• Lattice-Based Cryptography
• +۳ مورد دیگر

Cecilia Boschini is a Researcher affiliated with the Institute for Theoretische Informatik (Theoretical Computer Science) at ETH Zürich. Her work focuses on advanced cryptographic systems, particularly in post-quantum cryptography, lattice-based protocols, and privacy-preserving technologies. She contributes to developing secure digital signature schemes, threshold cryptography, and efficient cryptographic algorithms resistant to quantum computing threats. Her research bridges theoretical foundations with practical applications in cybersecurity and distributed systems. Key contributions include innovations in fail-stop signatures, two-round threshold signatures (Ringtail), and lattice-based multi-signature systems (MuSig-L). Boschini’s work emphasizes balancing security with efficiency, often addressing challenges in mobile device security and memory encryption. She has published extensively in top-tier venues, with a focus on cryptographic protocols that enhance privacy and data integrity without compromising usability.

Ivan Pudduمشاهده پروفایل

پژوهشگر

• Information Security
• Cybersecurity
• Computer Science
• +۳ مورد دیگر

Dr. Ivan Puddu is a Researcher affiliated with the Institute for Information Security at ETH Zürich. His work focuses on advancing cybersecurity, particularly in the realms of Trusted Execution Environments (TEEs), hardware security, and privacy-preserving technologies. He explores vulnerabilities in modern computing systems, including attacks on enclave-based security mechanisms and side-channel exploits. His research also addresses distributed systems, blockchain, and FPGA-accelerated architectures, aiming to enhance system sovereignty and data integrity. Notable contributions include studies on code confidentiality in TEEs, disaggregated memory systems, and mitigating security threats in low-power networks.

• Global Navigation Satellite Systems (GNSS)
• Avionics Systems
• Wireless Communication
• +۷ مورد دیگر

René Jr Landry is a full Professor in the Department of Electrical Engineering at École de technologie supérieure (ETS), Université du Québec, specializing in Global Navigation Satellite Systems (GNSS), avionics, and wireless communication technologies. His academic journey includes a B.Ing. from Polytechnique Montréal, M.Sc. from University of Surrey (UK), and Ph.D. from SupAréo in Toulouse. He maintains active research leadership through two key laboratories: LASSENA (Laboratory of Space Technologies, Embedded Systems, Navigation and Avionics) and LACIME (Communications and Microelectronic Integration Laboratory). His research spans critical aerospace navigation domains including GNSS signal processing, inertial navigation systems, software-defined radio for avionics, radio frequency interference mitigation, and indoor positioning technologies. Landry's work addresses real-world challenges in satellite navigation robustness, precision positioning in urban/denied environments, and next-generation avionic system security. His current projects focus on blockchain-enhanced IoT security, AI-driven GNSS disruption analysis, and adaptive RF front-ends for multi-band avionics applications. Analysis of his recent publications reveals strong emphasis on resilient positioning systems through multi-constellation integration (particularly Iridium-NEXT), blockchain applications for navigation security, and explainable AI techniques for GNSS signal quality assessment. His work increasingly bridges traditional navigation engineering with cutting-edge security and machine learning paradigms. 2014 Prix d'excellence du c.a. pour les services à la collectivité Landry has supervised over 100 graduate students across doctoral, master's, and research projects since 2005, with current supervision extending through Summer 2025. His research funding supports multiple industry partnerships focused on avionics certification, software-defined radio implementations, and next-generation navigation systems. The LASSENA laboratory under his leadership develops certified avionic products from open-source SDR platforms and advances multi-sensor fusion techniques for challenging navigation environments. His research infrastructure includes specialized facilities for GNSS signal simulation, avionics hardware testing, and multi-sensor integration. Current work emphasizes flight-tested validation of RF front-end technologies, blockchain-secured navigation data, and real-time interference mitigation systems for aviation applications.