جست‌وجوی استاد و پژوهشگر

• Computer Architecture
• Datacenter Systems
• Cloud-Native Server Architecture
• +۷ مورد دیگر

Babak Falsafi is a Full Professor at the School of Computer and Communication Sciences (IC) at EPFL, leading the Parallel Systems Architecture Laboratory (PARSA). He is a renowned expert in computer architecture, datacenter systems, and cloud-native server design. His research focuses on post-Moore era computing, emphasizing heterogeneous architectures, energy efficiency, and scalable IT infrastructure. Falsafi is the founder of EcoCloud, an EC-sponsored industrial-academic consortium investigating sustainable information technology. He holds ACM and IEEE fellowships, a Sloan Research Fellowship, and has contributed to major projects like Optimus Prime (data transformation acceleration), AstriFlash (flash-based online service systems), and Midgard (virtual memory re-design). His work spans hardware-software co-design, memory systems, and security. Falsafi advises numerous PhD students and collaborates with industry partners such as Google and Cavium. Key achievements include pioneering scalable multiprocessor architectures, snoop filters in IBM BlueGene, and spatial memory streaming in ARM cores. His lab develops open-source tools like QFlex for server simulation. He frequently presents at top conferences (HPCA, ISCA, MICRO) and chairs workshops on post-Moore infrastructure. Teaching roles include leading courses in computer architecture and parallel systems across multiple EPFL departments (SIN, EDIC, SSC, SMA). His work addresses datacenter challenges like the 'data tax' and mitigating latency through specialized accelerators.

David Basinمشاهده پروفایل

استاد

• Information Security
• Formal Methods
• Cryptography
• +۳ مورد دیگر

David Basin is a Full Professor at the Department of Computer Science, ETH Zurich, and heads the Information Security Group. He has held academic positions since 2003, including roles at the University of Freiburg (1997–2002) and the Max-Planck-Institut für Informatik (1992–1997). His research focuses on Information Security, including methods and tools for secure systems, formal verification, and cryptographic protocols. He is Editor-in-Chief of the ACM Transactions on Privacy and Security and Springer's Information Security and Cryptography book series. Basin founded the Zurich Information Security Center (ZISC) in 2003 and led it until 2011. Education: B.Sc. in Mathematics (Reed College, 1984), Ph.D. (Cornell University, 1989), and Habilitation (University of Saarbrücken, 1996). Research interests span formal methods for security protocol verification, privacy-preserving systems, and cryptographic implementations. He has contributed to foundational work on security protocols, including the Tamarin verification framework. His work addresses real-world systems like payment protocols (EMV), DNS security, and database isolation guarantees. Awards: ACM Fellow (2018) for contributions to Information Security and Formal Methods, IEEE Fellow. He has organized numerous conferences, including IEEE S&P, Euro S&P, and ACM CCS. Labs/Teams: Leads the Information Security Group at ETH Zurich and co-founded Anapaya Systems, a startup focused on network security solutions. His team develops tools like VeriMon (formally verified monitoring) and Tamarin for protocol analysis.

Zhendong Suمشاهده پروفایل

استاد

• Programming Languages
• Compilers
• Software Engineering
• +۳ مورد دیگر

Zhendong Su is a full professor in the Department of Computer Science at ETH Zurich since August 2018. Previously, he held a full professorship at UC Davis from 2003 until June 2019. He earned his Ph.D. in Computer Science from UC Berkeley and dual Bachelor’s degrees in Computer Science and Mathematics from UT Austin in 1995. Affiliations: ETH Zurich: Full Professor (since 2018) UC Davis: Full Professor and Chancellor’s Fellow (2003–2019) IEEE Fellow, ACM Fellow, and Member of Academia Europaea His research focuses on programming languages, compilers, software engineering, computer security, and education technologies . Key contributions include compiler validation (e.g., Project Yin-Yang for SMT solvers and DBMS testing), testing tools like SQLancer, and educational innovations such as the Algot visual programming language. Recent work emphasizes secure AI (e.g., CipherSteal for TEE-shielded models) and compiler reliability (e.g., Artemis/Apollo for JIT validation). He has pioneered techniques like metamorphic testing and equivalence modulo inputs (EMI) for compiler validation, uncovering thousands of bugs in GCC/LLVM and SMT solvers. Awards: ICSE MIP Award (2022), ACM SIGSOFT Impact Paper (2018), NSF CAREER Award, and multiple industrial awards. His students have won IEEE TCSE Rising Star and SIGSOFT Impact Paper awards, securing roles at top universities and companies like Google and NVIDIA. Service: Steering committee member of ISSTA and ESEC/FSE, ACM Distinguished Speaker, and Associate Editor for ACM TOSEM. Program chaired ISSTA 2012 and co-chaired FSE 2016. Labs/Teams: Leads research groups on compiler validation, secure AI, and education technologies. Projects include Yin-Yang (SMT testing), SQLancer (DBMS fuzzing), and Algot (visual programming for education).

Hongwei Wangمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Interconnected Systems
• Large Language Models
• +۶ مورد دیگر

Dr. Hongwei Wang is a Senior Researcher at Tencent AI Lab Seattle , specializing in applied machine learning for Natural Language Processing and Interconnected Systems . His work bridges Knowledge Graphs , Recommender Systems , and Graph Neural Networks , with a focus on large language models and retrieval-augmented generation. Ph.D. (2018), B.E. (2014) in Computer Science from Shanghai Jiao Tong University Postdoctoral Researcher : Stanford University (2019-2021), University of Illinois Urbana-Champaign (2021-2022) Dr. Wang’s research explores integrating Knowledge Graphs with Graph Neural Networks to enhance recommendation systems, language models, and information retrieval. His work spans Retrieval-Augmented Generation , Representation Learning , and GAN-based Graph Modeling , with recent papers on State-Space Exploration for LLM agents and Semantic Watermarking . His 15 most recent publications (2022-2024) focus on Retrieval Granularity , Interactive Memory , and Agent Systems , with keywords spanning Computer Science , Machine Learning , and Knowledge Graphs . Trends highlight advancements in Token-Level Semantic Matching , Schema-Guided Event Prediction , and Multi-Document Summarization . Scientific Awards: 2020 CCF Outstanding Doctoral Dissertation Award 2018 Google Ph.D. Fellowship Dr. Wang contributes to open-source projects like DKN and RippleNet , with 11 repositories on GitHub. He actively engages in Knowledge Graph Conferences (KDD, WWW, AAAI) and studies Chinese Classical Poetry and Film Arts .

David Cockمشاهده پروفایل

مدرس ارشد

• Formal Verification
• Operating Systems
• Hardware-Software Co-Design
• +۳ مورد دیگر

Dr. David Cock is a Senior Lecturer and Senior Researcher at ETH Zürich's Department of Computer Science, affiliated with the Systems Group. He holds a PhD from UNSW (2014) and a B.Sc. (hons) from UNSW (2004). His research focuses on formal verification, trustworthy systems, and hardware-software co-design, with notable contributions to projects like Enzian (a CPU/FPGA platform) and seL4 (formally verified kernel). He teaches Advanced Operating Systems and Informal Methods courses. Key achievements include the ACM Software System Award (2022) for seL4 and leadership in projects addressing hardware complexity and security. Research interests include formal methods for hardware modeling (Sockeye project), runtime verification, and mitigating timing channels. His work bridges theoretical foundations with practical systems, emphasizing secure and reliable computing platforms. Projects like Trustworthy BMC aim to enhance baseboard management systems' assurance. Collaborations span academia and industry, with open-source contributions to hardware designs and formal tools. Publications span formal verification, hardware modeling, and secure systems, with recent focus on heterogeneous computing and declarative hardware specifications. Teaching emphasizes practical formal techniques and OS design, leveraging real-world hardware (e.g., Barrelfish). His lab, the Systems Group, explores cutting-edge challenges in systems software and architecture.

Manos Athanassoulisمشاهده پروفایل

دانشیار

• Data Systems
• Cloud Data Management
• Database Systems
• +۷ مورد دیگر

Manos Athanassoulis is an Associate Professor in the Department of Computer Science at the College of Arts and Sciences, Boston University. He is the Founder and Director of the BU Data-intensive Systems and Computing (DiSC) lab and a member of the BU MiDAS group. His research focuses on data systems, particularly cloud data management, hybrid transactional/analytical workloads, and integration with emerging hardware such as non-volatile memory and heterogeneous computing. His educational background includes a PhD from EPFL (2014), an MSc in Computer Systems Technology, and a BSc in Informatics and Telecommunications from the University of Athens, Greece. Prior to BU, he was a Postdoctoral Researcher and Research Associate at Harvard University, supported by a SNSF Postdoc Mobility Fellowship. His research interests span data systems, database architectures, LSM trees, indexing, storage systems, and performance optimization. He explores how novel hardware can be leveraged to improve data management efficiency and scalability, especially in cloud environments. His recent publications (2021–2025) predominantly focus on LSM trees, covering topics such as compaction policies, Bloom filter tuning, DPU offloading, adversarial resilience, and sustainable caching. Earlier works include foundational contributions on access methods (RUM Conjecture) and optimal key-value stores (Monkey). The trend shows a consistent focus on data system efficiency, adaptability, and robustness under varying workloads and hardware constraints. Scientific Awards: NSF CAREER Award (2022) Facebook Faculty Research Award (2020) NSF CRII Award (2019) Best of VLDB 2017 and Best of SIGMOD 2017 SIGMOD Most Reproducible Paper Award (2017) Multiple ACM SIGMOD Distinguished PC Member recognitions (2018–2025) VLDB 2023 Best Demo Award RedHat Collaboratory Research Incubation Awards (multiple, 2021–2023) SNSF Postdoc Mobility Fellowship (2015–16) IBM PhD Fellowship (2011–12) Dr. Athanassoulis has advised numerous students and collaborators, evident from his co-authorship on works with researchers such as Niv Dayan, Stratos Idreos, and A. Ailamaki. His grants include major awards from NSF, Facebook, and RedHat, supporting research in robust data systems, hardware-software co-design, and learned cost models. He has also been recognized for teaching excellence at Harvard University. He leads the DiSC lab at Boston University, which focuses on data-intensive computing and systems research. The lab explores next-generation data architectures, particularly in cloud and hardware-aware environments. Collaborations with the BU MiDAS group enhance interdisciplinary research in data science and AI.

Tova Miloمشاهده پروفایل

استاد

• Databases
• Big Data Management
• Machine Learning for Data Management
• +۷ مورد دیگر

Professor Tova Milo is the Chair for Information Management at the School of Computer Science, Tel Aviv University, leading the prominent Databases Lab (DB Group). Her research spans databases, big data management, crowd-based data sourcing, and business process querying, with significant contributions to data integration and semi-structured data systems. Her research interests focus on innovative approaches to data management challenges through machine learning integration, crowd computing, and business process analysis. Key projects include Business Process Querying (BPQ) for analyzing BPEL specifications, MoDaS for crowd-based data management, and PROX for data provenance summarization. Her work bridges theoretical foundations with practical applications in fraud detection, recommendation systems, and data cleaning. Analysis of her recent publications reveals strong trends in human-in-the-loop data management systems, with growing emphasis on crowd integration for data cleaning and knowledge acquisition. Her research increasingly combines traditional database theory with machine learning techniques for scalable big data processing, while maintaining focus on business process modeling and provenance tracking. ACM PODS Alberto O. Mendelzon Test-of-Time Award (2010) ERC Advanced Investigators grant MoDaS (2011) The Weizmann Prize for Exact Sciences (2017) VLDB Women in Database Research award (2017) IEEE TCDE Impact award (2022) ISF Breakthrough Research Grant (2022) Doctorate Honoris Causa, University of Zurich (2023) ACM Fellow Member of Academia Europaea Professor Milo has advised over 30 graduate students including PhD candidates like Yael Amsterdamer and Ohad Greenshpan, and numerous MSc students working on projects including MoDaS, BPQ, and EDOS. Her research has been supported by major grants including the ERC Advanced Investigators grant and ISF Breakthrough Research Grant. She actively collaborates with industry partners including IBM and Microsoft, particularly in business process management standards. She directs Tel Aviv University's Databases Lab, which maintains the DB Group with multiple research streams including business process querying (BPQ), crowd-based data management (MoDaS), and self-adaptive data dissemination (EDOS/COLT). The lab operates from the Schreiber Building (M-20) and maintains strong international collaborations, particularly with European institutions through the ERC-funded MoDaS project.

Anastasios Vassilopoulosمشاهده پروفایل

استاد مدعو

• Composite Materials
• Wind Energy Structures
• Fatigue Analysis
• +۵ مورد دیگر

Anastasios Vassilopoulos serves as Head of the Composite Mechanics Group (GR-MeC) and Adjunct Professor at École Polytechnique Fédérale de Lausanne (EPFL), within the School of Architecture, Civil and Environmental Engineering. He directs the Doctoral Program in Civil and Environmental Engineering while maintaining active roles in the Structural Engineering Group and School Council. His research focuses on composite materials for renewable energy infrastructure , particularly wind turbine rotor blades. Key areas include fatigue analysis of adhesively bonded joints, experimental methods for FRP composites under complex loading, and design methodologies for composite structures. His work bridges fundamental mechanics with industrial applications through extensive collaboration with wind energy stakeholders. Analysis of his 15 most recent publications reveals dominant themes in thick adhesive joint mechanics (73% of articles), fatigue/fracture characterization (67%), and machine learning applications (40%). The research consistently targets wind turbine blade challenges, with 87% of articles addressing specific aspects of renewable energy infrastructure. Methodological trends show increasing integration of computational-experimental approaches and AI-driven predictive modeling. Dr. Vassilopoulos has secured 18 major research projects since 2000, primarily funded by Swiss National Science Foundation and international collaborations. Current projects include NSF-funded work on wind turbine blade adhesive joints (2020-2024) and fire-resistant composite bridge decks. His teaching portfolio includes advanced courses on composites design, structural mechanics, and floating offshore renewables. As Doctoral Program Director, he oversees PhD training while personally supervising 17 doctoral students to completion.

• Mathematical Physics
• Differential Geometry
• Topology
• +۴ مورد دیگر

Prof. Alberto S. Cattaneo is a faculty member at the University of Zurich, affiliated with the Department of Mathematics. He holds the rank of Professor and has been actively involved in teaching and research since at least 1998. His research interests span mathematical physics, differential geometry, topology, and interdisciplinary areas like computational biology, genomics, and digital forensics. He has developed courses on topics such as field theory, quantum mechanics, and differential manifolds, reflecting his expertise in theoretical and applied mathematics. Prof. Cattaneo has contributed to numerous publications, including works on distributed genomic analysis, sensor pattern noise (PNU) in forensics, and algorithm optimization for big data frameworks like Hadoop and Spark. His work bridges pure mathematics with applications in bioinformatics and cybersecurity. Though no awards are explicitly mentioned, his extensive publication record and teaching roles highlight his academic standing. He maintains an active presence through courses and research collaborations, with no indication of part-time roles or retirement.

Tomoë I. M. Steineckمشاهده پروفایل

مدرس

• East Asian Art History
• Visual Culture Studies
• Japanese History
• +۸ مورد دیگر

Tomoë I. M. Steineck serves as a Lecturer in East Asian Art History and Visual Culture at the University of Zurich, holding dual appointments in the Department of Art History and the Institute of Asian and Oriental Studies (AOI). She also functions as a Partnership Strategist responsible for advancing knowledge exchange between the University of Zurich and the Rietberg Museum of Zurich. Her academic journey includes a PhD in Japanese Studies from the University of Tübingen (2024), an MA with distinction from SOAS University of London (1999), and a BA from the University of Heidelberg (1995). Dr. Steineck's research specializes in decolonial perspectives on cultural imperialism, particularly examining the intersections of German-speaking Europe and Japan through missionary exchanges and religiously-based cultural criticism. Her work foregrounds the role of visual culture in shaping global cultural asymmetries while exploring subaltern resistance through visual vocality. Key projects include the Digital Humanities initiative Database Japanese Buddhist Art in European Collections (JBAE), a critical commentary on Inoue Tetsujirō's correspondence, and extensive provenance research on Japanese religious objects in European museums. Her scholarly output reveals consistent focus on Edo-period sacred art, Buddhist material culture in European collections, and Protestant-Japanese religious encounters. The publications demonstrate methodological diversity spanning art historical analysis, material culture studies, digital humanities, and critical decolonial theory, with increasing attention to visual representation in cross-cultural contexts since 2015. Promotionspreis der Universität Tübingen 2025 (Faculty Award for outstanding doctoral project) Independent Researcher Scholarship Award for Japanese Art History by the Culture Communication Fund, Amsterdam (2001) As a curator and academic, Dr. Steineck has secured institutional partnerships and research grants supporting her Digital Humanities projects and cross-institutional collaborations. Her work with the Ethnographic Museum of the University of Zurich, the Rietberg Museum, and Japanese institutions demonstrates her capacity to bridge academic research with museum practice. She leads the international cooperative project A Critical Commentary on Inoue Tetsujirō's Collected Correspondence and its Dissemination throughout East Asia in collaboration with NICHIBUNKEN. Dr. Steineck directs the Digital Humanities project Database Japanese Buddhist Art in European Collections (JBAE), developed in cooperation with Hosei University Tokyo and multiple European museums. This initiative represents a significant team effort involving researchers across Switzerland, Germany, and Japan focused on documenting and analyzing Japanese Buddhist objects in European collections through digital methodologies.

• Geometric Deep Learning
• Topological Deep Learning
• Topological Data Analysis
• +۷ مورد دیگر

Bastian Alexander Grossenbacher is a Full Professor of Machine Learning at the University of Fribourg, where he leads the AIDOS Lab within the Department of Informatics, Faculty of Science and Medicine. He holds secondary appointments at the Institute of AI for Health and the Helmholtz Pioneer Campus of Helmholtz Munich. He is also a TUM Junior Fellow and a member of ELLIS and AI-LIFE. He co-directs the Applied Algebraic Topology Research Network (AATRN) and is involved in the Topology, Algebra, and Geometry in Data Science (TAG DS) initiative. His research lies at the intersection of geometry, topology, and machine learning, with a focus on Geometric Deep Learning, Topological Deep Learning, and Topological Data Analysis. He develops novel machine learning methods that use topological and geometric priors to improve model robustness and interpretability, particularly in biomedical applications. His work spans theoretical foundations and practical implementations in areas such as single-cell analysis, medical imaging, and network science. The 15 most recent publications (2023–2025) reveal a strong trend toward integrating algebraic and differential topology into deep learning architectures. Key themes include the use of Euler Characteristic and magnitude transforms, curvature-based analysis of graphs and data, simplicial and manifold-based neural representations, and the application of topological methods to biomedical data. His articles appear in top-tier venues such as Nature Communications, ICML, NeurIPS, ICLR, and IEEE conferences, reflecting both theoretical depth and high-impact applications. ERC Starting Grant Bastian Rieck is actively involved in mentoring and academic leadership. He supervises PhD students and postdoctoral researchers in the AIDOS Lab and is open to new collaborations, particularly with candidates from interdisciplinary backgrounds. He has secured significant research funding, including the ERC Starting Grant, and leads multiple collaborative research initiatives. He emphasizes open science, sharing code, data, and educational materials publicly. He leads the AIDOS Lab, which focuses on advancing machine learning through topological and geometric principles. He is also a co-director of the Applied Algebraic Topology Research Network (AATRN), which hosts a large online seminar series. Additionally, he maintains DONUT, a curated database of non-theoretical applications of topology, and is active in the ELLIS and AI-LIFE networks, fostering international collaboration in AI and health.

Kenneth Patersonمشاهده پروفایل

استاد

• Cryptography
• Information Security
• Applied Cryptography
• +۳ مورد دیگر

Prof. Kenneth Paterson is a Full Professor at ETH Zürich's Department of Computer Science, leading the Applied Cryptography Group. He has held academic positions at Royal Holloway, University of London, and Hewlett-Packard Laboratories. His research focuses on cryptographic protocol analysis, provably secure solutions, and real-world system vulnerabilities. Key contributions include the Lucky 13 TLS attack, analyses of Telegram and OpenPGP, and work on cryptographic transition strategies. He has been recognized with awards such as the Google Distinguished Paper Award, IACR Fellowship, and ETH Golden Owl Teaching Award. His leadership roles include Department Head at ETH Zurich and Programme Chair for EUROCRYPT 2011. Paterson actively engages in standardization efforts through IRTF's CFRG and co-founded the Real World Cryptography workshop series. Education: B.Sc. (Mathematics, University of Glasgow, 1990), Ph.D. (Mathematics, University of London, 1993). Career highlights include EPSRC Leadership Fellowship (2010–2015) and IACR Distinguished Lecture at EUROCRYPT 2025. Research Interests: Cryptography, Information Security, Applied Cryptographic Protocols, TLS Analysis, Post-Quantum Cryptography, and Privacy-Preserving Technologies. Notable projects include cryptographic analysis of TLS, SSH, and cloud storage systems. Awards and Recognition: Google Distinguished Paper Award (2012) Applied Networking Research Prize (2013) IACR Fellow (2017) ETH Golden Owl Teaching Award (2022) Multiple Best Paper Awards at ACM CCS, CHES, and IEEE Security & Privacy Advising and Grants: Supervised students like Francesca Falzon and led projects funded by EPSRC, IRTF, and industry collaborations. Contributions to cryptographic agility and transition strategies for Internet protocols. Labs/Teams: Founder and Head of ETH Zurich's Applied Cryptography Group, associated with the Institute for Information Security. Collaborates with industry on cryptographic protocol development and security audits.

• Computer Architecture
• Distributed Systems
• Cloud Computing
• +۳ مورد دیگر

Javier Picorel is a former researcher at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Parallel Systems Architecture Lab (Parsa). His work focuses on computer architecture, distributed systems, and cloud computing, with an emphasis on optimizing storage systems, near-data processing, and high-performance computing. Picorel has contributed to advancements in scalable serverless computing, secure data center architectures, and accelerator design. His research interests include storage-class memory hierarchies, virtual machine performance optimization, and software-defined systems. Key projects include BlockNDP for block-storage acceleration, IndiLog for stateful serverless systems, and SPARTA for accelerator address translation. He has collaborated extensively with the Parsa group and published widely in top conferences such as ISCA, MICRO, and PACT.

Philippe Cudré-Maurouxمشاهده پروفایل

استاد

• Exascale Information Management
• Big Data
• Artificial Intelligence
• +۱۳ مورد دیگر

Philippe Cudré-Mauroux is a Full Professor at the University of Fribourg, Switzerland , where he leads the eXascale Infolab . He has held visiting researcher positions at MIT and Microsoft CISL , and serves on the Research Council of the Swiss National Science Foundation and the Scientific Advisory Board of the CHIST-ERA EU Research Programme . Research Interests: His work spans exascale information management , big data , AI , knowledge graphs , linked data , time series data repair , and emergent semantics . He focuses on building scalable, intelligent data systems that integrate storage, computation, and semantics. Publication Trends: His recent work emphasizes schema-aware knowledge graph completion , time series imputation and benchmarking , hardware-accelerated data systems , and large language models for data cleaning . His research bridges database systems, AI, and systems architecture, often targeting high-performance, real-world applications. Scientific Awards: ERC Consolidator Grant (2016) Google Faculty Research Award (2013) Verisign Internet Infrastructures Award (2012) Best Paper Awards at VLDB (2020), AAMAS (2019), and Swiss Data Science Conference (2020) EPFL Doctorate Award and Press Mention (2007) Best Mentor Award at ISWC (2010) Advising and Grants: He mentors a large group of researchers and students, many of whom are co-authors on his publications. He has secured significant funding, including a €2M ERC Grant and multiple Google and Amazon grants, supporting a vibrant research lab focused on next-generation data infrastructure. Labs and Teams: He leads the eXascale Infolab at the University of Fribourg, a dynamic research group actively publishing in top-tier venues and developing innovative tools for data management and AI integration.

Thomas Studerمشاهده پروفایل

استاد

• Logic
• Theoretical Computer Science
• Formal Methods
• +۴ مورد دیگر

Thomas Studer is a Professor of Computer Science at the University of Bern, leading the Logic and Theory Group. He holds a PhD in Computer Science from the University of Bern (2001) and has worked as a senior software engineer before returning to academia. His research focuses on mathematical logic, formal methods, blockchain technology, and data privacy. He serves on the board of the Swiss Society for Logic and Philosophy of Science and chairs the computer science committee for the Matura exam in Canton Bern. Research interests include justification logic, modal logics, proof theory, and applications in blockchain and secure systems. Recent work explores synergistic knowledge in distributed systems, conversational explanation frameworks, and probabilistic justification logics. He co-authored books on relational databases and logics of proofs. Leadership roles include the Executive Committee of SCNAT’s Platform MAP (2016–2024). He advises on technical and ethical challenges in AI and cryptography, contributing to international conferences and editorial boards.