Dr. Vinayak Ramkumar is a Postdoctoral Researcher at the Institute for Communications Engineering, Technical University of Munich (TUM), under Prof. Antonia Wachter-Zeh’s COD group. Previously, he was a Postdoctoral Fellow at Tel Aviv University (2023–2024) and a Visiting Researcher at Washington University in St. Louis. He earned his Ph.D. from the Indian Institute of Science (2023) under Prof. P. Vijay Kumar. His research focuses on Coded computation , Erasure codes for distributed storage , Information-theoretic privacy , Codes for low-latency streaming , and Quantum codes . Key contributions include explicit constructions of streaming codes and quantum locally recoverable codes. He has received prestigious awards, including the Qualcomm Innovation Fellowship India (2021) and the Prof. F. M. Mowdawalla Medal (2017–18) for his M.Sc. thesis. His work bridges theoretical foundations with practical applications in distributed systems and quantum computing.
Rafail Ostrovsky is a Distinguished Professor of Computer Science and Mathematics at UCLA, holding the Norman E. Friedman Chair in Knowledge Sciences at the Henry Samueli School of Engineering and Applied Science. As Director of the Center for Information and Computation Security, he leads research in cryptography, theoretical computer science, and secure computation with over 350 refereed publications and 15 issued USPTO patents. His primary research focuses on cryptography and theoretical computer science, with significant contributions to private information retrieval, zero-knowledge proofs, secure multi-party computation, and privacy-preserving technologies. His work bridges theoretical foundations with practical applications in network security, data analysis, and cryptographic protocols. Dr. Ostrovsky's research has evolved from fundamental cryptographic primitives to complex systems addressing modern security challenges in distributed environments, with recent work emphasizing efficient secure computation, robust protocols, and privacy-preserving techniques for high-dimensional data. His publication record demonstrates consistent leadership in cryptography, with recent articles focusing on zero-knowledge systems, secure computation protocols, and cryptographic primitives with enhanced security properties. The research trends show increasing emphasis on efficiency, robustness against malicious adversaries, and practical implementations of theoretical cryptographic concepts. 1993 Henry Taub Prize 2017 IEEE Computer Society Edward J. McCluskey Technical Achievement Award 2018 RSA Award for Excellence in Mathematics 2022 W. Wallace McDowell Award (highest award from IEEE Computer Society) Fellow of AAAS, ACM, IEEE, and IACR Foreign member of Academia Europaea Fellow of the National Academy of Inventors Dr. Ostrovsky has held significant leadership roles including chair of the IEEE Technical Committee on Mathematical Foundations of Computing (2015-2018) and chair of the IEEE FOCS 2011 Program Committee. He has served on over 40 international conference program committees and currently serves on editorial boards for Journal of ACM, Algorithmica Journal, and Journal of Cryptology. At UCLA, he teaches foundational courses including Introduction to Cryptography (CS183), Foundations of Cryptography (CS282A/M209A), and Cryptographic Protocols (CS282B/M209B). As Director of the Center for Information and Computation Security, Dr. Ostrovsky leads a multidisciplinary team advancing research in cryptography, network security, and privacy technologies. His group collaborates across computer science, mathematics, and engineering disciplines to develop innovative solutions for contemporary security challenges, with upcoming work focusing on obfuscation, proof systems, and secure computation as evidenced by his scheduled visiting scientist position for Summer 2025.
Xiao Wang is an Assistant Professor of Computer Science at Northwestern University, specializing in applied cryptography with a focus on privacy-preserving systems, secure multi-party computation, and zero-knowledge proofs. He holds a PhD from the University of Maryland and completed postdoctoral fellowships at MIT and Boston University. His research bridges theoretical cryptography and practical applications in machine learning, databases, health informatics, and legal domains. Education: Postdoctoral Fellowship: MIT & Boston University (2018–2020) PhD in Computer Science: University of Maryland (2015–2019) B.E. in Computer Science: Hong Kong University of Science and Technology (2011–2015) Research Interests: Secure computation frameworks (MPC, ZK) Privacy-preserving machine learning Cryptographic protocol design Applications in healthcare and legal systems Publications Trends: Recent work emphasizes scalable MPC protocols (e.g., BitGC), privacy in machine learning (Confidential-DPproof), and cross-domain applications like secure reporting systems. Over 40 peer-reviewed papers in top venues (CCS, S&P, Eurocrypt, USENIX Security) reflect his focus on both theoretical rigor and practical usability. Awards: ACM CCS Best Paper (2017, 2021) CSLAW Best Paper (2025) ICLR Spotlight Award (2024) Multiple industry-recognized competitions (iDASH 2015) Advising & Grants: Supervises a dynamic PhD/postdoc team (10+ active researchers). Leads NSF CAREER project on MPC systematization. Collaborates with Chicago-area hospitals and VA on secure health data analytics. Co-develops tools like ObliVM and ZKSMT . Labs/Teams: Core member of Northwestern's Cryptography and Privacy Engineering Group . Co-leads the MPC Tall Order initiative for standardized MPC frameworks. Partner in NIST threshold cryptography projects.
Aydin Abadi is an Assistant Professor at Newcastle University, specializing in cryptography, privacy-preserving technologies, and blockchain applications. His research focuses on secure multi-party computation, privacy-enhancing technologies (PETs), and financial fraud prevention through advanced cryptographic protocols. Education: PhD in Secure Multi-party Computation, University of Strathclyde MSc Computer Science, University of Leeds BSc Software Engineering, University of Lahijan, Iran Diploma in Mathematics and Physics, Iran Research Interests include Privacy-Preserving Machine Learning, Blockchain Security, Post-Quantum Cryptography, and the development of efficient cryptographic protocols using algebraic structures and data optimization techniques. He actively contributes to open-source projects, such as Functional Oblivious Transfer and Supersonic OT implementations, and collaborates with industry partners like Privitar and Cardiff University. Awards include the joint first prize in the UK-US Privacy Enhancing Technology Prize Challenge (2023) for the STARLIT project and the Euan Minto Prize for best research paper (2015). His work is funded by initiatives like the UK’s REPHRAIN national research center. He advises PhD candidates and postdocs in areas like cryptography, blockchain, and secure payment protocols. His recent grants and projects focus on mitigating cryptocurrency fraud and enhancing federated learning security. Labs and teams include collaborations on decentralized applications (DApps), smart contract development, and cryptographic software tools hosted on GitHub (e.g., Helix-Priority-OTs and O-PSI).
Binbin Chen is an Associate Professor in Information Systems Technology and Design at Singapore University of Technology and Design (SUTD). His research focuses on enhancing the security and efficiency of interconnected systems like cyber-physical systems and IoT networks. Prior to his current position, he earned a PhD from National University of Singapore (NUS) and a Bachelor's from Peking University, both in Computer Science. Key research areas include smart grid security, networked systems algorithms, and safety-security co-analysis. Notable contributions include work on RFID protocols, fault-tolerant distributed systems, and secure substation control mechanisms. His research has been funded by Singapore's Energy Market Authority (EMA), A*STAR, and the Singapore Cybersecurity Consortium. Publications highlight advancements in secure substation command delaying, privacy-preserving electricity data sharing, and fault-tolerant aggregate function computation. He leads development of tools like CyberSAGE for cyber-physical system security assessment and SoftGrid for substation cybersecurity testing. Received Best Paper Award at ACM SIGCOMM 2010 Contributed to over 30 peer-reviewed journal/conference publications Active in professional service including journal reviewing and conference organization Current research emphasizes integrating security and safety engineering principles in critical infrastructure systems, with particular focus on railway and smart grid resilience.
Stephanie Balzer is an Assistant Professor in the Principles of Programming Group of the Computer Science Department at Carnegie Mellon University. Her office is located in 9004 Gates-Hillman Center, and she can be reached at balzers@cs.cmu.edu with administrative support from Oliver Moss. Dr. Balzer received her PhD from ETH Zurich under the supervision of Thomas R. Gross. Her academic trajectory shows consistent focus on formal methods and programming language theory from her early work on object relationships through to her current research on verification systems. Her research program aims to enable the construction of failure-free software that is correct by design and secure to run. She deploys rigorous reasoning methods such as type systems and verification logics to formally prove adherence to desired properties. Her work emphasizes compositional methods for scalability and addresses verification needs arising from real-world problems. Dr. Balzer's interests span Programming Languages, Pure and Applied Logic, Software Verification, Type Theory, and Security . A driving force underlying her research is the belief that powerful solutions are fundamentally based on simple ideas that can be conveyed to and appreciated by non-experts. Analysis of Dr. Balzer's publication record reveals a sustained focus on session types, logical relations, and concurrent systems verification. Her recent work shows increasing sophistication in handling timed protocols, information flow control, and heterogeneous applications. She consistently publishes in top-tier venues including POPL, PLDI, ICFP, and ECOOP, often receiving distinguished paper awards for particularly impactful contributions. NSF CAREER Award on "A Semantic Framework for Verifying Heterogeneous Applications" (2024) ACM SIGPLAN Distinguished Paper Award (2023) ECOOP Distinguished Paper Award (2022) Supervised PhD student Jules Jacobs received Cum Laude distinction (2024) Dr. Balzer has secured significant research funding including an NSF CAREER Award (2025), an NSF Award on Integrated Verification of IoT and Real-time Communication Protocols (2022), an AFOSR Award (2021), CyLab Seed Funding (2020), and previous NSF and Mozilla Research Grants. She actively mentors a diverse research group including PhD candidates Yue Yao, Yinsen (Tesla) Zhang, and Zak Kent (co-advised with Guy Blelloch), as well as M.S. and undergraduate researchers. Her supervision extends to postdoctoral fellows and thesis committee roles for other students. Dr. Balzer leads research activities within CMU's ForML Lab and maintains active collaborations with researchers at ETH Zurich, Radboud University Nijmegen, and Cornell University. She plays significant leadership roles in the programming languages community including as founder of the PL Scholars Network, steering committee chair of the Programming Languages Mentoring Workshop (2023-2025), and co-organizer of the Oregon Programming Languages Summer School (2023).
Dr. Gabriel Kaptchuk is an Assistant Professor in the Computer Science Department at the University of Maryland, College Park (UMD), affiliated with UMIACS and MC2. He focuses on applied cryptography, privacy, and interdisciplinary work at the intersection of computer science and law. Previously, he was research faculty at Boston University and earned his Ph.D. from Johns Hopkins University under advisors Avi Rubin and Matt Green. His research includes secure multiparty computation (MPC), zero-knowledge proofs, steganography, and human-centered cryptography. He emphasizes ethical and societal implications of cryptographic systems and collaborates across disciplines to address privacy challenges in real-world contexts. Education: Ph.D., M.S., and B.S. in Computer Science from Johns Hopkins University (2015–2020). Research Interests: Applied cryptography, privacy-preserving technologies, secure multiparty computation, steganography, usable security, and cybersecurity policy. His work bridges technical and social aspects of cryptography, advocating for systems that account for power dynamics and societal impacts. Recent projects include frameworks for harm-aware data release, secure steganography in diffusion models, and privacy-focused research agendas for marginalized communities like sex workers. Teaching: Taught courses on network security, law and algorithms, and algorithmic governance at UMD and Boston University. Recent courses include INST878D/CMSC839C: Governing Algorithms and Algorithmic Governance and DS457/DS657/JD673: Law and Algorithms . Grants & Awards: Notably, his work on user expectations in differential privacy received a Best Paper Runner-up at ACM CCS 2021. He actively engages in policy discussions, including responses to NIST guidelines and technical research agendas for digital intimacy and smart home security. Labs/Teams: Leads research groups exploring MPC for social good, steganography, and privacy-preserving technologies. Collaborates with interdisciplinary teams in policy, law, and ethics to ensure technical solutions align with societal values.
Jonathan Katz is a Professor in the Department of Computer Science at the University of Maryland, affiliated with the College of Computer, Mathematical, and Natural Sciences. He holds appointments in both Computer Science (CS) and Electrical and Computer Engineering (ECE). His research focuses on cryptography, cybersecurity, and theoretical computer science, with contributions to cryptographic protocol design, post-quantum cryptography, and secure multiparty computation. He has led the Maryland Cybersecurity Center (2013–2019) and served as an Eminent Scholar in Cybersecurity at George Mason University (2019–2020). Education: Ph.D. in Computer Science from Columbia University (2002), B.S. in Mathematics and Chemistry from MIT (1996). Awards: ACM Fellow (2021), IACR Fellow (2019), ACM SIGSAC Outstanding Contribution Award (2019), UMD Distinguished Scholar-Teacher (2017), Humboldt Research Award (2015), NSF CAREER Award (2004). Research Interests: Cryptographic protocols, post-quantum security, privacy-preserving computation, and blockchain technologies. Notable contributions include foundational work on password-based authenticated key exchange and co-authoring the textbook Introduction to Modern Cryptography . Students Advised: Includes PhD candidates such as Kasra Abbaszadeh, Noemi Glaeser, and Benjamin Sela. His work has been supported by grants from NSF, DARPA, and industry partnerships. Labs/Teams: Active in the Joint Center for Quantum Information and Computer Science (QuICS) and the Maryland Cybersecurity Center, focusing on post-quantum cryptography and secure distributed systems.
Dana Dachman-Soled is an Affiliate Associate Professor in the Department of Computer Science at the University of Maryland, with a joint appointment in the Department of Electrical and Computer Engineering. Her research focuses on cryptography, algorithmic fairness, and theoretical computer science, with applications to post-quantum security, privacy-preserving algorithms, and secure multiparty computation. She has advised at least one PhD student, Yvonne Zhou. Her work combines foundational cryptographic theory with practical implementations, addressing challenges such as tamper-resistant data encoding, fair machine learning, and secure communication protocols. In 2023, she received a $1M NSF award for research on post-quantum cryptography. She has contributed to advancements in non-malleable codes, leakage-resilient cryptography, and the security of lattice-based schemes like LWE and NTRU. Her research also explores ethical AI, including fairness in data classification and privacy-preserving synthetic data. She has published extensively in top venues like ITC, CRYPTO, and IEEE conferences, with a focus on cryptographic primitives, side-channel vulnerabilities, and algorithmic bias mitigation. Dr. Dachman-Soled collaborates widely, with grants supporting her work on non-malleable codes and the theoretical foundations of secure computation. Her lab engages in interdisciplinary projects at the intersection of computer science, mathematics, and cybersecurity.
Felice Manganiello is an Associate Professor and Associate Director for Mathematics and Statistics Education in Clemson University's College of Science, Department of Mathematical and Statistical Sciences. His research specializes in coding theory with applications to quantum computing, cryptography, and secure communications. His work bridges theoretical mathematics and practical implementations in information security and distributed systems. Research interests include the development of quantum-resistant cryptographic systems, error-correcting codes for quantum computing, and secure multiparty computation protocols. Recent publications focus on constructing specialized codes for quantum fault tolerance, developing zero-knowledge proof systems, creating efficient batch coding schemes for distributed storage, and designing secure computation methods for matrix operations. His work demonstrates consistent innovation in applying algebraic structures to solve contemporary challenges in information security and network communications.
Joshua Brody is an Associate Professor in the Computer Science Department at Swarthmore College, where he has been faculty since 2014. His research focuses on theoretical computer science, particularly communication complexity and its applications to algorithms, data structures, and property testing. He holds a Ph.D. from Dartmouth College (2010), with postdoctoral work at Tsinghua University and Aarhus University. Brody has taught courses such as Data Structures and Algorithms, Competitive Programming, and Theory of Computation. His work spans over 30 publications in top conferences like CCC, FOCS, and SODA, and he has secured grants including a Danish Council research award. He advises undergraduate researchers and coaches the Swarthmore ICPC programming team. Education: Ph.D., Computer Science, Dartmouth College (2010) M.S., Computer Science, New York University (2005) B.S., Mathematics/Computer Science, Carnegie Mellon University (1997) Research Interests: Brody’s work emphasizes lower bounds in communication complexity, query complexity, and their implications for streaming algorithms, data structures, and cryptographic protocols. He explores how communication constraints influence computational efficiency and has developed techniques to derive impossibility results across domains. Grants & Awards: Notable funding includes a Lower Bounds via Communication Complexity grant from the Danish Council (2011–2013) and the Eugene M. Lang Faculty Fellowship (2018). His work bridges foundational theory and practical applications, such as anomaly detection in streams and secure multiparty computation. Teaching: Brody has taught foundational courses like CS 35 (Data Structures) and specialized topics such as Cryptogenography and Randomized Algorithms. His courses emphasize competitive programming and algorithmic problem-solving.
Martin BRENNECKE is a doctoral researcher at the University of Luxembourg’s Interdisciplinary Centre for Security, Reliability and Trust (SnT), affiliated with the FINATRAX research group led by Prof. Dr. Gilbert Fridgen. He is pursuing a PhD in Computer Science and Engineering within the Doctoral Programme at the University of Luxembourg. His research bridges management and computer science, focusing on decentralized technologies like distributed ledgers, digital identities, and multiparty computations, particularly their societal and organizational impacts. He holds a master’s in International Economics and Governance and a bachelor’s in Philosophy and Economics from the University of Bayreuth, Germany, with an interdisciplinary focus on integrating economics, public policy, and philosophy into information systems research. **Research Contributions**: Martin has published in journals like Information Systems Frontiers and conferences such as ICIS and HICSS. His work explores blockchain governance, AI-driven cybersecurity, and socio-technical challenges in decentralized finance. His articles analyze topics ranging from Ethereum mixers to federated learning adoption strategies, reflecting a dual focus on technical innovation and socio-ethical implications. **Professional Involvement**: He serves as a reviewer for journals including Financial Innovation and conferences like ECIS and PACIS, and as an associate editor at the Academy of Management (AoM). Previously, he worked as a research assistant at Fraunhofer Institute and interned in e-commerce and automotive sectors, gaining industry insights into strategic information management and distributed ledger applications. **Technical Expertise**: His work emphasizes interdisciplinary collaboration, integrating computer science with management science to address challenges in digital transformation, energy transitions, and financial systems. Current research agendas include blockchain’s role in social justice and the human factors influencing blockchain ecosystem adoption.
Joerg Kliewer is a Professor in the Department of Electrical and Computer Engineering at NJIT. His research focuses on information theory, secure distributed computing, error correction, and network communication resilience. Education: Ph.D. in Electrical Engineering, University of Kiel (1999) M.S. in Computer Science, Stanford University (1984) Diploma in Electrical Engineering, Hamburg University of Technology (1993) Research: Develops coding schemes for distributed storage, privacy-preserving machine learning, and straggler-tolerant cloud computing. Recent work includes federated learning optimization and reinforcement learning-based decoding.
Dr. Shaoquan Jiang is an Assistant Professor at the University of Windsor's School of Computer Science. He holds a Ph.D. in Electrical & Computer Engineering from the University of Waterloo (2005). Research interests: His work spans network security architectures, cryptographic protocol design, blockchain implementations, quantum-resistant cryptography, and security education frameworks. Current projects focus on post-quantum security and authentication systems. Teaching: He instructs courses in cryptography, network security, and cyber security fundamentals at undergraduate and graduate levels.
Fatemeh Rezaeibagha is Senior Lecturer in Cyber Security at Murdoch University's School of Information Technology. Her research develops cryptographic solutions for blockchain systems, IoT security, and privacy-preserving protocols. Awards include the Associate Fellow teaching certificate (2019) and Murdoch Fellowship (2023). Recent publications focus on: privacy-enhanced data sharing for medical IoT; redactable blockchain architectures; attribute-based access control; and lattice-based cryptography. Applied contributions include traceability-revocation schemes for industrial IoT and accountable systems for vehicular networks. Research emphasizes efficiency and post-quantum security in distributed environments.
