Mariano Scazzariello is a Lecturer at KTH Royal Institute of Technology, Sweden, affiliated with the School of Electrical Engineering and Computer Science and the Department of Network and Systems Engineering. He teaches the course 'Network Systems with Edge or Cloud Datacenters (IK2227)'. His research focuses on advanced networking topics including machine learning in networks, high-speed packet processing, network emulation, and software-defined networking innovations. His work spans contributions to network emulation tools like Kathará and Megalos, stateful packet processing at terabit scales, and leveraging large language models (LLMs) for network configuration and vulnerability detection. Recent research emphasizes low-latency protocols (e.g., SRv6/DetNet integration) and GPU-centric networking on commodity hardware. Mariano’s publications (2020–2025) highlight expertise in network function virtualization, ASIC-based switching, and optimizing network configurations through AI-driven approaches. He has pioneered frameworks for evaluating routing protocols and virtualizing large network scenarios at scale.
Nadia Polikarpova is an Associate Professor in the Department of Computer Science and Engineering at the University of California, San Diego . She earned her PhD from ETH Zurich in 2014 under Bertrand Meyer , followed by postdoctoral research at MIT CSAIL with Armando Solar-Lezama . Her academic contributions have been recognized with prestigious awards including the 2020 Sloan Fellowship , 2020 Intel Rising Stars Award , and 2020 NSF CAREER Award . Polikarpova's research focuses on program synthesis , program verification , and type systems . She leads the Programming Systems group at UCSD and contributes to the IFIP Working Group 2.8 on Functional Programming since 2022. Her work spans foundational research and practical tools, including projects like Synquid , SuSLik , and Laurel that combine formal methods with machine learning for code generation. Her recent publications in venues like OOPSLA , NeurIPS , and ICFP reveal trends in AI-assisted programming , live programming environments , and formal verification . She has advised numerous PhD and Master’s students including Shraddha Barke , Zheng Guo , and Tristan Knoth , many of whom have moved to prominent academic and industry positions. Notable artifacts from her lab include tools like ColDeco for spreadsheet inspection and Superfusion for eliminating intermediate data structures. 2020 : Sloan Fellow 2020 : Intel Rising Stars Award 2020 : NSF CAREER Award 2021 : Distinguished Paper at POPL 2023 : Distinguished Artifact at PLDI 2023 : Distinguished Paper at OOPSLA Polikarpova actively contributes to academic service, serving on program committees for PLDI , POPL , and OOPSLA , and co-chairing the OOPSLA Review Committee in 2023. She has delivered keynotes at APLAS'20 and PLDI'24 , emphasizing the integration of large language models with formal methods.
Amir Ali Ahmadi is a Professor at Princeton University's Department of Operations Research and Financial Engineering (ORFE), with affiliations across multiple disciplines including PACM, Computer Science, Mechanical & Aerospace Engineering, Electrical Engineering, and the Center for Statistics and Machine Learning. He serves as Director of Princeton's Optimization and Quantitative Decision Science Certificate Program and has taken temporary roles at Citadel GQS (2021-2022) and Google Brain (2020-2021). His research bridges optimization theory , dynamical systems , and control theory , focusing on scalable algorithms for complex problems in robotics, autonomous systems, and machine learning. He has pioneered DSOS/SDSOS relaxations as alternatives to traditional sum-of-squares methods, enabling faster solutions through linear/second-order cone programming. Recent publications explore: Higher-order Newton methods for socially responsible investment Data-efficient learning of dynamical systems Computational complexity of local minima Robust-to-dynamics optimization frameworks Award highlights include: 2024 Egon Balas Prize in Optimization 2024 Princeton Engineering Council Teaching Award 2023 Distinguished Teaching Award (Princeton SEAS) 2019 NSF CAREER Award 2017 DARPA Young Faculty Award 2017 Sloan Fellowship in Computer Science He advises prominent researchers like Georgina Hall (Tucker Prize finalist) and Bachir El Khadir (Goldstine Fellow), and leads the Princeton Optimization Seminar and MURI project on Control-Oriented Learning on the Fly.
Andrew Miller is an Associate Professor in the Electrical and Computer Engineering department at the University of Illinois, specializing in Programming Languages, Formal Methods, Software Engineering, Security and Privacy, and Systems and Networking. His research focuses on blockchain technologies, cryptography, and secure systems. Professor Miller's research spans multiple critical areas in modern computer security. His work primarily focuses on blockchain technologies , where he has made significant contributions to understanding and improving the security, privacy, and performance of systems like Bitcoin and Ethereum. He has conducted empirical analyses of privacy in the Lightning Network and developed protocols for confidential smart contracts. His work in cryptography includes research on multiparty computation, zero-knowledge proofs, and formal methods for cryptographic protocol design. Miller also investigates security vulnerabilities in proof-of-stake systems and resource exhaustion attacks, contributing to the robustness of decentralized systems. His applied security research extends to privacy-preserving health applications, as evidenced by his work on the Safer Illinois platform for COVID-19 contact tracing. Miller's publication record demonstrates consistent contributions to top security and systems venues including IEEE Security & Privacy, ACM CCS, Financial Cryptography, and USENIX Security. His research shows a clear trajectory from foundational work in blockchain security to more applied systems addressing real-world privacy and security challenges. Recent work focuses on making multiparty computation services publicly auditable and developing decentralized identity solutions that maintain compatibility with existing systems. Distinguished Reviewer Award, IEEE Security & Privacy 2018 Professor Miller has advised students including Vivek Nair, who joined the prestigious Hertz Fellows program in 2022. He has taught various courses including Introduction to Algorithms & Models of Computation, Advanced Computer Security, Cryptography, Applied Cryptography, and Ideal Functionality in Cryptography. His research has received support through grants including the SaTC: CORE: Medium project on "Automated Support for Writing High-Assurance Smart Contracts" in 2018. Miller is actively involved in research groups focusing on blockchain security, cryptographic protocols, and privacy-preserving systems. His lab appears to collaborate extensively with researchers across multiple institutions, as evidenced by the diverse author lists on his publications. Current work seems to be focused on making decentralized systems more secure, privacy-preserving, and accessible for real-world applications.
Assia Mahboubi is a tenured researcher ( directrice de recherche ) at INRIA in the Gallinette team, Nantes, France, and an endowed professor in the Algebra and Number Theory section of the Vrije Universiteit Amsterdam, Netherlands. Her work bridges theoretical computer science and formal mathematics, with significant contributions to proof assistants and formal verification. Her research focuses on the foundations and formalization of mathematics in type theory, particularly on the automated verification of mathematical proofs. She explores the interplay between computer algebra and formal proofs, and is a key contributor to the Rocq prover (formerly Coq) and the Mathematical Components libraries. Her work often examines how familiar mathematical objects can be optimally represented for computer-aided proof checking. Recent publications show a strong trend toward categorical reasoning, diagram chasing, and continuity properties in constructive type theory, with increasing focus on practical applications of formal methods in computational mathematics. Her work demonstrates the maturation of formal verification techniques from theoretical foundations to practical tools for mathematical research. ERC Consolidator grant for the FRESCO (Fast and Reliable Symbolic Computation) project Mahboubi actively supervises doctoral students including Vojtěch Štěpančík, Tomás Vallejos Parada, and Alain Chavarri Villarello. She has received significant research funding through her ERC Consolidator grant for the FRESCO project, which aims to develop fast and reliable symbolic computation techniques. She is deeply involved in the international research community, serving on program committees for major conferences including POPL, CPP, and ICFP. She leads research in the Gallinette team at INRIA, which focuses on the intersection of proof assistants, programming languages, and formal mathematics. Her work has helped establish formal verification as a practical tool for mathematical research, moving beyond theoretical foundations to real applications in computational mathematics.
Supratik Chakraborty serves as the Bajaj Group Chair Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. He maintains dual affiliations with the Centre for Formal Design and Verification of Software and the Centre for Liberal Education at IIT Bombay, demonstrating his cross-disciplinary engagement. Professor Chakraborty's research spans formal methods with focus on formal verification, rigorous analysis of system models, and automated synthesis of systems from specifications. His work bridges theoretical foundations with practical applications, particularly in developing mathematically provable guarantees for increasingly complex hardware, software, and intelligent systems. Current research interests include constrained counting and sampling, scalable formal verification of software and hardware systems, automated synthesis of programs and circuits, and applications of automata, logic and finite model theory to practical verification challenges. His publication trajectory shows a significant evolution from traditional hardware and software verification toward addressing verification challenges in machine learning and AI systems. Recent work increasingly focuses on interpretability of black-box models, verification of neural networks, and synthesis techniques applicable to intelligent systems. The research demonstrates strong interdisciplinary connections between formal methods, programming languages, and artificial intelligence. IIT Bombay Excellence in Thesis (CSE) Award 2011 (for Bhargav Gulavani's thesis) IIT Bombay Excellence in Thesis (CSE) Award 2017 (for Abhisekh Sankaran's thesis) Best Paper in Algorithms and Architecture track at IEEE International Conference on Computer Design: VLSI in Computers and Processors, 1998 Professor Chakraborty has successfully supervised 11 doctoral students, with research spanning formal verification techniques, Boolean functional synthesis, constrained counting, and applications to hardware and software systems. His students have gone on to positions at major institutions including Microsoft Research, TCS Research, Georgia Tech, and BARC, reflecting the strong industry and academic impact of his mentorship. Current research directions show increasing emphasis on verification challenges posed by machine learning systems and AI. His research group at IIT Bombay, while not explicitly named in the materials, appears to focus on formal methods with strong connections to the Centre for Formal Design and Verification of Software. The group maintains active collaborations with international researchers including Moshe Y. Vardi at Rice University, and has made significant contributions to verification tools like VeriAbs that bridge theoretical advances with practical applications.
Debjit Pal is a Post-Doctoral Associate at the School of Electrical and Computer Engineering, Cornell University, and a member of the Computer Systems Laboratory. His research focuses on machine learning techniques for hardware verification, SoC validation, and FPGA optimization. Education: Ph.D. in Computer Engineering (University of Illinois at Urbana-Champaign, 2019) M.S. in Computer Science (IIT Kharagpur, 2012) B.E. in Electronics Engineering (Jadavpur University, 2008) Research Interests: Machine Learning for Electronic Design Automation (EDA) System-on-Chip (SoC) Verification Edge Intelligence as a Service Compiler Optimizations for Reconfigurable and High-Performance Computing Scientific Awards: IEEE CEDA Student Research Award (2016) Best Paper Nomination (ICCAD 2015, DAC 2018, ASP-DAC 2019) E. J. McCluskey Best Doctoral Thesis Competition Semi-Finalist (2020) Travel Grants for ICCAD/DAC/ASPDAC (2018-2019) Professional Roles: Technical Program Committee Member (DAC, VLSID), Reviewer (IEEE TVLSI, DATE, ICCAD). Collaborates with researchers like Zhiru Zhang and Shobha Vasudevan.
Henry Yuen is the Srivani Family Associate Professor of Computer Science at Columbia University, with affiliations in the CS Theory group, Data Science Institute, and Columbia Quantum Initiative. His work bridges theoretical computer science and quantum information, focusing on the computational foundations of quantum systems. Yuen received his BA in Mathematics from the University of Southern California (2010) and PhD in Computer Science from MIT (2016). His research explores quantum complexity theory, quantum cryptography, and quantum information through both theoretical frameworks and practical applications. His recent publications reveal a strong focus on quantum pseudorandomness, quantum circuit complexity, and quantum cryptographic primitives. The research trajectory demonstrates increasing sophistication in connecting quantum computational models with fundamental questions in complexity theory, particularly through the lens of quantum interactive proofs and quantum state complexity. His work frequently intersects with operator algebras and quantum information theory, reflecting the interdisciplinary nature of modern quantum computing research. NSF CAREER award Sloan Fellowship Yuen actively mentors graduate students, with several PhD students having graduated to postdoctoral positions or faculty roles. His service includes co-organizing the Columbia CS Theory Seminar and serving on program committees for major conferences including QIP, STOC, and ITCS. He has organized multiple workshops on quantum computing challenges and cryptography. As a member of the Columbia Quantum Initiative, Yuen contributes to Columbia's growing quantum ecosystem, collaborating across departments to advance both theoretical foundations and potential applications of quantum information processing.
Wolfgang Kunz is a Full Professor (C4, W3) and Chair of Electronic Design Automation at the Technische Universität Kaiserslautern since 2001. His academic career spans multiple prestigious institutions, including Goethe-University Frankfurt/Main and the University of Massachusetts, Amherst. He has held leadership roles such as Dean (2005-2007) and Vice-Dean (2007-2009) at TU Kaiserslautern. Habilitation (Dr. rer. nat. habil.), Computer Science, University of Potsdam (1996) Doctoral degree (Dr.-Ing.), Electrical Engineering, University of Hannover (1992) Dipl.-Ing. degree, Karlsruhe Institute of Technology (1989) His research focuses on hardware verification, security, and optimization, particularly in embedded systems and processors. His work on formal verification methods has been commercialized by companies like Synopsys, Mentor Graphics, and Siemens EDA. His 2016-2021 publications address critical security issues such as Spectre/Meltdown and introduce innovative verification frameworks adopted by industry leaders like Infineon and OneSpin Solutions. Scientific awards include the IEEE Fellow (2006), German IT Society Award (2005), and TU Kaiserslautern Distinguished Teaching Award (2016). He has served on editorial boards of major journals and coordinated the Erasmus Mundus European Master Program in Embedded Computing Systems since 2010. Key students: Jörg Bormann, Raik Brinkmann, Tobias Ludwig Collaborations: Siemens EDA, Infineon, AbsInt, Intel SCAP Spin-offs: LUBIS EDA, OneSpin Solutions
Remko Van Hoek serves as Professor of Practice in the Department of Supply Chain Management at the Sam M. Walton College of Business, University of Arkansas. He teaches Sourcing and Procurement courses across undergraduate, master's, and doctoral programs. Prior to joining the University of Arkansas, Dr. Van Hoek held academic positions in Europe and served as a visiting professor at Cranfield School of Management, complemented by extensive industry experience as a supply chain and procurement executive at global corporations including Nike, PwC, and The Walt Disney Company. He currently serves on the Council of Supply Chain Management Professionals (CSCMP) Board of Directors and acts as executive director of the CSCMP Supply Chain Hall of Fame hosted by the Walton College. Dr. Van Hoek's research centers on digital transformation in procurement and supply chain management, with particular focus on blockchain implementation, artificial intelligence applications, and sustainable sourcing practices. His work investigates how emerging technologies reshape procurement processes, supplier relationship management, and risk mitigation strategies. He explores innovative approaches to supplier diversity programs, ethical sourcing frameworks, and the strategic evolution of procurement from cost reduction to value creation. His research consistently bridges academic theory with industry practice through case studies from major corporations, developing actionable frameworks for practitioners facing digital disruption and sustainability challenges. Analysis of his 15 most recent publications (2023-2025) reveals dominant themes in AI-driven supply chain risk prevention, blockchain implementation for transparency, and sustainable supplier engagement. His work demonstrates consistent industry collaboration, drawing from case studies at Walmart, Moet Hennessy, and Bayer to address post-pandemic resilience challenges. A significant portion examines procurement's strategic evolution beyond transactional functions, with recurring emphasis on ethical considerations in digital transformation and the practical implementation barriers for emerging technologies in global supply networks. As a Professor of Practice, Dr. Van Hoek integrates executive-level industry experience into curriculum development and student mentorship. His industry-engaged teaching model includes guest lecturer programs connecting students with supply chain practitioners, as evidenced by his co-authored work on integrating industry insights into supply chain education. While specific grant funding details are not publicly documented, his leadership in the CSCMP Supply Chain Hall of Fame demonstrates commitment to professional development and industry-academia knowledge transfer. Dr. Van Hoek directs the CSCMP Supply Chain Hall of Fame initiative, which documents transformative contributions to supply chain management through interviews with industry pioneers and historical case studies. This platform serves as both an educational resource for Walton College students and a professional development tool for supply chain practitioners globally. The Hall of Fame preserves critical industry knowledge while highlighting contemporary innovations in supply chain strategy and technology implementation.
Christina L. Garman is an Assistant Professor in the Department of Computer Science at Purdue University, where she joined in Spring 2018. Her research focuses on practical cryptography and cryptographic automation to make secure system development accessible to non-experts through error-resistant design methodologies. Her educational background includes: Bachelor of Science in Computer Science and Engineering from Bucknell University (2011) Bachelor of Arts in Mathematics from Bucknell University (2011) Master of Science in Engineering in Computer Science from Johns Hopkins University (2013) Doctor of Philosophy in Computer Science from Johns Hopkins University (2017) Professor Garman's work centers on real-world cryptographic system security, spanning protocol analysis (e.g., RC4 in TLS, Apple iMessage flaws), decentralized anonymous systems (Zerocash/ZCash), and cryptographic automation. She pioneered techniques for removing human error in cryptographic deployments through automated tools and frameworks. Her research bridges theoretical cryptography with practical implementation challenges in privacy-preserving technologies and secure infrastructure. Analysis of her 2021-2025 publications reveals expanding research horizons: hardware security vulnerabilities (Rowhammer, SGX), privacy network enhancements (Tor onion services), software supply chain security (SBOM tools), and advanced cryptographic protocols (zkSNARKs, MPC). This evolution demonstrates consistent focus on real-world security impact while diversifying into hardware-software cross-layer threats and formal verification methods for cryptographic implementations. Her major scientific recognitions include: NSF CAREER Award (2021) for cryptographic automation research ACM CCS Best Paper Award (2016) for iMessage security analysis IEEE Test of Time Award (2024) for foundational Zerocash work Professor Garman co-founded ZCash, a privacy-focused cryptocurrency based on her Zerocash protocol, and her NSF CAREER grant supports cryptographic automation development. Her research has received significant media coverage in The Washington Post, Wired, and The New York Times, highlighting real-world relevance. While specific student advising details aren't public, her active publication record indicates ongoing mentorship of graduate researchers in security and cryptography. Her work maintains strong industry connections through ZCash development and Tor network contributions, with recent projects like keyless CDNs demonstrating practical applications of cryptographic automation. She remains a leading voice in cryptographic research communities through conference participation and collaborative projects addressing evolving security challenges.
Justine Sherry is the A. Nico Habermann Associate Professor of Computer Science at Carnegie Mellon University, affiliated with the College of Engineering. She holds a PhD (2016) and MS (2012) from UC Berkeley and a BS/BA (2010) from the University of Washington. Her research focuses on networked systems, including middleboxes, cloud computing, congestion control, and hardware acceleration (e.g., SmartNICs/FPGAs). Notable projects include Pigasus (open-source 100Gbps IDS), APLOMB (cloud-based middlebox scaling), and BlindBox (encrypted traffic scanning). Her academic roles include serving on the SIGCOMM CARES Committee, DARPA ISAT Study Group, and ACM CoNEXT Steering Committee. Awards include the Alfred P. Sloan Fellowship, VMware Systems Award, and IETF Applied Networking Prize. She advises over 15 students and collaborates with industry partners like Intel and VMware. Research highlights include radical shifts in datacenter architectures (SmartNIC compute control), fairness in congestion algorithms (BBR analysis), and database-proxy innovations (Tigger with eBPF). Her teaching emphasizes systems as science labs, integrating experimental design and hypothesis testing into projects. Education: PhD UC Berkeley (2016), MS UC Berkeley (2012), BS/BA University of Washington (2010) Labs/Teams: CyLab, SNAP Research Group, CMU Portugal Collaboration Grants: NSF, Intel, Google Faculty Awards
Andrew Rice is a Professor of Computer Science at the University of Cambridge's Department of Computer Science and Technology, and holds the Hassabis Fellowship in Computer Science. He is also the Director of Studies in Computer Science at Queens' College. His research focuses on programming languages, software engineering, and machine learning applications in software development. He leads projects like Isaac Computer Science and ALTA (Automated Language Teaching and Assessment), advancing adaptive learning technologies. His work includes static analysis tools such as Error Prone at Google, energy efficiency studies in computing infrastructure, and contributions to the Computing for the Future of the Planet initiative. His teaching emphasizes practical skill development through flipped classrooms and video lectures, earning him the 2014 Pilkington Prize for teaching excellence. He has held visiting roles at Google and collaborated on energy consumption research for mobile devices and data centers. His research spans systems, networking, and natural language processing, with a strong focus on applying computational methods to real-world challenges. Key Projects: Isaac Physics/Computer Science, ALTA, Error Prone Static Analysis Research Themes: Programming Languages, Machine Learning, Energy Efficiency Awards: Pilkington Prize (2014)
Anil Madhavapeddy serves as Professor of Planetary Computing at the University of Cambridge's Department of Computer Science and Technology and directs the Cambridge Centre for Carbon Credits (4C). A Fellow of Pembroke College, he integrates systems research with environmental conservation through the Computer Laboratory's Environment and Energy Group. His career spans industry leadership (NetApp, Citrix, Intel), academic appointments (Cambridge, Imperial, UCLA), and entrepreneurial ventures (XenSource, Unikernel Systems, Docker). Madhavapeddy earned his PhD at Cambridge's Computer Laboratory in 2006. His research bridges computational systems and planetary-scale environmental challenges, with deep expertise in open-source development (OCaml, Xen, Docker, OpenBSD) and technology strategy advising for organizations including Zededa, Tezos Foundation, and Tarides. His work centers on environmental computing and climate informatics, leveraging distributed systems and functional programming to develop sensing infrastructure for conservation. Recent projects focus on carbon credit systems, AI-driven biodiversity monitoring, and sustainable computing architectures that minimize ecological footprints while maximizing analytical capability. Analysis of his 2025 publications reveals a concentrated effort on AI-integrated conservation tools, privacy-preserving carbon accounting, and energy-efficient computing. Key themes include spatial networking for ecological data, LLM-enhanced evidence retrieval in conservation science, and novel metrics for extinction risk assessment—demonstrating computational innovation applied to urgent planetary boundaries. No scientific awards were documented in the source material. Madhavapeddy advises multiple technology firms on strategic development while leading the Cambridge Centre for Carbon Credits, though specific grant funding details remain unreported. He actively contributes to the Environment and Energy Group at Cambridge's Computer Laboratory and directs the interdisciplinary Cambridge Centre for Carbon Credits (4C). His open-source leadership spans critical infrastructure projects including OCaml, Xen, and Docker, fostering collaborative development communities that underpin modern cloud and container technologies.
Alex Lombardi is an Assistant Professor of Computer Science at Princeton University, specializing in cryptography and theoretical computer science. His work explores cryptographic proof systems, post-quantum security, and quantum cryptography. Princeton University (Current) Simons-Berkeley Postdoctoral Fellow (Former) MIT (Graduate Training) Visiting Scientist, Cryptography 10 Years Later Program (2025) Education: PhD in Computer Science from MIT (advised by Vinod Vaikuntanathan) Master's Thesis on Provable Instantiations of Correlation Intractability and the Fiat-Shamir Heuristic Dr. Lombardi's research spans foundational cryptography, with a focus on indistinguishability obfuscation, worst-case assumptions, and quantum cryptographic protocols. His work on SNARGs and PPAD hardness has advanced cryptographic proof systems, while his recent projects address quantum verification and post-quantum security. He encourages prospective cryptography students to apply to Princeton's PhD program. His publications highlight advancements in LWE-based cryptography, quantum protocols, and complexity-theoretic foundations. Key themes include secure computation, hash function design, and cryptographic reductions under quantum assumptions. Scientific Awards: Simons-Berkeley Postdoctoral Fellowship Dr. Lombardi serves on program committees for STOC 2025, EUROCRYPT 2025, and other conferences. He has taught courses like COS 433/533 (Cryptography) and COS 533 (Advanced Cryptography) at Princeton.
