Ravi Sethi serves as a Laureate Professor in the Department of Computer Science within the College of Engineering at the University of Arizona. His office is located in GS 842, and he can be contacted via email at rsethi@cs.arizona.edu or by phone at 520-621-0689. His primary research interests include: Software technologies Communications systems Compilers Programming languages Algorithms Professor Sethi is renowned for his foundational contributions to compiler design, particularly as co-author of the seminal textbook "Compilers: Principles, Techniques and Tools". His publication record spans over four decades with works translated into multiple languages, reflecting global influence in computer science education. Analysis of his recent articles reveals persistent focus on compiler construction, programming language semantics, and software engineering methodologies. Key trends include modern compiler optimizations, formal language theory, and enterprise communication systems, demonstrating sustained relevance in evolving technical landscapes. No scientific awards, student advising details, grant information, or laboratory affiliations were mentioned in the provided text.
David Zwicker serves as a Max Planck Research Group Leader at the Max Planck Institute for Dynamics and Self-Organization in Göttingen, Germany, where he heads the Theory of Biological Fluids group. His research investigates how soft and fluid-like biological materials achieve precise spatial and temporal organization through physical principles. Dr. Zwicker's work centers on biomolecular condensates, pattern formation, and smart materials design. His group employs statistical physics, dynamical systems theory, and fluid dynamics to model biological processes including phase separation in cells, active matter systems, and nasal airflow mechanics. Current projects explore how phase transitions might enable cellular information processing and how chemical activity drives droplet self-propulsion. Recent publications (2024-2025) reveal strong focus on phase separation dynamics in biological contexts, with emerging themes in active condensates, multicomponent mixtures, and computational modeling tools. His group develops open-source software like flory for phase diagram analysis and py-pde for partial differential equations. Scientific recognition includes: ERC Starting Grant for biomolecular condensates research Dr. Zwicker leads an active research team currently comprising postdoctoral researchers Guido Kusters and Filipe Thewes (joined October 2024), with ongoing recruitment for ERC-funded projects. His group maintains strong computational focus while collaborating across physics and biology disciplines. The Theory of Biological Fluids group operates within the Max Planck Institute's Department of Fluid Dynamics, utilizing advanced modeling to bridge theoretical physics and cellular biology.
Ruslan Nikolaev is an Assistant Professor in the Department of Computer Science and Engineering, specializing in nonblocking algorithms, memory reclamation, and concurrent data structures. His research spans operating systems, virtualization, and lock-free programming paradigms. Academic Rank: Assistant Professor Department: Computer Science and Engineering Research Interests focus on: Nonblocking and wait-free algorithms Memory-efficient reclamation techniques Lock-free data structures Operating system virtualization Device driver security Recent work includes 2025 advancements in SCOT and RRR-SMR frameworks for nonblocking structures, 2024 contributions to wait-free reclamation, and 2022 innovations in address space randomization (Adelie), critical service domains (Kite), and wait-free queues (Wcq). Earlier projects (2013-2020) explored OS virtualization (VirtuOS) and reclamation mechanisms (LibrettOS). Trends in his publications highlight: Optimization of concurrent algorithms Security enhancements in Linux drivers Virtualization techniques for critical services Efficient memory management strategies Robust fault tolerance in distributed systems
Vijay Narayanan is the Robert Noll Chair Professor in Computer Science & Engineering and Electrical Engineering at Pennsylvania State University. He co-directs the Microsystems Design Lab and leads research in embedded visual analytics, self-powered processors, and system design using emerging devices. Education: B.E in Computer Science and Engineering (1993) from University of Madras, India Ph.D. in Computer Science and Engineering (1998) from University of South Florida, USA His research spans Power Aware Computing , Computer Architecture , and Embedded Systems , with emphasis on Visual Cortex on Silicon and Self-Powered Processors . Current work includes Non-Volatile Processors and Design Automation under unreliable power conditions via NSF ERC ASSIST. Recent publications focus on GPU architecture (Tensor Cores, ACE), Memory Consistency Verification (QED), and Neural Radiance Fields (Disorf, Distwar) for robotics and rendering. Key collaborations include Tsinghua University and DARPA/SRC LEAST Center . Scientific Awards: IEEE Fellow ACM Fellow He leads the Architecture, Benchmarking and Circuits Thrust in the DARPA/SRC LEAST Center and contributes to NSF ERC ASSIST for self-powered systems. Grants and projects emphasize cross-layer optimizations and hardware-software co-design.
Seiichiro Tani is a Professor at Waseda University's Faculty of Education and Integrated Arts and Sciences since April 2024. He previously held prominent roles at NTT Communication Science Laboratories (2003-2024), including Leader of the Computing Theory Research Group and Project Manager of the Research Center for Theoretical Quantum Information. He has also served as a Visiting Professor at Tokyo Institute of Technology (2022-2024) and a researcher at JST's ERATO projects (2004-2009). His academic journey includes a Ph.D. in Computer Science from the University of Tokyo (2006), preceded by M.E. and B.E. degrees from the University of Tokyo and Kyoto University, respectively.
Daniel Höller is a researcher in the Foundations of Artificial Intelligence (FAI) Group at the Department of Computer Science, Saarland University, Germany. He joined the group in January 2020, having previously worked at the Institute of Artificial Intelligence at Ulm University from November 2013 to December 2019. He holds an M.Sc. in Computer Science from Bonn-Rhein-Sieg University, where he studied from 2007 to 2013. Ph.D., Computer Science, Ulm University M.Sc., Computer Science, Bonn-Rhein-Sieg University (2013) Daniel Höller's research lies at the intersection of theoretical and practical aspects of AI planning. His primary focus is on Hierarchical Task Network (HTN) planning, where he has made significant contributions to expressivity analysis, solver development, and the use of classical planning heuristics to guide HTN search. He also works on lifted planning, plan repair, plan recognition, and the integration of planning with deep reinforcement learning. His work often involves formal analysis, heuristic development, and the creation of practical planning systems. He is particularly interested in how planning can be made more efficient, reliable, and applicable to real-world problems, including human-aware applications. His recent publications demonstrate a consistent trend in advancing HTN planning through novel formalisms (e.g., HDDL), sophisticated solving techniques (e.g., progression search, SAT-based approaches), and the development of robust software frameworks (e.g., PANDA, TOAD, LiSAT). His work increasingly bridges planning with learning, exploring how learned models can inform planning and how planning can provide structure for learning. The subfields span formal methods, search algorithms, knowledge representation, and system building. ICAPS 2024 Best Dissertation Award for his thesis on hierarchical planning SoCS 2024 Best Student Paper Award (co-authored) Winner in 4 out of 6 tracks in the 2023 IPC HTN competition ICAPS 2018 Best Student Paper Award ICTAI 2018 Best Paper Award TCTS 2018 Best Paper Award Shortlisted for Best Paper at KI 2020 Daniel Höller has been actively involved in teaching and mentoring, having taught courses on Artificial Intelligence and AI Planning at Saarland University, and previously served as a teaching assistant for a wide range of AI and computer science courses at Ulm and Bonn-Rhein-Sieg Universities. He has received funding through his involvement in the Transregional Collaborative Research Center SFB/Transregio 62 at Ulm University. He has organized and contributed to numerous workshops and conferences, demonstrating strong service to the academic community. Daniel Höller is a core developer of the PANDA planning framework, the TOAD HTN solver, and the LiSAT system for lifted planning. These systems are state-of-the-art tools that implement his research on heuristic search, model transformation, and SAT-based compilation. His work is conducted within the FAI group at Saarland University, a leading research group in automated planning.
Sidharth Kumar is an Associate Professor in the Department of Computer Science at the University of Illinois at Chicago (UIC), where he leads research in high-performance computing and data visualization. He joined UIC in August 2023 after previously working at the University of Alabama at Birmingham. His research focuses on developing scalable algorithms and data structures for data-intensive applications, intersecting HPC, visualization, databases, and machine learning. Education: Ph.D. in Computing (2016) from the University of Utah's Scientific Computing and Imaging Institute, advised by Valerio Pascucci. Bachelor of Technology in Information and Communication Technology (2009) from DAIICT, Gandhinagar, India. Research Interests: Dr. Kumar's work centers on parallel I/O, GPU acceleration, big data processing, and scientific visualization. His projects include: 1) Exascale data management systems, 2) GPU-accelerated web visualization, 3) Declarative analytics frameworks, and 4) Topology-driven analysis for neuroscience and virology. He develops solutions for memory-constrained environments and heterogeneous systems. Publication Trends: Recent works (2023-2025) demonstrate strong focus on GPU-accelerated databases (Datalog optimizations), parallel communication algorithms (all-to-all collectives), memory-efficient visualization techniques (speculative raycasting), and applied topological analysis (brain networks, virus taxonomy). His publications consistently appear in top-tier HPC and visualization venues. Awards & Honors: Best Paper Awards: IEEE HiPC (2019), ISC Hans Meuer (2020), LDAV (2023) Honorable Mention: PacificVis (2025) Poster Awards: SC23 Finalist, HiPC SRS (2021) NSF EPSCoR Research Fellow (2022) Grants & Advising: NSF PPoSS Large: Declarative Analytics ($960K PI) NSF SHF: Scalable I/O Runtime ($300K PI) NSF EPSCoR: Relational Algebra ($265K PI) Advises 6 PhD students in HPC and visualization research Lab & Service: Leads a research team working on exascale computing challenges. Serves on technical committees for SC, ISC, IPDPS, and HiPC conferences. Teaches courses in Database Systems, Algorithms, and Data Visualization.
Dr. Alexander R. Block is an Assistant Professor at the University of Illinois at Chicago (UIC) , specializing in Cryptography and Coding Theory . He focuses on the concrete security and space-efficiency of SNARKs, error-correcting codes , and locally decodable codes . Before UIC, he was a postdoctoral researcher at Georgetown University and University of Maryland , advised by Justin Thaler and Jonathan Katz. His PhD from Purdue University (2022) was supervised by Jeremiah Blocki. His research bridges theoretical and applied aspects, including field-agnostic SNARKs (CRYPTO 2024) with expand-accumulate codes, Fiat-Shamir security analysis of FRI protocols (ASIACRYPT 2023), and memory-hard puzzles in the standard model (SCN 2022). He has contributed to insertion-deletion error codes (CCC 2023) and secure computation with leaky correlations (TCC 2018, CRYPTO 2017). Dr. Block has received multiple scientific awards , including the Emil Stefanov Fellowship (2021) and Purdue Three Minute Thesis Competition Finalist (2022). His teaching includes courses like UIC's CS 505 - Computability and Complexity Theory (Spring 2025), where he emphasizes interactive proofs and zero-knowledge systems . He actively serves on program committees for CRYPTO , EUROCRYPT , and ZKProof Workshop , and has reviewed for leading journals and conferences.
Philipp Schuster is a researcher at the University of Tübingen, Germany, specializing in programming languages, compiler design, and functional programming. His work focuses on effect handlers, type systems, and efficient code compilation, with a strong emphasis on lexical scope and formal verification. His research contributions include innovations in capability-passing style for effect handlers, direct-style compilation, and monomorphization techniques. He has actively participated in program committees and artifact evaluations for major conferences like ICFP, SPLASH, and APLAS. Key trends in his publications revolve around effect handling, lambda calculus, type safety, and compiler optimization. His work bridges theoretical foundations with practical implementations, aiming to improve modularity and runtime efficiency in functional programming languages. He has served on program committees and artifact evaluation panels for conferences such as ICFP, SPLASH, APLAS, and HOPE, demonstrating leadership and collaboration in advancing programming language research.
Wayne Kelly is an Associate Professor in the School of Computer Science at Queensland University of Technology (QUT), Faculty of Science. He has over 25 years of academic experience and serves as the Academic Lead for Teaching and Learning and Course Coordinator for the Bachelor of Information Technology degree. PhD in Computer Science, University of Maryland, College Park, 1996 BSc (Hons) in Computer Science, University of Queensland, 1989 His research expertise lies in Programming Languages, Compiler Construction, and Parallel Computing, with significant contributions to High Performance Computing, Big Data, and Bioinformatics. His work has led to collaborations with Microsoft Research and over $2 million in external funding. His recent publications reflect a strong trend in parallel and distributed systems, embedded computing, bioinformatics data analysis, and remote sensing. Key themes include optimization of computational systems, memory management, and scalable data processing. Wayne Kelly has made impactful contributions to both teaching and research, guiding numerous postgraduate students and leading curriculum development in information technology. Optimizing I/O cost and managing memory for bioinformatics A communication model for streaming applications on MPSoC Ruby.NET: a compiler for the Common Language Infrastructure He is actively engaged in real-world technology development, including a project with a vision-impaired student to improve public transportation accessibility, currently trialed by transport authorities in Australia and the US.
Anders Møller is a Professor at the Department of Computer Science , Aarhus University , Denmark. His career spans roles as an author , committee member , and session chair in conferences like SPLASH, OOPSLA, ECOOP, ISSTA, ICSE, and PLDI. Affiliation: Aarhus University Co-founder: Coana Research Focus : Specializing in static and dynamic program analysis for JavaScript, TypeScript, Java, and Node.js applications, his work addresses: Pointer analysis precision in Java Race condition detection in Node.js Library evolution and semantic patching Soundness improvements in static analyzers Type safety in modern languages Concolic execution for web testing Publication Trends : Recent work (2021–2024) emphasizes security-critical static analysis (taint specifications, Node.js security), soundness optimization (approximate interpretation), and program verification (channel-based communication). Earlier work (2013–2018) includes foundational contributions to JavaScript refactoring , Dart type safety , and AJAX race detection . Scientific Recognition : ISSTA 2019 Distinguished Paper Award Leadership Roles : Active in steering committees for SPLASH, ECOOP, and SIGPLAN, with chairs in OOPSLA, ECOOP, and PLDI program committees.
Michelle Strout is a Professor in the Department of Computer Science at the University of Arizona, where she has been faculty since August 2015. Her research focuses on high-performance computing with particular expertise in compiler technologies and parallel systems. Her research interests span multiple domains within computer systems: High Performance Computing for scientific applications Compiler design and optimization techniques Run-time systems for parallel execution Scientific computing methodologies Software engineering for performance-critical systems Dr. Strout has made significant contributions to the field including the Universal Occupancy Vector (UOV) for storage mappings in stencil computations and the Sparse Polyhedral Framework (SPF) for inspector-executor loop transformations. Her work addresses fundamental challenges in parallelization of irregular applications like molecular dynamics simulations. Her scientific recognition includes: NSF CAREER Award (2008) DOE Early Career Award (2010) Dr. Strout is actively involved in the programming languages and high-performance computing communities, serving on program committees for major conferences including PLDI, SPLASH, and PPoPP. She has demonstrated commitment to mentoring through her involvement with PLMW (Programming Languages Mentoring Workshop), where she has served as organizer, session chair, and presenter.
Jakob Bleier is a PreDoc Researcher at the Institute of Security and Privacy, part of the Faculty of Informatics at Technische Universität Wien. His work focuses on mobile and IoT security, with an emphasis on Android and iOS application analysis, malware lifecycle assessment, and reverse engineering techniques. He contributes to projects such as IoTIO (2020–2025) and W4MP (2023–2027), addressing challenges in software attribution and cross-platform security. Research Interests: Mobile application security (Android/iOS) Static and dynamic malware analysis Binary code analysis and disassembly IoT security and exploit lifespan quantification Software attribution and provenance tracking His publications highlight advancements in cross-platform app comparison, Android disassembly evaluation, and IoT malware lifecycle studies. He has supervised diploma theses on topics like framework identification in Android apps and PII leakage analysis in IoT companion apps. Current Projects: IoTIO: Investigating IoT security and privacy challenges W4MP: Exploring mobile security methodologies SPFBT: Security in pervasive and future networks
Vikram Sadanand Adve is the Donald B. Gillies Professor at the University of Illinois Urbana-Champaign, holding appointments in the Siebel School of Computing and Data Science, Information Trust Institute, Coordinated Science Lab, and National Center for Supercomputing Applications (NCSA). His research focuses on compiler design, parallel programming, and AI-driven solutions for critical domains like agriculture and environmental sustainability. He earned recognition through prestigious awards including the ACM Fellow (2014), ACM Software System Award (2012), Amazon Research Award (2020), and Machine Learning Research Award (2019). His work bridges theory and practice, with contributions to compilers, hardware-software co-design, and AI applications in agriculture. Adve leads interdisciplinary initiatives such as AIFARMS, applying AI to enhance agricultural resilience. He collaborates globally, with recent research emphasizing tensor program optimization, code generation for infrastructure automation, and retargetable compilers for modern hardware architectures. Key Affiliations: Siebel School of Computing and Data Science Information Trust Institute Coordinated Science Lab National Center for Supercomputing Applications (NCSA) Research Themes: Compiler Optimization Parallel Computing AI for Agriculture Hardware-Software Co-Design Recent Grants & Projects: Amazon Research Award supporting machine learning innovations NSF-funded AIFARMS initiative
Giorgio Alberti is a Full Professor at the University of Udine , Department of Agri-Food, Environmental and Animal Sciences. His research focuses on forest ecology, carbon sequestration, remote sensing applications, climate change impacts on tree species, and ecosystem services. He leads projects like CarboMark and contributes to Horizon Europe initiatives. Key Research Areas Forest carbon dynamics and biodiversity conservation Integration of field measurements with remote sensing Climate change adaptation in agricultural and forest systems Ecosystem service trade-offs in protected areas His recent work involves machine learning for forest carbon estimation, ecohydrological studies in vineyards, and global biodiversity assessments. He actively participates in international collaborations, including the LATEST Erasmus+ project and Dinaric Alps old-growth forest research. Project Involvement PRI. FOR. MAN Dashboard for wood resource mapping Horizon Europe Project 101081177 on carbon-biodiversity datasets Post-windstorm forest regeneration studies in the Alps Governance of Natura 2000 protected areas
