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Lars KarlssonView profile

Associate Professor

• High-Performance Computing
• Numerical Linear Algebra
• Parallel Algorithms
• +2 more

Lars Karlsson is an Associate Professor at the Department of Computing Science, Umeå University, where he serves as Assistant Head of Department with responsibilities for undergraduate education. His research focuses on developing efficient algorithms for matrix and tensor computations within high-performance computing environments. He is affiliated with the Parallel and Scientific Computing research group at Umeå. Karlsson's primary research areas include: Numerical Linear Algebra : Specializing in matrix factorizations and eigenvalue computations Parallel Algorithms : Designing scalable solutions for distributed and shared-memory systems Tensor Computations : Developing decomposition methods and completion algorithms Performance Optimization : Auto-tuning techniques for modern computing architectures His publications (2010-2025) demonstrate consistent focus on parallel algorithms for numerical problems, particularly matrix reductions, eigenvalue computations, and tensor decompositions. Recent work emphasizes auto-tuning, robustness in numerical methods, and efficient scheduling for high-performance systems. The majority of publications involve collaborative research within European computing consortia like NLAFET. Karlsson contributes to educational research, having explored mastery learning approaches in university settings. His administrative responsibilities include oversight of undergraduate programs at the Department of Computing Science.

Lixin TaoView profile

Professor

• Cloud Computing
• Internet/Web Computing
• Intelligent Systems
• +4 more

Dr. Lixin Tao is a tenured Professor and Chairperson of the Computer Science Department at Pace University's Seidenberg School of CSIS. He earned his PhD in Computer Science from the University of Pennsylvania in 1988 and has conducted research and teaching at Concordia University (1988-2001) before joining Pace University. Research Interests: Dr. Tao's work spans Internet Computing , Server Scalability , Component Technologies , Parallel Computing , Functional Simulation , and Combinatorial Optimization , with recent focus on Knowledge Graphs , Semantic Web , and Secure Mobile Cloud Systems . He has pioneered cloud computing research since the 1990s and developed industry standards like OWL extensions. Over 300 peer-reviewed publications Director of Pace University's PhD Computer Science Program (2013-2017) Developed MS in Enterprise Analytics (2015) and BS in Computer Engineering (2017) Scientific Awards: Recognized as IEEE Senior Member (2020), ABET Evaluator (2001-2012), and recipient of multiple research grants including a $12M NSERC Strategic Technology Program and NSF awards for server infrastructure. He received Pace University's Presidential Research Grant and collaborated with institutions like Stanford University on knowledge engineering projects. Professional Contributions: Directed ABET accreditation for Pace's BS-CS program (2010-2012), served as Editor-in-Chief for the Journal of Computer Science Research (2018-present), and supervised dozens of PhD/DPS students in areas ranging from Mobile Payment Protocols to Drug Side Effect Knowledge Graphs . His lab focuses on Knowledge-Empowered AI and Secure Software Development .

Sidharth KumarView profile

Associate Professor

• High-performance computing
• Data visualization
• Scalable algorithms
• +7 more

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.

Alexander R. BlockView profile

Assistant Professor

• Cryptography
• Coding Theory
• SNARKs
• +7 more

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.

Georg HagerView profile

Researcher

• High Performance Computing
• Performance Engineering
• Computational Physics
• +7 more

Dr. Georg Hager is Head of Research at the Erlangen National High Performance Computing Center (NHR@FAU), Friedrich-Alexander-Universität Erlangen-Nürnberg, and an associate lecturer at the Institute of Physics, University of Greifswald. His work focuses on performance engineering, node-level optimization, and analytic modeling in high performance computing. Research Interests: High Performance Computing (HPC) Performance Engineering and Modeling Architecture-Specific Optimization Energy Efficiency in Computing Scientific Code Optimization Execution-Cache-Memory (ECM) Model Development Computer Architecture for HPC His recent publications and tutorials emphasize performance modeling, node-level engineering, hybrid programming (MPI+OpenMP), and benchmarking on modern architectures such as Ice Lake, Sapphire Rapids, and A64FX. He has contributed to the development of the LIKWID tool suite and promotes best practices in HPC education. Scientific Awards: ISC Gauss Award (2018) Informatics Europe Curriculum Best Practices Award (2011) Georg Hager has been instrumental in developing and teaching international tutorials on performance engineering and hybrid programming, often in collaboration with HLRS Stuttgart and TU Wien. He is the co-author of the widely used textbook Introduction to High Performance Computing for Scientists and Engineers . His work bridges theoretical modeling and practical application, aiming to improve time-to-solution and resource efficiency in large-scale scientific computing.

• string algorithms
• data structures
• graph algorithms
• +5 more

Shay Golan is a Senior Lecturer in the Computer Science department at Ariel University, where he teaches core algorithms and data structures courses. Previously, he held postdoctoral positions at Reichman University, Haifa University (hosted by Shay Mozes and Oren Weimann), and was a Fulbright Postdoctoral Fellow at UC Berkeley's EECS department (hosted by Jelani Nelson). He earned his Ph.D. in Computer Science from Bar-Ilan University under the supervision of Ely Porat and Tsvi Kopelowitz. Dr. Golan's primary research focuses on string algorithms with emphasis on streaming, small space, and dynamic settings. His work spans multiple subfields including data structures, graph algorithms, and discrete algorithms. He has made significant contributions to pattern matching, edit distance problems, and string compression techniques, with applications extending to bioinformatics for DNA sequence analysis. His recent publication trajectory (2022-2026) reveals a strong focus on string algorithmic challenges across multiple dimensions: theoretical complexity analysis (LZ77 compression, string covers), specialized string problems (2D string matching, hairpin structures), graph algorithm applications (planar graph distance oracles), and bioinformatics implementations (DNA minimizers). His work consistently appears in top theoretical computer science venues including STOC, SODA, and CPM, demonstrating both theoretical depth and practical relevance. Fulbright Postdoctoral Fellow at UC Berkeley As an educator, Dr. Golan has consistently taught foundational computer science courses including Algorithms 1, Algorithms 2, Data Structures, and Computability since 2016. His research is supported through collaborations with leading institutions including Reichman University, Haifa University, and UC Berkeley. He maintains active research partnerships with prominent computer scientists including Itai Boneh, Ely Porat, and Tsvi Kopelowitz. Dr. Golan participates in the broader theoretical computer science community through conference presentations and workshop participation, with recorded talks available for several of his publications. His work bridges theoretical computer science with practical applications, particularly in computational biology and genomic sequence analysis.

Michelle StroutView profile

Professor

• High Performance Computing
• Compilers
• Run-time Systems
• +4 more

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.

Ludovic ApvrilleView profile

Professor

• Embedded Systems Design
• Cyber-Physical Systems
• System-on-Chip (SoC) Modeling
• +7 more

Ludovic Apvrille is a Professor at Telecom Paris (Institut Polytechnique de Paris), where he leads research in the Communications and Electronics (Comelec) department and previously headed the LabSoC (Laboratory on System on Chip). His work focuses on embedded systems design , with particular emphasis on safety, security, and formal verification of complex systems including automotive applications, drones, and cyber-physical systems. Research Areas: Embedded Systems, Cybersecurity, Model-Driven Engineering, Formal Verification, AI-assisted Design Key Tools: TTool, SysML-Sec, AVATAR, SMASHUP, DIPLODOCUS His recent publications analyze security vulnerabilities in RISC-V architectures using the gem5 simulator, while his ongoing work explores AI integration in system modeling and unified verification techniques for hardware/software co-designs. He actively supervises research projects in safety-security-performance trade-offs and microarchitectural security , with applications to autonomous vehicles and critical infrastructure systems. Grants & Projects: EVITA project, PEPR-5G HISEC, MoVe4SPS, PEPR-Security ARSENE

Jonah LiptonView profile

Research Fellow

• Anthropology
• African Studies
• Sierra Leone Studies
• +8 more

Dr. Jonah Lipton is a Research Fellow at the Firoz Lalji Centre for Africa and the ESRC Centre for Public Authority and International Development at the London School of Economics and Political Science. Specializing in the anthropology of Sierra Leone and West Africa, his work examines youth experiences, family dynamics, crisis response, informal economies, global health systems, and humanitarian interventions through ethnographic fieldwork in Freetown's urban neighborhoods. His research program centers on long-term ethnographic engagement, beginning with PhD fieldwork conducted immediately before and during the 2014-2015 Ebola outbreak, which explored how young men navigated the crisis within intimate social and economic contexts of home and community. Subsequent research expanded to investigate 'family politics,' analyzing family meetings and domestic power structures in Sierra Leonean households. Lipton's methodological approach combines classic anthropological techniques with contemporary analysis of digital communication and urban political economy. Lipton's scholarly output reveals consistent thematic development across publications, with a clear trajectory from immediate Ebola crisis documentation to deeper theoretical contributions about social order during emergencies. His work demonstrates how global health interventions intersect with local cultural practices, particularly examining burial rituals as sites of cultural negotiation during the Ebola epidemic. The 2017 Journal of the Royal Anthropological Institute article 'Black' and 'White' Death established his reputation for analyzing how crises reveal underlying social tensions through the lens of everyday practices. As an active public intellectual, Lipton contributes to media discourse on pandemic responses, having drawn parallels between Ebola and coronavirus experiences. His forthcoming book 'In the Time of Ebola' (Cornell Press, November 2024) represents a significant scholarly contribution to the field. He convenes the LSE Critical African Writings reading group and maintains engagement with both academic and public audiences through diverse publication venues from scholarly journals to major media outlets.

Muhammad ShahbazView profile

Assistant Professor

• Networking and Operating Systems
• Artificial Intelligence
• Machine Learning
• +5 more

Dr. Muhammad Shahbaz is the Kevin C. and Suzanne L. Kahn New Frontiers Assistant Professor in Computer Science at Purdue University. He specializes in designing domain-specific abstractions, compilers, and architectures for emerging workloads such as machine learning and self-driving networks. His research bridges networking, machine learning, and computer architecture to create high-performance, scalable systems. Shahbaz holds a Ph.D. and M.A. in Computer Science from Princeton University and a B.E. in Computer Engineering from the National University of Sciences and Technology (NUST). Before joining Purdue, he conducted postdoctoral research at Stanford University and worked as a Research Assistant at Georgia Tech and the University of Cambridge. His research interests include Networking and Operating Systems, Artificial Intelligence, Machine Learning, Computer Architecture, Distributed Systems, and Programming Languages/Compilers. He has developed influential open-source systems like Pisces, SDX, and NetFPGA-10G, which are widely adopted in industry and academia. Shahbaz has received prestigious awards including the Facebook, Google, and Intel Research Awards; IETF/IRTF ANRP Prize; ACM SOSR Systems Award; and APNet Best Paper Award. His work focuses on advancing edge computing, smartNICs, in-network machine learning, and scalable distributed systems. His research portfolio includes contributions to network caching, hardware acceleration, and AI-driven network optimization. He leads projects like CAREER (per-packet AI on heterogeneous data planes) and EdgeScaler (smart auto-scaling for 5G edge networks). His systems address challenges in tail latency, resource harvesting, and scalable multicast in modern networks.

• Decision Neuroscience
• Neuroeconomics
• Cognitive Neuroscience
• +3 more

Scott Huettel is a Professor in the Department of Psychology and Neuroscience at Duke University, holding concurrent roles as Senior Associate Dean for Research in Trinity College of Arts & Sciences and Bass Fellow. He also serves as Professor of Neurobiology and Psychiatry and Behavioral Sciences, and holds affiliations with multiple interdisciplinary centers including the Center for Cognitive Neuroscience and Duke Institute for Brain Sciences. His research focuses on decision neuroscience, investigating brain mechanisms underlying economic and social decisions using fMRI, behavioral assays, and computational methods. He has authored influential textbooks like Functional Magnetic Resonance Imaging and pioneered applications of fMRI analysis techniques such as functional connectivity and pattern classification. Education: Ph.D. in Psychology from Duke University (1999). Research Interests : Decision neuroscience, neuroeconomics, social decision making, and the neural basis of individual differences in behavior. His work bridges cognitive neuroscience with computational models to explore how brain systems mediate complex choices, particularly in contexts involving risk, ambiguity, and social dynamics. Grants & Leadership : Leads major grants including the NIH-funded Neurobiology Training Program and Duke’s Psychiatry Physician-Scientist Residency Program. Past roles include Chair of Psychology and Neuroscience and Interim Co-Director of the Duke Institute for Brain Sciences. Active in educational innovation through Bass Connections and courses like Decision Neuroscience. Labs & Teams : Core faculty in the Center for Brain Imaging and Analysis, contributing to advanced neuroimaging methodologies. Collaborates across disciplines to address translational challenges in health behavior, consumer decision-making, and aging.

• Programming Languages
• Formal Methods
• Software Engineering
• +4 more

Elsa Gunter is a Research Professor and Senior Lecturer at the Siebel School of Computing and Data Science, part of the Grainger College of Engineering at the University of Illinois Urbana-Champaign. She holds a Ph.D. in Mathematics from the University of Wisconsin (1987). Her research focuses on programming languages, formal methods, software engineering, and interdisciplinary computing education. Key research areas include the semantics of programming languages, compiler optimization, formal verification frameworks, and integrating computing into interdisciplinary education. She teaches courses like CS 421 (Programming Languages & Compilers), CS 431 (Embedded Systems), and CS 477 (Formal Software Development Methods). Her work emphasizes practical applications of formal methods in software development and pedagogical innovations in computing education. Recent projects explore challenges in interdisciplinary computing curricula and the formal semantics of programming languages. Elsa’s academic contributions span over four decades, with notable work on theorem proving tools (e.g., HOL90), compiler correctness frameworks, and educational technologies for programming courses.

Michael MarshView profile

Senior Lecturer

• Cybersecurity
• Networking
• Distributed Systems
• +3 more

Michael Marsh is a Senior Lecturer in the Department of Computer Science at the University of Maryland. His roles include teaching courses such as Computer and Network Security (CMSC414), Computer Networking (CMSC417), and Advanced Data Structures (CMSC420). He has developed the Diptych application to assist in managing large courses on Canvas, offering cross-platform binaries and open-source code. His research interests span cybersecurity, distributed systems, and parallel programming, with a focus on peer-to-peer networks, load balancing, and cryptographic protocols. Marsh has advised students such as Cole Lashley on projects like Shellcode Compilers. His work includes contributions to desktop grid systems, trust management in distributed environments, and robust secret distribution mechanisms. He maintains an active GitHub repository for Diptych, addressing issues like group list rendering and grading reports. His publications reflect expertise in resource discovery, decentralized PKI, and network protocol optimization. Awards and grants are not explicitly listed, but his academic contributions are highlighted through his teaching innovations and open-source projects. He continues to develop educational materials, including free e-books for his courses, and supports students through detailed course expectations and supplementary resources.

• Comparative Literature
• Trauma Studies
• Gender Studies
• +7 more

Professor Katrin Wehling-Giorgi is a leading scholar in comparative literature and trauma studies at Durham University's School of Modern Languages and Cultures. She holds a D.Phil in Comparative Literature from the University of Oxford and has held fellowships at Warwick University. Her research focuses on 20th-century literature, trauma narratives, gender studies, and feminist theory, with a specialization in Italian and transnational women's writing. She directs the MA in Languages, Literatures and Cultures and chairs the Italian Studies program. Education: D.Phil (Doctorate) in Comparative Literature, University of Oxford M.St (Master's) in Comparative Literature, University of Oxford Bachelor's in Philosophy and Modern Languages, University of Oxford Research Interests: Trauma studies and its intersections with literature and visual culture Gender studies, feminist theory, and maternal imagery Comparative analysis of post-WWII women's writing (Elsa Morante, Elena Ferrante, Goliarda Sapienza) European modernism and psychoanalytic literary criticism Cross-cultural narratives of space and subjectivity Publications: Authored book: Gadda and Beckett: Storytelling, Subjectivity and Fracture (2014) Edited volumes on Elsa Morante, Elena Ferrante, and Goliarda Sapienza Recent articles on trauma topographies in Morante and Scego's works, transgenerational trauma, and feminist reimaginings of maternal narratives Awards: Gadda First Prize (2014) for her book on Gadda and Beckett Grants & Collaborations: Co-edited Fifty Years of La Storia (2024) and Trauma Narratives in Italian and Transnational Women's Writing (2022) Guest-edited special journal issues on Elena Ferrante and comparative trauma studies Current book project: Spectral (Hi)stories: Women Narrating Trauma in Post-war Italy (Palgrave Macmillan) Labs/Teams: Collaborates with global networks in medical humanities, feminist literary studies, and cultural trauma research through her fellowship at Durham's Institute for Medical Humanities.

Martin KarstenView profile

Professor

• Software Systems
• Networking
• Operating Systems
• +4 more

Martin Karsten is a Professor at the David R. Cheriton School of Computer Science, University of Waterloo, where he leads research in software systems and networking. His work focuses on finding simple approaches to building robust and efficient systems infrastructure. He teaches courses including Real-time Programming, Operating Systems, Distributed Systems, and Computer Networks. His research explores fundamental patterns for software infrastructure design and redesigning systems using modular building blocks. Primary interests include system-level runtime systems (OS kernels, hypervisors), performance optimization through simplicity, and structural commonalities across software layers. Key research areas encompass system software, network architecture, network services, and network software. Karsten holds a Diplom-Wirtschaftsinformatiker from Universität Mannheim and Dr.-Ing. from TU Darmstadt. His career includes positions as Assistant Professor (2002-2007), Associate Professor (2007-2020), and Professor (2021-present) at Waterloo, with administrative roles including Associate Director of the School since 2020. He maintains active collaborations through sabbaticals at SAP and visiting positions at TU Kaiserslautern. He currently advises multiple graduate students in the MMath program and has contributed to open-source projects like libfibre (user-level threading) and KOS (experimental OS kernel). His professional service includes roles in academic integrity initiatives and conference organization.