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Jia LiuView profile

Professor

• Computational Mathematics
• Numerical Linear Algebra
• Sparse Matrix Computations
• +9 more

Dr. Jia Liu is a Professor and Chair of the Department of Mathematics and Statistics at the University of West Florida, within the Hal Marcus College of Science and Engineering. She has been a key academic figure at UWF since 2006, leading both research and departmental initiatives in computational and applied mathematics. Her educational background includes a Ph.D. in Mathematics from Emory University, funded by the National Science Foundation, focusing on preconditioned Krylov subspace methods for incompressible flow problems. She earned her M.S. and B.A. in Mathematics from Central China Normal University, where her bachelor's thesis received the highest honor. Dr. Liu's research lies at the intersection of numerical linear algebra, scientific computing, and interdisciplinary applications. Her primary interests include: Numerical solvers for large sparse linear systems Krylov subspace iterative methods Preconditioning techniques Applications to Navier-Stokes and optimization problems Geometric and topological analysis of ellipsoids Complex networks and community detection via spectral clustering Machine learning for disease prediction and biological modeling The trends in her publications reflect a consistent focus on robust numerical algorithms with applications across fluid dynamics, network science, and biomedical modeling. Her work emphasizes both theoretical development and practical implementation in high-performance computing environments. Dr. Liu has served as an editor and editorial board member for several peer-reviewed journals and regularly reviews submissions. While specific awards are not listed, her sustained publication record in prestigious venues such as SIAM Journal on Scientific Computing and Journal of Biological Dynamics underscores her scholarly impact. As department chair and professor, she plays a central role in academic advising, curriculum development, and research mentorship. She teaches core courses including Differential Equations, Numerical Analysis, and Real Analysis, contributing significantly to both undergraduate and graduate education. Her leadership extends to managing research grants and fostering collaborations across disciplines. Though no formal lab name is mentioned, her research activities suggest involvement with computational modeling groups, likely associated with applied mathematics and data science initiatives at UWF. Her ongoing work continues to advance numerical methods for complex systems in science and engineering.

Alex Ferrer FerreView profile

Associate Professor

• Materials Design
• Aeronautical Engineering
• Computational Mechanics
• +4 more

Àlex Ferrer Ferre is a Serra-Hunter Associate Professor at the Department of Physics, Universitat Politècnica de Catalunya (UPC) in Barcelona, and an associate researcher at the International Center for Numerical Methods in Engineering (CIMNE). His research focuses on topology optimization, computational mechanics, and advanced material design. He holds a PhD in Computational Mechanics from UPC (2017) and has conducted postdoctoral research at the University of Oxford and École Polytechnique. Key roles include teaching courses like Flight Mechanics and leading the Swan project for topology optimization software. His work integrates academic and industrial collaborations with entities like ESA and INEGI. Research interests span multiscale design, topology optimization for additive manufacturing, and fracture mechanics. Major projects include the TopSat CubeSat chassis project (ESA-funded) and the Flexion project on flexible material design. Awards include the Marie Curie Fellowship (2019) and an Excellent Cum Laude PhD. His labs and teams collaborate globally, emphasizing open-source tools and collaborative research.

Heiko RiegerView profile

Professor

• Theoretical Biophysics
• Statistical Physics
• Computational Physics
• +12 more

Prof. Dr. Heiko Rieger is a full Professor in the Department of Theoretical Physics at Saarland University , within the Faculty of Natural Sciences and Technology . He leads a research group focused on theoretical biophysics, statistical physics, and computational physics, with significant involvement in the Collaborative Research Center SFB 1027, which investigates the physical principles of biological functioning. His research interests lie primarily in non-equilibrium systems , encompassing a broad range of phenomena including: The biophysics of killing , particularly how cytotoxic T cells eliminate infected or cancerous cells. Tumor growth dynamics , vascularization, interstitial fluid flow, and drug delivery. Active matter , collective behavior of self-propelled particles, and pattern formation. Stochastic search processes and optimization strategies in biological and physical contexts. Quantum phase transitions , relaxation, and thermalization in isolated quantum systems. Imbibition and fluid flow in nano-porous media. His recent publications (2024–2025) demonstrate a strong trend toward interdisciplinary modeling at the interface of physics and biology. Key themes include non-reciprocal interactions in flocking and active matter, stochastic thermodynamics in particle-field systems, collective chemotactic search , and crosstalk in cytoskeletal components during cell migration. His work combines analytical theory with computational simulations, often in collaboration with experimental groups. Prof. Rieger actively supervises a team of postdoctoral researchers and PhD students, contributing to the training of the next generation of theoretical physicists. His group members include Astik Haldar, Anil Kumar Dasanna, Marc Thome, Atul Tanaji Mohite, Jiwon Choi, Barbara Schmidt, Johannes Sicks, Marwa Hijazi, and Ivan Hornak. His research is supported through institutional affiliations and collaborative grants, notably within SFB 1027. He has no listed scientific awards in the provided text, but his extensive publication record in high-impact journals such as Physical Review Letters , Nature Communications , Biophysical Journal , and European Physical Journal underscores his scientific impact. The Rieger group is based at Campus E2.6, Room 4.17, Saarbrücken, and is part of a vibrant theoretical physics community at Saarland University.

• Optimization Theory
• Numerical Optimization
• Newton-Type Methods
• +5 more

Mikhail V. Solodov is a Researcher at the Institute for Pure and Applied Mathematics (IMPA) in Rio de Janeiro, Brazil, where he conducts cutting-edge research in optimization theory and algorithms. His work spans theoretical foundations and practical applications, with significant contributions to Newton-type methods, augmented Lagrangian techniques, and equilibrium problems. Dr. Solodov's educational background includes: Ph.D. in Optimization/Computer Sciences from University of Wisconsin-Madison (1995) M.S. in Computer Sciences from University of Wisconsin-Madison (1992) Diploma (with Honors) in Applied Mathematics from Moscow State University (1991) His research focuses on developing and analyzing optimization algorithms, particularly Newton and Newton-related methods for optimization and variational problems under weakened assumptions, augmented Lagrangian techniques, decomposition methods, and nonsmooth optimization (especially bundle methods). He has made significant contributions to understanding optimization problems with degenerate constraints and has developed relaxed regularity concepts for these challenging problems. Dr. Solodov's recent publications (2022-2025) show a strong trend toward applications in energy markets while maintaining theoretical rigor. His work bridges mathematical theory with practical implementation, demonstrating how optimization theory can solve real-world problems in energy systems and economic equilibrium modeling. The publications reveal increasing focus on equilibrium problems with applications to energy markets, while continuing to advance theoretical understanding of optimization algorithms. His recognition in the field is evident through his editorial appointments: Mathematical Programming, Series A (since 2005) Optimization Methods and Software (since 2002) SIAM Journal on Optimization (2009-2024) Dr. Solodov has also contributed to special journal issues dedicated to prominent figures in optimization, including a special issue on Hierarchical Optimization in Mathematical Programming (2023) and volumes dedicated to the memory of Prof. Naum Shor and Olvi Mangasarian.

Mark SherwinView profile

Professor

• Condensed Matter Physics
• Terahertz Science
• Quantum Optics
• +3 more

Mark Sherwin is a Professor of Physics and Director of the Institute for Terahertz Science and Technology at the University of California, Santa Barbara (UCSB) . His research focuses on experimental condensed matter physics using terahertz (THz) free-electron lasers (FELs) for quantum control and spectroscopy. He has mentored over 30 graduate students and holds Fellowships from the American Physical Society and the Alfred P. Sloan Memorial Fellowship . Harvard College BA (1981) UC Berkeley PhD (1988) Research Areas : Quantum coherence in spin systems Terahertz-driven electron-hole recollisions High-field electron paramagnetic resonance (EPR) Quantum dot and nanostructure dynamics Nonlinear optics in semiconductors Charge-density-wave materials Scientific Awards : Fellow, American Physical Society Alfred P. Sloan Memorial Fellowship Collaborations include NASA’s Jet Propulsion Laboratory, small companies for THz modulation, and Prof. Songi Han (UCSB Chemistry/Biochemistry). His group designs custom apparatus with Dr. Nikolay Agladze and develops THz detectors/mixers.

Niv BuchbinderView profile

Professor

• Combinatorial Optimization
• Online Algorithms
• Algorithmic Game Theory
• +2 more

Prof. Niv Buchbinder is a faculty member in the Department of Statistics and Operations Research at the School of Mathematical Sciences, Tel Aviv University. His research centers on algorithmic solutions for combinatorial optimization in offline and online contexts, with significant contributions to primal-dual methodologies and algorithmic game theory. His academic background includes a Ph.D. in Computer Science from the Technion (2008) under Prof. Seffi Naor and an M.Sc. in Computer Science from the Technion (2003) under Prof. Erez Petrank. Key research areas encompass Combinatorial Optimization, Online Algorithms, Algorithmic Game Theory, Primal-Dual Methods, and Submodular Optimization, focusing on competitive analysis for problems like set cover, ad-auctions, and caching. Recent publications (2012-2015) reveal a concentrated effort in submodular optimization and online decision-making, with applications in advertising, resource allocation, and machine learning. These works consistently employ primal-dual frameworks to achieve strong competitive ratios in adversarial settings. Scientific recognition includes: Best Paper Award at ESA 2007 for “Online Primal-Dual Algorithms for Maximizing Ad-Auctions Revenue” Best Paper Award at FOCS 2011 for “A Polylogarithmic Competitive Algorithm for the k-Server Problem” No information is available regarding student advising or research grants. Similarly, details about laboratory facilities, research teams, or future projects are not provided in the source materials.

Heloisa Cristina Figueiredo FrizzoView profile

Associate Professor

• Occupational Therapy
• Palliative Care
• Cancer Care
• +4 more

Heloisa Cristina Figueiredo Frizzo is an Associate Professor in the Occupational Therapy program at the Institute of Health Sciences, Universidade Federal do Triângulo Mineiro (UFTM) in Uberaba, Minas Gerais, Brazil. As a PhD in Sciences and Master in Medical Sciences, she contributes significantly to both undergraduate and graduate education in occupational therapy, with a focus on hospital contexts and palliative care. Her academic work bridges theoretical knowledge with practical healthcare applications. Dr. Frizzo's research spans multiple dimensions of occupational therapy, with particular emphasis on palliative care, cancer treatment contexts, grief and bereavement processes, and the integration of digital technologies in healthcare. Her work explores how occupational therapy can enhance patient self-care capacity during chemotherapy, optimize care for children and adolescents with cancer through digital games, and address the emotional aspects of cancer treatment through music therapy. She has made significant contributions to understanding how healthcare professionals process death in oncology settings and intensive care units. Her publication record reveals a consistent focus on innovative therapeutic approaches, including auriculotherapy for mental health conditions, virtual technologies for patient care, and collaborative care models through digital platforms. The trajectory of her research demonstrates an evolving interest in integrating complementary therapies with traditional occupational therapy practices, particularly in challenging healthcare contexts like cancer treatment and end-of-life care. Dr. Frizzo has been actively involved in professional development initiatives, including coordinating videoconferencing activities through the Telemedicine University Network to support continuing education for occupational therapists. Her work reflects a commitment to advancing the field through both scholarly research and practical applications that improve patient care experiences.

• Materials Science
• Applied Mathematics
• Partial Differential Equations
• +5 more

Pierluigi Cesana is a Professor conducting research at the intersection of Materials Science and Applied Mathematics. His work centers on mathematical analysis of singular equations and ill-posed optimization problems, with applications in elasticity theory and materials science, while integrating analytical methods with Artificial Intelligence techniques. His primary research areas include: Mathematical analysis of Partial Differential Equations (PDEs) and Boundary Value Problems with highly oscillating solutions Calculus of Variations, relaxation, and Gamma-convergence for material behavior modeling Integration of variational analysis with AI methods (machine learning, neural networks, genetic algorithms) Micro- and nano-scale instabilities in multifunctional materials influencing macroscopic engineering systems Recent extensions to financial mathematics and blockchain technology using probability and statistics Cesana leads a research lab addressing complex multi-physics phenomena, such as optimizing ring-opening reaction rates in nanoswitches through combined quantum mechanics and thermodynamics frameworks. His theoretical work examines pattern formation and topological defects in soft crystals and shape-memory alloys. No scientific awards were mentioned in the source text. Details about student advising, grants, or specific laboratory teams were not provided.

• Work and Health
• Health Diagnostics
• Data Science
• +4 more

Dr. Patric Wyss is a Research Associate at the School of Applied Psychology, University of Applied Sciences Northwestern Switzerland (FHNW) and concurrently serves as a Research Associate at the Institute for Social and Preventive Medicine (ISPM), University of Bern. His interdisciplinary work bridges psychology, data science, and healthcare, focusing on innovative approaches to health diagnostics and workplace mental health. Dr. Wyss completed his academic training at the University of Bern, Switzerland with a Doctorate in Biomedical Sciences (2019-2022), Master's degree in Statistics and Data Science (2017-2020), Master's degree in Psychology (2014-2017), and Bachelor's degree in Psychology with a Minor in Mathematics (2010-2014). His research interests center on work and health, predicting health variables with complex algorithms, and data-driven personalized health diagnostics. Dr. Wyss has made significant contributions to dementia diagnosis through data-driven approaches, cognitive assessment tools, and digital interventions for mental health. His work often integrates machine learning with clinical psychology to develop predictive models for health outcomes. Analysis of his recent publications reveals a strong focus on neurodegenerative diseases, particularly dementia and cognitive decline in aging populations. His research increasingly incorporates digital health technologies, virtual reality, and algorithmic approaches to develop personalized diagnostic tools. The publications demonstrate a progression from fundamental cognitive neuroscience to applied health diagnostics with practical workplace applications. Dr. Wyss has been actively involved in several significant projects including Digital Balance, Healthy@Work, and work-related stress and mental disorders in the workplace. His current position at the Institute for Mental and Organizational Health at FHNW focuses on how digitalization, social upheavals, and new forms of work present both opportunities and challenges for mental and organizational health. His professional activities include research collaboration across multiple institutions, development of digital assessment tools, and investigation of HR analytics applications for health monitoring. Dr. Wyss has also contributed to the development of serious games for cognitive assessment and rehabilitation, particularly for older adults and patients with neurological conditions.

Rakesh VenkatView profile

Assistant Professor

• Theoretical Computer Science
• Approximation Algorithms
• Hardness of Approximation
• +1 more

Rakesh Venkat is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad. His research focuses on Theoretical Computer Science, including approximation algorithms, hardness of approximation, and communication complexity. Education : Ph.D., Tata Institute of Fundamental Research (TIFR), Mumbai. Research Trends : His work addresses fundamental challenges in algorithm design, such as optimizing cache misses, improving clustering algorithms, analyzing graph expansion, and exploring embedding techniques. Publications span top-tier conferences like APPROX, FSTTCS, ICALP, and ITCS, with collaborations at institutions including HUJI, TIFR, and IIT-Bombay. Teaching : Courses taught include Approximation Algorithms, Advanced Data Structures, Discrete Mathematics, and Spectral Graph Theory.

• Computer Architecture
• Memory Models
• Parallel Programming
• +4 more

Sarita Adve is the Richard T. Cheng Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign, recognized for transformative contributions to memory consistency models and leadership in computing communities. Her research spans the hardware/software interface with core expertise in memory models for programming languages (C++/Java), cache coherence, hardware reliability, and power management. Current work focuses on scalable system specialization and resiliency, including groundbreaking DRFrlx semantics for relaxed atomics in heterogeneous systems. She challenges conventional wisdom by demonstrating data-race-free models' superiority across diverse computing environments. Adve's major awards include: ACM-IEEE CS Ken Kennedy Award (2018) for memory model leadership and exceptional mentoring ACM Fellow (2010) for contributions to hardware/language memory models and resilient systems IEEE Fellow (2012) and Anita Borg Institute Woman of Vision award SIGARCH Maurice Wilkes Award (2008) She provides exceptional mentorship with three of her PhD students' theses nominated for the ACM Doctoral Dissertation Award within five years. As SIGARCH chair, she revolutionized community engagement through CARES (harassment support initiative), diversity programs, and DARPA ISAT participation, while previously serving on NSF CISE and Computing Research Association boards.

Soham ChakrabortyView profile

Assistant Professor

• Programming Languages
• Compilers
• Computer Architecture
• +3 more

Soham Chakraborty is an Assistant Professor at the Programming Languages Group, TU Delft since 2021. He previously served as an Assistant Professor at the CSE Department, IIT Delhi before joining TU Delft. His academic journey includes a PhD from Max Planck Institute for Software Systems (MPI-SWS) in 2019 and a Master's degree from CSE Department, IIT Kharagpur in 2008. Affiliation: TU Delft, IIT Delhi, MPI-SWS Research Interests: Programming Languages, Compilers, Architecture, Verification, Concurrency His research focuses on formal semantics, compiler correctness, architecture-to-architecture translation, and verification of weak memory models. He has contributed to major conferences including POPL, PLDI, CGO, and ASPLOS. His work addresses challenges in heterogeneous concurrency, relaxed memory concurrency, and binary translation for weak memory architectures. Recent works include How Hard is Weak-Memory Testing? (POPL'24) and Toast: A Heterogeneous Memory Management System (PACT'24). He also received the Distinguished Paper Award at DATE'25 and Distinguished Artifact Award at PODC'22 . Teaching: Courses like Concepts of Programming Languages (CS2120), Parallel and Concurrent Programming (CS4555), Compiler Construction (CS4555), Analysis of Concurrent and Distributed Programs (CS4405), Software Fundamentals (Rust), and Seminar Programming Languages (COL 380) Students: PhD student Dennis Sprokholt, MSc students Michal Raczkiewicz, Alexandru Dumitriu, Huixuan Wu, and alumni including Pieter van den Ham, Mingyu Gao, Jeroen Kloppenburg, and others. Service: Served on program committees for POPL, PLDI, CGO, VMCAI, APLAS, and Eurosys workshops.

Xinyu FengView profile

Professor

• Programming Languages
• Formal Methods
• Concurrency Theory
• +3 more

Xinyu Feng is a Professor at the Department of Computer Science and Technology , Nanjing University , and collaborates with Huawei . His work focuses on programming languages and formal methods , particularly concurrent system software verification , separation logic , and certified compilation . His research has produced influential contributions in verifying low-level system software with hardware interrupts, preemptive threads, and concurrent data structures. Notable publications include work on progress guarantees for concurrent objects modular verification of synchronization primitives parameterized memory models . In professional activities, he has served on program committees for major conferences like PLDI'21 , POPL'18 , and CAV'16 . He received a Distinguished Paper Award at PLDI'19 .

Mohamed Faouzi AtigView profile

Professor

• Formal Verification
• Concurrency
• Model Checking
• +4 more

Mohamed Faouzi Atig is a Professor in Computer Systems at Uppsala University's Department of Information Technology since July 2021, following a progression from Assistant Professor (2014-2018) to Associate Professor (2018-2021). His academic career began with a post-doctoral position at Uppsala University (2010-2012) after earning his PhD from University of Paris Diderot-Paris 7 in 2010, followed by a docent degree (habilitation equivalent) from Uppsala University in 2017. His research focuses on formal verification of concurrent and infinite-state systems, with particular expertise in model checking , weak memory models (including x86-TSO, Release-Acquire), and automata theory applied to string constraints. His work bridges theoretical foundations with practical verification techniques for modern hardware and programming language semantics. Analysis of his publication record reveals a sustained focus on verification challenges in concurrent systems, evolving from foundational work on memory models (2015) to sophisticated techniques for string constraints (2017) and persistent memory (2024-2025). His research demonstrates consistent contributions to top venues like PLDI and POPL, with increasing complexity in handling real-world memory models while maintaining theoretical rigor. At Uppsala University, he has served on program committees for major conferences including POPL, VMCAI, and SPLASH, demonstrating active engagement with the programming languages research community.

Minki ChoView profile

Research Fellow

• Verified Compilation
• Relaxed Memory Concurrency
• Program Logic
• +2 more

Minki Cho is a Research Fellow in the Department of Computer Science and Engineering at Seoul National University, South Korea. Having completed their Ph.D. in August 2023 with a thesis titled "Simplifying Reasoning under Weak Memory Concurrency," they continue active research while maintaining institutional affiliation. Cho's educational background includes: Sep. 2017 - Aug. 2023: Ph.D. Computer Science and Engineering, Seoul National University Mar. 2014 - Feb. 2017: B.S. Computer Science and Engineering, B.S. Philosophy of Mathematics and Logics (double major), Seoul National University Mar. 2011 - Feb. 2014: Seoul Science High School Cho's research focuses on Verified Compilation , Relaxed Memory Concurrency , and Program Logic , bridging theoretical foundations with practical applications in programming language design and verification. Their work addresses fundamental challenges in weak memory models, compiler optimizations, and formal verification frameworks, with particular emphasis on developing rigorous semantic models that enable practical compiler optimizations while maintaining program correctness. Cho's publication record demonstrates consistent contributions to top-tier venues including PLDI, POPL, and OOPSLA from 2020-2025, showing evolution from foundational work on relaxed memory concurrency toward more comprehensive verification frameworks supporting complex language features like integer-pointer casting and liveness properties. Recognition for Cho's work includes: PhD Dissertation Award, Department of Computer Science and Engineering, Seoul National University (2023) Gold medal in University Students Contest of Mathematics, Korean Mathematical Society (2014) Prior to completing their Ph.D., Cho gained teaching experience as a TA for: Computational Civilization (2020 Spring) Programming Languages (2019 Fall) Principles and Practices of Software Development (2019 Spring/2018 Spring) Principles of Programming (2018 Fall)