جست‌وجوی استاد و پژوهشگر

• Pulmonary Medicine
• Critical Care Medicine
• Cardiovascular Research
• +۳ مورد دیگر

Edward Manning is an Assistant Professor of Medicine (Pulmonary) at Yale School of Medicine. He specializes in pulmonary and critical care medicine, treating chronic lung disorders and cardiopulmonary issues. He holds dual MD/PhD degrees from Albert Einstein College of Medicine and completed residency at the Hospital of the University of Pennsylvania and a fellowship at Yale. Education: MD/PhD (Biophysics), Albert Einstein College of Medicine (2014) Residency: Internal Medicine, Hospital of the University of Pennsylvania (2016) Fellowship: Pulmonary/Critical Care, Yale School of Medicine (2020) His research focuses on cardiopulmonary aging, hypoxia-induced vascular remodeling, and pulmonary fibrosis. Key projects include studying age-related stiffening of pulmonary arteries and the role of GPR87 in fibrosis. Publications highlight themes such as chronic hypoxia effects, vascular senescence, and translational immunology. Notable awards include the Butler-Williams and Pepper Scholarships, recognizing his contributions to aging research and translational medicine. Grants/Awards: National Institute on Aging (Butler-Williams Scholar) Yale Pepper Center (Pepper Scholar) He collaborates with labs like the Kaminski Lab and leads projects in the Pulmonary Vascular Disease Program. His work integrates clinical care, basic science, and translational research to address cardiopulmonary health challenges.

Louise Skinnariمشاهده پروفایل

استادیار

• Experimental Particle Physics
• High Energy Physics
• Top Quark Studies
• +۴ مورد دیگر

Louise Skinnari is an Assistant Professor in the Department of Physics at Northeastern University, affiliated with the College of Science. Her research focuses on experimental particle physics using the CMS detector at CERN's Large Hadron Collider (LHC), particularly studying top quarks and upgrading the CMS trigger system to enhance charged particle trajectory identification. Prior to Northeastern, she was a research associate at Cornell University working on the CMS experiment, and completed her PhD at UC Berkeley investigating physics beyond the Standard Model with the ATLAS experiment. Education: PhD in Physics from University of California, Berkeley (ATLAS Collaboration); prior work at Cornell University (CMS Collaboration). Research Interests: Experimental particle physics, top quark dynamics, dark matter detection, Standard Model precision measurements, and detector development for high-luminosity LHC runs. She contributes to the Future Circular Collider feasibility studies and explores novel signatures of beyond-Standard-Model physics through CMS data. 2025 Breakthrough Prize in Fundamental Physics (shared with Northeastern team) 2020 Department of Energy Physics Grant recipient Her work involves collaborations on detector upgrades, including the CMS Phase-2 Outer Tracker, and employs advanced analysis techniques such as machine learning for event classification. Active in both proton-proton and heavy ion collision studies, her research bridges fundamental physics questions with cutting-edge experimental techniques. Labs/Groups: CMS Collaboration at CERN, Northeastern High Energy Physics Group, and Future Circular Collider Studies.

• Kidney Disease
• Cardiology
• Extracellular Matrix Regulation
• +۳ مورد دیگر

Zafer Akman, MD is a Research Fellow at the Yale School of Medicine (Yale SOM), affiliated with the Department of Internal Medicine and the Cantley Lab. He completed his MD at Istanbul University-Cerrahpasa in 2022. His research focuses on extracellular matrix regulators in kidney diseases, particularly the role of metalloproteinases in polycystic kidney disease. He also contributes to cardiovascular research, studying antiplatelet therapies, cardiomyopathy treatments, and cardiac toxicity. Additional interests include sarcopenia in kidney transplant recipients and inflammatory mechanisms in autoimmune disorders. Education: MD, Istanbul University-Cerrahpasa (2022) Research Interests: Polycystic Kidney Disease Pathogenesis Cardiovascular Pharmacology and Surgery Complications Sarcopenia in Chronic Illness Inflamed Tissue Immunology (B Cell Subsets) Key Contributions: His recent work includes landmark studies on ADAMTS1’s role in cyst expansion (JASN, 2024) and the impact of ticagrelor on CABG bleeding (Heart Vessels, 2024). Collaborations with Prof. Cantley and Dr. Somlo highlight his involvement in translational nephrology research. Labs/Teams: Active member of the Cantley Lab, investigating molecular mechanisms in renal pathologies.

• Lyme Disease
• Immunology
• Infectious Diseases
• +۳ مورد دیگر

Linda Bockenstedt is the Harold W. Jockers Professor of Medicine and Deputy Dean for Faculty Affairs at Yale School of Medicine. She holds appointments in the Section of Rheumatology and the Department of Medicine. With a PhD from Harvard and MD from Ohio State University, she completed residency and fellowship training at Yale and UCSF. Her research focuses on Lyme disease pathogenesis, host immune responses to Borrelia burgdorferi, and improving diagnostic methods. She has been funded by NIH since 1990 and leads studies on spirochete motility, antigen persistence, and inflammation post-treatment. Collaborations include work with L2 Diagnostics to develop novel diagnostic tests using in vivo expressed antigens. Education: AB in Chemistry & Physics, Harvard College (1977) MD, The Ohio State University College of Medicine (1981) Fellowship in Rheumatology, UCSF (1989) Research Interests: Linda’s work spans immunology, microbiology, and infectious diseases. Key areas include: Host immune response to Lyme disease spirochetes Mechanisms of pathogen persistence and antigenic debris Role of spirochete motility and membrane fluidity in evading immune defenses Development of improved Lyme disease diagnostics Recent Articles: Her 2024 studies highlight omics approaches in Lyme disease, B cell immunophenotyping in skin lesions, and Borrelia miyamotoi diversity. Articles emphasize proteomic analysis of host responses and comparative studies with West Nile virus. Awards: Master of the American College of Rheumatology Elected member, The Henry Kunkel Society Best Doctors in America Advising & Grants: As Deputy Dean, she supports faculty development and equity initiatives. Her grants focus on aging immune systems and interdisciplinary Lyme disease research with engineers and data scientists. Labs & Teams: Collaborations with Eric Dufresne (Engineering) and L2 Diagnostics advance spirochete biophysics and diagnostic tools. Her lab uses multiphoton microscopy and speckle microscopy to study real-time pathogen dynamics.

• Numerical Linear Algebra
• Scientific Computing
• Image Reconstruction
• +۵ مورد دیگر

Misha Kilmer is the William Walker Professor of Mathematics at Tufts University, with a secondary appointment in Computer Science. She also serves as Deputy Director of ICERM at Brown University and co-PI of Tufts TRIPODS Institute. Her research focuses on numerical linear algebra, scientific computing, and image reconstruction/restoration. Kilmer has held leadership roles, including Chair of Tufts' Mathematics Department (2013-2019) and has received prestigious recognition, including SIAM Fellowship (2019) and the Tufts Undergraduate Teaching Award (2001). Education: PhD in Applied Mathematics, University of Maryland (1997) MA in Mathematics, Wake Forest University (1994) BS in Mathematics, Wake Forest University (1992) Research Interests: Kilmer's work emphasizes tensor decompositions, iterative methods, and model reduction. She develops algorithms for high-dimensional data analysis, imaging applications, and inverse problems. Her techniques bridge computational mathematics and engineering challenges, with applications in biomedical imaging, environmental monitoring, and machine learning. Publications Trends: Recent work highlights advancements in tensor-based neural networks, dynamic image reconstruction, and efficient algorithms for large-scale data. Key contributions include randomized algorithms for tensor decompositions and compressed sensing techniques for multi-modal data. Awards: SIAM Fellow (2019) Tufts Undergraduate Initiative in Teaching Award (2001) Advising & Grants: Kilmer has secured funding from NSF, NIH, IARPA, DARPA, and IBM. She co-chairs major SIAM conferences and serves on editorial boards for journals like SIAM Review and La Matematica . Labs/Teams: Active in Tufts' Data Intensive Studies Center (DISC) and co-leads the TRIPODS Institute. Collaborates internationally on projects involving tensor analysis and computational science.

Harikrishnan Parameswaranمشاهده پروفایل

دانشیار

• Biomechanics
• Mechanobiology
• Respiratory Physiology
• +۳ مورد دیگر

Harikrishnan Parameswaran is an Associate Professor in the Department of Bioengineering at Northeastern University’s College of Engineering. His research focuses on cell-cell and cell-extracellular matrix (ECM) interactions in airways, particularly investigating mechanisms underlying airway narrowing and asthma pathology. He holds a PhD in Biomedical Engineering from Boston University and completed an NIH K99 postdoctoral fellowship there under Dr. Kenneth Lutchen. Education: NIH K99 Postdoctoral Fellow, Boston University Ph.D., Biomedical Engineering, Boston University (Advisor: Dr. Bela Suki) M.S., Biomedical Engineering, Boston University B.Tech, Electronics & Telecommunication, College of Engineering, Trivandrum, India Research Interests: His lab, the Breathe Lab, explores ECM-driven hypercontractility in airway smooth muscle cells and its role in asthma. Key areas include mechanobiology of airway narrowing, ECM stiffness effects, and intercellular communication in smooth muscle physiology. His work bridges computational modeling and experimental approaches to understand disease mechanisms. Awards & Grants: NSF CAREER Award (2021) NIH R01 (2020) American Thoracic Society Rising Star (2023) Principal Investigator on multiple NIH and institutional grants Teaching: Courses include BIOE 5440 (Cell as a Machine), BIOE 5800 (Systems, Signals, and Controls), and GE2361 (Math Methods in Bioengineering). Labs & Teams: Leads the Breathe Lab, collaborating with institutions like Boston University and the Institute for Mechanobiology. Research focuses on translational studies linking molecular mechanisms to clinical asthma therapies.

Tony Seمشاهده پروفایل

استادیار

• Commutative Algebra
• Homological Algebra
• Algebraic Geometry
• +۳ مورد دیگر

Dr. Tony Se is an Assistant Professor in the Department of Mathematics at Florida A&M University (FAMU), part of the College of Science & Technology. He holds a Ph.D. in Mathematics from the University of Kansas (2016). His academic journey includes postdoctoral research at West Virginia University (2019–2021) and a Visiting Assistant Professorship at the University of Mississippi (2016–2019). Education: Ph.D. in Mathematics, University of Kansas, 2016 Research Interests: Dr. Se specializes in Commutative Algebra and Homological Algebra , with contributions to algebraic geometry and category theory. His work explores semidualizing modules, Cohen-Macaulay properties, and asymptotic stability in algebraic structures. Awards: 2023 Faculty Research Awards Program (FRAP), FAMU, $5000 Teaching & Grants: He teaches courses including Calculus I/II, College Algebra, and Abstract Algebra. His 2023 research grant supports undergraduate research projects in his field. Labs/Teams: No specific labs or teams mentioned, but collaborates with researchers like Hailong Dao, Sandra Spiroff, and Olgur Celikbas.

Michael Bronsteinمشاهده پروفایل

استاد

• Geometric machine learning
• Deep learning on graphs
• 3D shape analysis
• +۷ مورد دیگر

Michael Bronstein is a Professor & Chair in Machine Learning and Pattern Recognition at the Department of Computing, Imperial College London (since 2018), with a concurrent professorship at the Institute for Computational Science, University of Lugano, Switzerland (since 2010, currently on leave). His academic career includes visiting positions at Stanford University (Visiting Lecturer, 2008-2009), Tel Aviv University (Visiting Associate Professor, 2015-2017), Harvard University (Visiting Scholar, 2017-2018), and MIT (Research Affiliate, 2017-2018). Dr. Bronstein's research focuses on theoretical and computational geometric methods for data analysis, with applications spanning machine learning, computer vision, graphics, geometry processing, biology, and social networks. His work in geometric deep learning has established foundational frameworks for processing non-Euclidean data such as graphs and manifolds, bridging the gap between traditional Euclidean deep learning and complex structured data. His publication record demonstrates a clear trajectory from fundamental geometric methods to their application in diverse domains. Early work focused on 3D shape analysis and non-rigid shape recognition, while more recent publications showcase the application of geometric deep learning to protein structure analysis, point cloud processing, and graph-based machine learning. The consistent thread throughout his research is the development of mathematical frameworks that respect the intrinsic geometry of data. Royal Academy of Engineering Silver Medal (2020) Fellow of IEEE, IAPR, and ELLIS Five ERC grants (Starting 2012, Consolidator 2016, and Proof of Concept 2016, 2018, 2019) Royal Society Wolfson Research Merit Award Young Scientist, World Economic Forum (2014) Bronstein has successfully translated academic research into practical applications through multiple entrepreneurial ventures. As ML Lead for Project CETI and Head of Graph Learning Research at Twitter (since 2019), he bridges academic research with industrial applications. His previous startups include Fabula AI (acquired by Twitter in 2019) and Invision (acquired by Intel in 2012), where he contributed to the development of Intel RealSense 3D camera technology. His research has been supported by significant funding including ERC grants and industry awards from Google, Amazon, and Facebook.

Sebastian Schlechtمشاهده پروفایل

استاد مهمان

• Acoustics
• Signal Processing
• Reverberation
• +۴ مورد دیگر

Sebastian Schlecht is a Visiting Professor in the Department of Information and Communications Engineering at Aalto University, associated with the Virtual Acoustics research group. He holds a Doctoral degree in Engineering and Technology from Friedrich-Alexander-Universität Erlangen-Nürnberg (2017). His research focuses on acoustics, signal processing, and audio engineering, with a strong emphasis on reverberation, impulse response analysis, and feedback systems. Key research contributions include advancements in room impulse response completion, feedback delay networks, and audio processing libraries. His work has led to multiple awards, including the Best Paper Award at WASPAA 2019 and recognition at DAFx conferences. Schlecht leads the CExAM ARTS-ELEC project (2023–2027), exploring multi-objective optimization in digital signal processing. He has supervised five theses and contributed to datasets like the 'Sauna Impulse Responses' and 'Variable Acoustics Room Arni' collections. His research aligns with UN Sustainable Development Goals related to innovation and infrastructure.

• Pharmacology
• Vascular Biology
• Preclinical Drug Development
• +۳ مورد دیگر

Denis deBlois is a Full Professor at the Faculty of Pharmacy, Université de Montréal, where he maintains an active research program in cardiovascular pharmacology and drug development. His laboratory is located in the Jean Coutu Pavilion, office 2266. Dr. deBlois holds a Ph.D. in Pharmacology from Université Laval (1991) and completed postdoctoral training in General Pathology at the University of Washington, Seattle (1994). His primary research interests include vascular biology, pharmacometrics, pharmacotherapy, and preclinical drug development. Dr. deBlois leads projects focused on hypertension pathogenesis, cardiac remodeling, and vascular dysfunction mechanisms, with particular emphasis on the role of kinin receptors and the renin-angiotensin system. His work spans basic molecular mechanisms to translational applications in cardiovascular disease. Analysis of his recent publications reveals consistent focus on hypertension mechanisms, vascular remodeling, erectile dysfunction related to cardiovascular disease, and developmental origins of adult cardiovascular disorders. His research frequently employs rat models to investigate molecular pathways involved in cardiac and vascular pathologies, with particular attention to receptor signaling systems including muscarinic cholinergic receptors and kinin receptors. Dr. deBlois serves as a member of the GRUM (Groupe de recherche universitaire sur le médicament) and the Orthopedic Molecular Biology Laboratory. He has received funding from major Canadian research agencies including FRQS and CIHR for projects spanning from 2008 to ongoing work through 2029. He has supervised multiple Master's students including Etienne Durette (2017), Frédéric Mampouma Mantsouaka (2010), Marielle Doyon (2009), and France Wagner (2008). His teaching responsibilities include courses SBP1000 (Drug Discovery and Development), SBP2052 (Preclinical Safety and Toxicity), SBP2100 (Human Pathophysiology 3), and SBP3016 (Integration Project: Concepts and Skills 1).

Xiao Fuمشاهده پروفایل

دانشیار

• Machine Learning
• Signal Processing
• Optimization
• +۵ مورد دیگر

Xiao Fu is an Associate Professor in the Department of Electrical Engineering and Computer Science at Oregon State University's College of Engineering. He holds a B.S. (2005) and M.S. (2010) in Communications and Information Engineering and Signal and Information Systems from the University of Electronic Science and Technology of China (UESTC), and a Ph.D. (2014) in Electronic Engineering from The Chinese University of Hong Kong (CUHK). His research focuses on machine learning, signal processing, and optimization, with applications in nonlinear factor analysis, unsupervised learning, and deep neural networks for signal processing tasks. He has received notable awards including the 2022 NSF CAREER Award and the 2024 OSU Promising Scholar Award. His work emphasizes developing robust algorithms for factor analysis (e.g., tensor and matrix factorization), large-scale optimization in data mining, and deep learning techniques for hyperspectral imaging, radio map estimation, and crowd-sourced label analysis. Key research groups affiliated with him include Data Science and Engineering, Artificial Intelligence and Robotics, and Communications and Signal Processing. His recent projects include advancing unsupervised machine learning to reduce reliance on labeled data in AI systems and exploring applications in environmental sensing and medical imaging. Xiao Fu's publications span topics like radio map estimation via latent-domain denoisers, noisy label learning with crowd wisdom, and identifiability in nonlinear mixture models. His research bridges theoretical advancements in optimization and practical applications in wireless communication, ecological networks, and biomedical imaging. Current efforts aim to enhance unsupervised deep representation learning and develop scalable algorithms for high-dimensional data analysis. Awards: NSF CAREER Award (2022), OSU Promising Scholar Award (2024) Grants: NSF-funded CAREER Award project on nonlinear factor analysis tools Labs/Teams: Affiliated with interdisciplinary teams in signal processing, AI, and ecological systems modeling

Ian M.C. Dixonمشاهده پروفایل

استاد

• Molecular Cardiology
• Cardiac Fibrosis
• Heart Failure
• +۹ مورد دیگر

Dr. Ian M.C. Dixon is a Professor in the Department of Physiology at the University of Manitoba and a Principal Investigator at the Institute of Cardiovascular Sciences. His research focuses on the molecular mechanisms underlying cardiac fibrosis and heart failure, particularly in the context of myofibroblast activation and extracellular matrix remodeling. Dr. Dixon obtained his PhD from the University of Manitoba in 1990 and completed a postdoctoral fellowship at the University of Toronto under Drs. Mike Sole and C.C. Liew. His academic journey has been deeply rooted in cardiovascular sciences, with a sustained focus on fibrotic pathways in the heart. His research interests include cardiac fibrosis, myofibroblast biology, Smad and Hippo signaling pathways, autophagy, apoptosis, and extracellular matrix dynamics . His lab investigates how signaling proteins regulate fibroblast-to-myofibroblast transition, collagen production, and cell viability. A major goal is to identify endogenous inhibitors of fibrosis such as Smad7 and Ski, and to explore therapeutic strategies to modulate fibrotic progression in heart disease, particularly heart failure with preserved ejection fraction (HFpEF). Dr. Dixon has co-edited the book "Cardiac fibrosis and heart failure: Cause or effect?" with Dr. Jeffrey Wigle, reflecting his leadership in the field. His work combines molecular biology, cell culture, transgenic models, and whole-animal physiology, with a 25-year expertise in rat myocardial infarction models and recent development of inducible knockout mouse lines. Heart and Stroke Foundation of Manitoba Robert E. Beamish Memorial Award (2002, 2007) Myles Robinson Heart Health Scholarship CIHR (MRC) Scholar MHRC Scholar Heart and Stroke Foundation Studentship Medical Research Council of Canada Post-Doctoral Fellowship Dr. Dixon has supervised 26 graduated graduate students and currently mentors 4. He has received continuous funding and has served on national and international review panels including CIHR, NIH (USA), Heart and Stroke Foundation (Canada), Wellcome Trust, Alberta Heritage Foundation, and Michael Smith Foundation. He is an active reviewer for journals such as Cardiovascular Research, Circulation, Circulation Research, American Journal of Physiology, Journal of Cell Science, and Journal of Cell Physiology . His laboratory collaborates with leading scientists including Drs. Wayne Giles (Calgary), Boris Hinz (Toronto), M. Fujii (NIH), Francesco Ramirez (Mount Sinai), Hiroshi Miyazono (Tokyo), Hal Dietz (Baltimore), Jeffery Molkentin (Cincinnati), Paul Benya (UCLA), and University of Manitoba colleagues Jeff Wigle, Mike Czubryt, Andrew Halayko, Tom Klonisch, and Grant N. Pierce. The lab has pioneered techniques in FTIR microspectroscopy for collagen assessment and studies on trans fatty acid effects on myofibroblast viability.

Milan Pokornýمشاهده پروفایل

دانشیار

• Graph Theory
• Integral Graphs
• Discrete Mathematics
• +۳ مورد دیگر

Milan Pokorný is an Associate Professor at the Department of Mathematics and Informatics, Faculty of Education, University of Trnava in Trnava. His academic career spans over two decades, with significant contributions to graph theory and mathematical education. He actively engages in research, teaching, and educational technology development. His research interests include Graph Theory Integral Graphs Discrete Mathematics Mathematical Education Algorithm Complexity Statistical Data Processing The majority of his publications focus on spectral properties of graphs and educational methodologies. His work explores integral complete multipartite graphs, distance energy of graphs, and blended learning approaches in mathematics education. Milan Pokorný teaches courses in descriptive statistics, algorithm complexity theory, mathematics for natural sciences, financial mathematics, and technology integration for mathematics educators. He provides supporting materials for various subjects and maintains regular consultation hours for students.

Harald Lanigمشاهده پروفایل

دانشیار

• Molecular Dynamics
• Computational Chemistry
• Protein-Ligand Interactions
• +۲ مورد دیگر

Dr. Harald Lanig serves as Executive Secretary at the Erlangen National High Performance Computing Center (NHR@FAU) at Friedrich-Alexander-Universität Erlangen-Nürnberg, while maintaining active research in computational chemistry and molecular modeling. Previously, he was Managing Director of the Central Institute for Scientific Computing (ZISC) from 2013-2019 and has held various research positions at the University since completing his habilitation. Dr. Lanig received his Dr. rer. nat. from the Institute of Physical Chemistry at Julius-Maximilians University of Würzburg, with his thesis focusing on fluorescence spectroscopy and semiempirical model calculations. He completed his habilitation in Pharmaceutical Chemistry at the University of Erlangen-Nuremberg in 2012 with research on molecular dynamics simulations of organic molecules and biopolymers. His research interests center on computational approaches to biomolecular systems, with particular expertise in molecular dynamics simulations, protein-ligand docking, and comparative modeling techniques. His work spans applications in pharmaceutical chemistry, plant biochemistry (particularly cardenolide biosynthesis), structural biology of extracellular matrix proteins, and immunology. Analysis of his recent publications reveals a consistent focus on applying computational methods to solve complex biological problems, with increasing interdisciplinary collaborations spanning biochemistry, plant sciences, and immunology. His work demonstrates strong continuity in methodological approaches while expanding into new biological applications. Dr. Lanig has maintained an active research program alongside his administrative responsibilities, with 15 publications in the last five years (2019-2024) as co-author, demonstrating his ongoing engagement with the scientific community. His research has been supported through Collaborative Research Centers including CRC 814 (Additive Manufacturing) and CRC 1411 (Design of Particulate Products). As Executive Secretary at NHR@FAU, he oversees administrative operations of the National Center for High Performance Computing while continuing his research activities. His dual role bridges computational infrastructure management with active scientific research, positioning him at the intersection of high-performance computing and molecular sciences.

Tomasz Kociumakaمشاهده پروفایل

استاد

• String Algorithms
• Pattern Matching
• Edit Distance
• +۵ مورد دیگر

Tomasz Kociumaka is a Professor and Group Leader in the Algorithms and Complexity Department at the Max Planck Institute for Informatics in Saarbrücken, Germany. He previously served as a Research Scientist at INSAIT in Sofia, Bulgaria (2024-2025), and as a Postdoctoral Researcher at the Max Planck Institute for Informatics (2022-2024). His academic journey includes postdoctoral positions at the University of California, Berkeley (2020-2022) and Bar-Ilan University, Israel (2019-2020). Dr. Kociumaka received his PhD in Computer Science from the University of Warsaw in 2019, with a thesis titled Efficient Data Structures for Internal Queries in Texts under the supervision of Professor Wojciech Rytter. He also completed both his BSc and MSc in Computer Science at the University of Warsaw between 2009 and 2014. His research focuses on string algorithms , particularly sequence similarity measures , approximate pattern matching , lossless data compression , and text indexing data structures . He approaches string problems from multiple perspectives including fine-grained complexity, dynamic algorithms, streaming, sketching, sublinear algorithms, and quantum computing. His work bridges theoretical computer science with practical applications in text processing and bioinformatics. Analysis of his recent publications reveals a strong emphasis on edit distance algorithms, pattern matching techniques, and data compression methods. His work demonstrates increasing sophistication in handling complex string problems with optimal time and space complexity, with growing interest in quantum computing applications for string processing. Presburger Award (2025) Cor Baayen Award (2021) Witold Lipski Prize (2018) Dr. Kociumaka serves on program committees for major theoretical computer science conferences including STOC, FOCS, SODA, and ICALP. He is also on the editorial board of Information Processing Letters and served as a guest editor for a special issue of SIAM Journal on Computing related to STOC 2024. His professional activities demonstrate significant leadership in the theoretical computer science community, particularly in the subfield of string algorithms and combinatorial pattern matching.