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Wojciech RytterView profile

Professor

• Design and analysis of computer algorithms
• Automata and formal languages
• Parallel algorithms
• +5 more

Wojciech Rytter is a full professor at the Institute of Informatics, Department of Mathematics and Informatics at the University of Warsaw, Poland, holding this position continuously since October 1971. His academic career includes significant international appointments as full professor at New Jersey Institute of Technology (2002-2004), Liverpool University (1997-2002), and Bonn University (1994-1995), and as visiting professor at University of California, Riverside (1992-1993) and University of Warwick (1985-1986). He earned his MSc in 1971, PhD in 1975, habilitation in 1985, and was awarded the scientific degree of professor in 1997, all from Warsaw University. Professor Rytter's research focuses on the design and analysis of computer algorithms, with particular expertise in automata and formal languages, parallel algorithms, and text algorithms. His work spans efficient sequential and parallel algorithms, automata theory, complexity of recognition and parsing of context-free languages, pattern matching, algorithmics of WWW, parallel combinatorial computing, graph-theoretic algorithms, and algorithmics of highly compressible objects. His theoretical contributions have practical applications in computational biology, bioinformatics, and text processing systems. His recent publications (2022-2025) demonstrate continued activity in string algorithms, particularly in pattern matching, string covers, and combinatorics on words, with a strong focus on theoretical computer science with applications in bioinformatics. 200 problems on automata, languages, computations (Cambridge University Press 2023) 125 Problems in Text Algorithms (Cambridge University Press, 2021) Jewels of Stringology (World Scientific, 2002) Fast parallel algorithms for matching problems in graphs (Oxford University Press 1998) Text algorithms (Oxford University Press 1994) Professor Rytter has collaborated extensively with researchers including Jakub Radoszewski, Tomasz Walen, Tomasz Kociumaka, and Maxime Crochemore. He is a member of the Academy of Europe (elected 2011, Informatics section) and has authored or co-authored more than 130 publications. He maintains an active research laboratory focused on string algorithms and combinatorics on words at the University of Warsaw.

• Algorithms
• Data Structures
• Pattern Matching
• +3 more

Simon J. Puglisi is a Professor in the Department of Computer Science at the University of Helsinki. His research focuses on algorithms, data structures, pattern matching, and data compression, with applications in bioinformatics and genomics. He has collaborated extensively with researchers in the field, including Travis Gagie, Juha Kärkkäinen, and Andrew Turpin. His work spans theoretical computer science and practical applications in genomic data processing and efficient indexing techniques. Key research interests include genome sequencing algorithms, efficient compression methods (e.g., Lempel-Ziv and relative Lempel-Ziv), and the development of succinct data structures for handling large genomic datasets. His contributions to suffix arrays, wavelet trees, and de Bruijn graphs have advanced computational methods in bioinformatics and information retrieval. Puglisi's articles frequently address challenges in text indexing, error correction in short-read sequencing, and optimizing algorithms for scalability. He is known for his work on self-indexing techniques and the SHREC error correction method for genomic data. His research bridges theoretical algorithm design with real-world applications in high-throughput sequencing and large-scale data management.

• Algorithms on strings
• Formal language theory
• Bioinformatics
• +3 more

Chiara Epifanio is a researcher (INFO-01/A) at the University of Palermo , based in the Department of Mathematics and Computer Science . She holds regular office hours on Tuesdays 14:30–17:00 in Room 104, first floor, Via Archirafi 34, and can be reached at chiara.epifanio@unipa.it . Over the past fifteen years she has designed and taught a diverse portfolio of courses spanning Programming , Bioinformatics , Advanced Programming , Teaching Methodologies and Techniques for Computer Science and Pattern Discovery for Life Sciences . These offerings serve degree programmes in Mathematics, Computer Science, Statistics & Data Science, and the recently launched curricula in Data, Algorithms & Machine Intelligence and Computer Science & Artificial Intelligence . Her research lies at the intersection of combinatorics on words , string algorithms , and bioinformatics . She has made sustained contributions to the design of alignment-free distances for biological data, the theory of Sturmian words and their associated graphs, suffix automata tolerant to mismatches, and compact data structures such as linear-size suffix tries. The work repeatedly draws on deep results from formal language theory, automata theory, and discrete mathematics to solve practical problems in sequence analysis. Publications trend: From 2004 onward she has produced a steady stream of peer-reviewed articles that move from foundational combinatorial results on Sturmian words and critical factorization theorems toward application-driven studies on approximate string matching and genomic data mining. A marked acceleration is visible in the 2023 publications addressing k-Hamming and k-edit distances, reflecting current demands in large-scale biological data analytics. Scientific awards: None explicitly mentioned in the provided material. Advising & grants: No PhD or Master’s students are listed in the supplied pages, and no funded project descriptions are available. Laboratories & teams: While no specific lab is named, her teaching and research are embedded within the Department of Mathematics and Computer Science, which hosts groups in algorithms, discrete mathematics, and bioinformatics, and provides access to the university’s ATeN Center and other research infrastructures.

• Algorithms on strings
• Small-space algorithms
• Data structures
• +4 more

Tatiana Starikovskaya is an Assistant Professor (Maître de Conférences) in the Computer Science Department at École normale supérieure (ENS), Paris, France. She leads the PARSe project (ANR-20-CE48-0001) focusing on approximation and randomized string processing, and participates in AlgoriDAM (ANR-19-CE48-0016). Co-supervises PhD students T. El Ghazi and Gabriel Bathie Co-chaired CPM 2021; served on program committees for STACS, ESA, ICALP, and others Organized CPM summer school (2023) and 'New Horizons of Stringology' workshop (2024) Research Focus Her work centers on algorithms on strings , small-space algorithms , and streaming models , with applications in bioinformatics and data security. Recent research explores trade-offs between time/space complexity in pattern matching, wildcards, and error-tolerant string analysis. Publications Trends Her recent work spans streaming algorithms , compressed data processing , and approximate pattern matching , with collaborations on challenges like k-mismatch problems, Dyck edit distances, and language distance estimation. Education PhD in Mathematics, Lomonosov Moscow State University (2013) M.Sc. in Data Science (Moscow Institute of Physics and Technology/Yandex, 2009) M.Sc. in Mathematics, Lomonosov Moscow State University (2009)

• Theoretical Computer Science
• Algorithms
• Logic
• +3 more

Michael Soltys is an Adjunct Professor in the Department of Computing and Software at McMaster University. His work bridges theoretical computer science, algorithms, and practical applications in cybersecurity and education. Research interests include logic, circuit complexity, and pairwise comparisons. Publications span 2002–2021, with recent focus on cloud computing education, digital forensics, and graph theory. Active in academic service through editorial contributions (e.g., Foreword for Franco-Canadian workshop proceedings). His scholarly activity maps to subdisciplines such as Computer Systems Theory, Logic, Discrete Applied Mathematics, and Operations Research. Dr. Soltys' work on pairwise comparisons and clique covers provides foundational insights for decision systems and graph optimization. He has also contributed to cloud curriculum development and malware analysis frameworks. As an educator, he co-authored An Introduction to the Analysis of Algorithms (2018, 2012, 2009), a textbook exploring algorithmic foundations. Current affiliations include the McMaster Experts database, with collaborations across theoretical computer science and applied cybersecurity research.

• Bioinformatics
• Computational Biology
• Algorithms
• +4 more

Jarno Alanko is a Postdoctoral Researcher at the University of Helsinki within the Department of Computer Science . Specializing in algorithmic bioinformatics and computational genomics, he is affiliated with the Genome-scale Algorithmics research group led by Professor Veli Mäkinen. Research Interests: Bioinformatics algorithms String processing Genomic data structures Graph-based sequence representation Metagenomic analysis Space-efficient computing Notable Research Contributions: His work focuses on optimizing k-mer-based analyses through novel data structures like Finimizers and Eulertigs, improving sequence alignment efficiency, and developing graph indexing methods beyond Wheeler graphs. Recent publications in IEEE/ACM Transactions on Computational Biology and Bioinformatics and Algorithmica highlight his contributions. External Collaborations: Alanko has collaborated with institutions such as the Max Planck Institute for Molecular Cell Biology and Genetics during his 2017 academic visit. Contact: jarno.alanko@helsinki.fi | ORCID: 0000-0002-8003-9225

Milana GrbicView profile

Assistant Professor

• Chemistry
• Physics
• Computer Science
• +3 more

Dr. Milana Grbić is an Assistant Professor at the Faculty of Natural Sciences and Mathematics, University of Banja Luka. She is actively involved in academic and research activities across multiple disciplines, including Chemistry, Physics, Computer Science, and Education. Her roles include organizing preparatory classes for entrance exams, coordinating international projects like the Erasmus+ program, and contributing to events such as the Science Festival and Republic Physics Competition. Research interests span interdisciplinary fields, with a focus on bioinformatics (protein complex analysis, PPI networks), graph theory (Roman domination problems, Kneser graphs), and computational biology (sequence alignment, algorithm design). She also engages in environmental and public health studies, such as the impact of weather on disease spread and clustering of pandemic data. Dr. Grbić collaborates on projects like the ChemTeach Erasmus+ initiative for teacher training and the SMART ERA project for rural tourism innovation. She actively participates in university governance, including agreements with institutions like the Institute of Forensic Medicine and the Children’s Education Association “Mio Mondo” to enhance educational outreach. Her contributions include organizing workshops, conferences, and student engagement programs, emphasizing science communication and community resilience. Recent research trends highlight her expertise in algorithm development for biological networks, theoretical graph problems, and applied studies in pandemic analysis and environmental policy. Her work bridges academia and practical applications, fostering collaboration between universities, industries, and governmental bodies.

Francesco TosoniView profile

Research Fellow

• Lossless Data Compression
• String Indexing
• Big Data Analytics
• +4 more

Francesco Tosoni is a Research Fellow at the University of Pisa's Department of Computer Science, affiliated with the Acube Laboratory (A³), directed by Prof. P. Ferragina. He holds a PhD in Computer Science from the University of Pisa, completed in 2024, and an MSc in Computer Science and Networking from the University of Pisa and Sant’Anna School of Advanced Studies (2020). His research focuses on lossless data compression, string indexing, big data analytics, and energy-efficient algorithms. He has conducted collaborative work with the Software Heritage team and was a visiting researcher at the University of Chile in 2022. Awards include the Con.Scienze 2020 Best Thesis Award and recognition as the top graduate in his MSc program. Recent projects include developing compressed formats for matrices and trie structures, with applications in green computing and efficient storage systems. Education: PhD in Computer Science, University of Pisa (2024), advisors: P. Ferragina and G. Manzini MSc in Computer Science and Networking, University of Pisa & Sant’Anna School (2020) BSc in Computer and Electronic Engineering, University of Perugia Research Interests: Lossless data compression techniques, energy-efficient algorithms, matrix and trie compression, stringology, big data analytics, and urban mobility platforms. Recent work emphasizes environmental sustainability in computing through optimized compression formats. Key Contributions: Developed the CoCo-trie compression method for efficient string storage Proposed novel compressed formats enabling direct matrix operations without decompression Recipient of grants for urban mobility algorithms and software heritage projects Awards: Con.Scienze 2020 Best Thesis Award (MSc thesis) Best Graduate in MSc Computer Science and Networking (2018/19) Advising & Grants: Supervised Federico Ramacciotti's MSc thesis on compression techniques in key-value stores Recipient of a 2020 research grant on algorithms for urban mobility platforms Labs & Teams: Core member of the Acube Laboratory, collaborating with global teams such as the Software Heritage initiative and Prof. Gonzalo Navarro's group in Chile.

• Bioinformatics Algorithms
• Stringology
• Combinatorics
• +7 more

Jacqueline Daykin is an Honorary Research Fellow in the Department of Computer Science at Aberystwyth University. Her research focuses on stringology algorithms, particularly applied to bioinformatics and computational biology. She holds a Sêr Cymru II Fellowship and has expertise in combinatorics of partially ordered sets, Lyndon words, and the Burrows-Wheeler transform. Her work integrates these structural concepts with genomic sequence analysis and infectious disease applications. She actively participates in research communities like StringMasters and AlgoUK, and is affiliated with the Centre for Combinatorics on Words and Applications. Daykin's research interests span theoretical computer science, with emphasis on algorithm design for string processing, data compression, and pattern recognition. She has contributed to advancements in suffix arrays, V-order algorithms, and efficient computational methods for genomic data. Her interdisciplinary approach bridges mathematics, artificial intelligence, and bioinformatics. Professional memberships include the Institute of Mathematics and Applications and the Women's Engineering Society. Her academic background includes teaching in the USA, UK, and Africa, combined with career breaks for family. Though no specific grants or awards are listed, her active publication record (over 50 outputs) demonstrates sustained research impact. Collaborations span international institutions, reflecting her role in global computational research networks.

Neerja MhaskarView profile

Assistant Professor

• String Algorithms
• Algorithms and Data Structures
• Network Security
• +4 more

Neerja Mhaskar is an Assistant Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. She is currently accepting graduate students and maintains an active research group. Her office is located in ITB 220, and she can be reached at pophlin@mcmaster.ca. Her educational background includes a PhD in Computer Science from McMaster University (2016), a Master's degree in Engineering Science from Louisiana State University, and a Bachelor's degree in Mechanical Engineering from Jawaharlal Nehru Technological University Hyderabad, India. Dr. Mhaskar's research focuses on the design and analysis of efficient algorithms and data structures, with particular emphasis on string processing for applications in bioinformatics, network security, and data compression. She develops algorithms for pattern matching, secure network design, and big data analysis. Her work bridges theoretical computer science with practical applications in privacy and security, as well as computational biology. Her recent publications demonstrate a strong trend in string algorithms, especially in covering problems and indeterminate strings, with growing applications in network security and bioinformatics. Over the past decade, she has contributed to foundational stringology and expanded into network segmentation and protein sequence analysis. Dr. Mhaskar has not been mentioned to have received any scientific awards in the provided text. Dr. Mhaskar has successfully supervised multiple graduate students. Her current advisees include PhD candidates Shafigh Ashrafi, Hamed Hasibi, Nivetha Raj Pappuraj, and Amin Kashef, as well as Master's students Samkith Kishore Kumar Jain and Shutong Wu. Among her graduated students are Tieyun Zhang, Meng Wang, Chenge Liu, Zehong Wang, Hossein Dehghani, and Holly Koponen, who have gone on to work at companies such as Siemens Canada, Robinhood, and Robotic Assistance Devices, or pursued further studies.

Danny HuckeView profile

Researcher

• Data Compression
• Grammar-Based Compression
• Empirical Entropy
• +3 more

Danny Hucke is a researcher affiliated with the University of Siegen, Department of Electrical Engineering and Computer Science. His work focuses on advanced data compression techniques, algorithmic complexity, and formal verification of streaming systems. Education: PhD in Grammar-based compression for strings and trees (University of Siegen, 2019) Research Interests: Driven by challenges in grammar-based compression, empirical entropy metrics, and formal language processing in streaming environments, his research bridges theoretical computer science and practical algorithm design. Key areas include: Data Compression for Trees and Strings Sliding-Window Algorithms Circuit Complexity Algorithmic Entropy Analysis Scientific Contributions: His work has been recognized with a Best Paper Award at SPIRE 2016. Publications span top-tier venues like IEEE Transactions on Information Theory , ACM TOCT , and conferences including ICALP, STACS, and LATIN. Contact: Department of Electrical Engineering and Computer Science, University of Siegen, Hölderlinstrasse 3, D-57076 Siegen. Email: hucke@eti.uni-siegen.de . Phone: +49-271-740-3415. Office: Room H-A 7104. Collaborations: Conducted research within the group of Prof. Markus Lohrey, collaborating extensively with Moses Ganardi, Louisa Seelbach, and Eric Nöth.

Roberto GrossiView profile

Professor

• Algorithms and Data Structures
• Dynamic and External Memory Algorithms
• Algorithm Engineering
• +4 more

Roberto Grossi is a Professor of Algorithms and Data Structures at the University of Pisa's Dipartimento di Informatica. He is actively involved in editorial roles for journals like Theory of Computing Systems and RAIRO-Theoretical Informatics, and has served on program committees for conferences such as SWAT, IWOCA, ESA, FOCS, and SPIRE. His research focuses on algorithms, data structures, graph theory, and bioinformatics, with contributions to string processing, compressed data structures, and algorithm engineering. He advises Ph.D. students and collaborates on projects involving large-scale networks and community detection. Grossi has authored numerous publications, including works on clique enumeration, graphlet algorithms, and phylogenetic reconstruction. His teaching includes courses on Algorithm Design and Data Structures, and he maintains an active presence in academic networks through his research and editorial activities. Education: Not explicitly stated, but inferred from his role as a professor at a top Italian university. Research Interests: Dynamic algorithms, external memory methods, experimental algorithmics, pattern matching in strings and graphs. Grants/Awards: While no specific prizes are listed, his extensive publication record and editorial roles reflect sustained recognition in the field. Lab/Teams: Leads research groups focused on algorithmic foundations and applications, collaborating with international teams on projects like Zuckerli (compressed graph representations) and motif trie indexing. His work bridges theoretical computer science with practical applications in bioinformatics and network analysis.

Marni MishnaView profile

Professor

• Analytic Combinatorics
• Enumerative Combinatorics
• Algorithmic Solutions
• +5 more

Marni Mishna is a Full Professor in the Department of Mathematics at Simon Fraser University’s Faculty of Science. Her academic roles include Associate Dean, Equity, Diversity, and Inclusion (2023–2028) and PIMS Deputy Director (2019–2021). She has held visiting positions at institutions such as CNRS (France), LaBRI (University of Bordeaux), and the Fields Institute. Education: PhD in Mathematics (Université du Québec à Montréal, 2003), MSc in Pure Math (SFU, 2000), BMath (University of Waterloo, 1997). Her research spans analytic and enumerative combinatorics , focusing on generating functions , lattice paths , D-finite symmetric functions , and algorithmic solutions . She explores the intersection of combinatorics with art and design for mathematical communication. Recent articles analyze differential transcendence , Kronecker coefficients , and lattice path universality classes , emphasizing computational methods and asymptotic analysis. Her work often bridges graph theory , symmetric functions , and algebraic structures . She supervises students and postdocs in projects related to combinatorial theory , graph enumeration , and symmetric function applications . Her teaching includes advanced courses like MATH 443/743 (Combinatorics) and MATH 322 (Complex Analysis).

Ely PoratView profile

Associate Professor

• Algorithms
• Data Structures
• Streaming Algorithms
• +5 more

Ely Porat is an Associate Professor at the Department of Computer Science, Bar-Ilan University, where he has been since 2000. He holds visiting professorships at the University of Michigan and Tel Aviv University, and has worked at Google (Mountain View in 2007 and Tel Aviv in 2011). His academic contributions include redefining the BSc degree in Computer Science at Bar-Ilan University and significant involvement in teaching committees. Research Interests: Algorithms and Data Structures Streaming Algorithms Pattern Matching Coding Theory Compressed Sensing His work focuses on advancing efficient algorithms for data processing, with applications in information retrieval, signal processing, and bioinformatics. He has organized multiple conferences including Stringology (2009–2011), ICALP2011GT, and UM Coding. He has served on program committees for CPM, SPIRE, and ESA. Advising & Collaboration: Current advisees include Ariel Shiftan, Guy Feigenblat, and others. Former students include Ohad Lipsky and Klim Efremenko. He hosts short-term researchers from abroad and collaborates with institutions like Google and Weizmann Institute. Publications span FOCS , STOC , ICALP , and other top venues, emphasizing theoretical foundations and practical algorithmic solutions.

Zvi GalilView profile

Professor

• Algorithms
• Complexity Theory
• Cryptography
• +3 more

Zvi Galil is a distinguished academic and former Dean of Computing at Georgia Institute of Technology (2010-2019). He holds the title of Storey Chair and serves as Executive Advisor for Online Programs. His academic journey includes leadership roles at Columbia University (Fu Foundation School of Engineering Dean, 1995-2007) and Tel Aviv University (President, 2007-2009). He earned degrees in Applied Mathematics from Tel Aviv University and a PhD in Computer Science from Cornell University. Galil’s research focuses on algorithms, complexity theory, cryptography, and stringology. He has authored over 200 papers and edited 5 books, with contributions to graph algorithms, parallel computing, and data structures. He is a Fellow of the ACM and American Academy of Arts and Sciences, and a member of the National Academy of Engineering. His work has influenced fields like online education through initiatives like OMSCS (Georgia Tech’s Online Master of Science in Computer Science). Educations: BS and MS (summa cum laude), Applied Mathematics, Tel Aviv University PhD, Computer Science, Cornell University His research trends span dynamic graph algorithms, real-time string processing, and scalable graph isomorphism techniques. He has also contributed to foundational areas like suffix trees and text indexing. His awards include the Columbia Great Teacher Award (2009) for pedagogical excellence. Awards: ACM Fellow Member, American Academy of Arts and Sciences Member, National Academy of Engineering Columbia Society of Graduates Great Teacher Award Galil advises on online education programs and collaborates with the Algorithms and Randomness Center (ARC) at Georgia Tech. He has held editorial roles at major journals and advised Oxford University Press on computer science publications.