Genome Assembly Programming Challenge

Alexander S. Kulikov serves as a visiting professor at the University of California, San Diego, and a leading research fellow at the Steklov Institute of Mathematics in St. Petersburg. His academic journey includes earning his Ph.D. in 2009 and Dr.Sci. in 2017 from the St. Petersburg Department of Steklov Institute of Mathematics. His research focuses on algorithms for NP-hard problems and circuit complexity, with significant contributions to computational complexity theory and algorithm design. He has authored several influential educational resources, including "Learning Algorithms Through Programming and Puzzle Solving" and co-created major online courses on platforms like Coursera and edX. His teaching experience spans more than eight years, during which he has developed innovative approaches to algorithms education. Currently at JetBrains as a researcher, he continues to advance the field through his work on algorithmic problem-solving and computational complexity, while maintaining his academic connections through his visiting professorship at UCSD and research position at Steklov Institute.

Michael Levin serves as Chief Data Scientist at Yandex.Market, Russia's leading price comparison and online shopping service, while also maintaining a position as Lecturer in Computer Science at the National Research University Higher School of Economics since 2015. His academic excellence began at Moscow State University, where he earned his degree in mathematics and achieved both silver and bronze medals at the ACM ICPC World Finals as part of the university's team. His expertise in algorithms, machine learning, and data science has made him a prominent figure in both industry and education, leading to his role as an instructor for the University of California San Diego's online courses in algorithms and data structures, which have reached over 345,000 students worldwide. His teaching portfolio includes comprehensive courses in algorithmic design, graph algorithms, string processing, and advanced complexity theory, making him a influential figure in computer science education while maintaining his leadership role in one of Russia's largest tech companies.

Pavel Arkadevich Pevzner serves as the Ronald R. Taylor Professor of Computer Science at the University of California, San Diego, and director of the NIH Center for Computational Mass Spectrometry, where he has revolutionized the field of computational biology since 2000. After receiving his Ph.D. in mathematics and physics from the Moscow Institute of Physics and Technology, he completed postdoctoral work with Michael Waterman at USC, before establishing himself through positions at Penn State and USC. His groundbreaking research spans bioinformatics algorithms, genome rearrangements, DNA sequencing, and computational proteomics, leading to significant advances in genome assembly and antibiotics discovery. His academic excellence has been recognized through numerous prestigious honors, including the Howard Hughes Medical Institute Professorship (2006), ACM Fellowship (2010), ISCB Fellowship (2012), and the ACM Paris Kanellakis Theory and Practice Award (2018). As an educator, he has transformed bioinformatics education through innovative approaches, including the development of massive open online courses that have reached over half a million students, and authored influential textbooks including "Computational Molecular Biology: An Algorithmic Approach" and "Bioinformatics Algorithms: An Active Learning Approach"

Neil Rhodes serves as an adjunct lecturer in the Computer Science and Engineering department at the University of California, San Diego. With a strong background in software engineering, he previously worked as a staff software engineer at Google. Rhodes has extensive teaching experience, having instructed courses on Algorithms, Machine Learning, Operating Systems, and Software Engineering at both undergraduate and graduate levels. He has also contributed to summer programs aimed at incoming and transfer students at UCSD.Rhodes holds both a B.A. and M.S. in Computer Science from UCSD and has taught at Harvey Mudd College as well. He left the Ph.D. program at UC San Diego to co-found Palomar Software, where he spent fifteen years developing software and authoring books on software development. His diverse teaching portfolio includes advanced topics such as Data Structures and Algorithm Design, reflecting his commitment to bridging theoretical concepts with practical applications in computer science education.