Dennis Shasha is affiliated with New York University in the United States and has a research focus primarily within the field of Computer Science, contributing extensively to subfields such as Artificial Intelligence, Molecular Biology, Computer Networks and Communications, Computer Vision and Pattern Recognition, and Plant Science.
The scientist's research topics encompass a wide range of interests including Advanced Database Systems and Queries, Scientific Computing and Data Management, Graph Theory and Algorithms, Data Stream Mining Techniques, Machine Learning and Data Classification, Bayesian Modeling and Causal Inference, and Distributed Systems and Fault Tolerance.
Among recent publications, key works include:
Frequent co-authors in Shasha's research include Thomas Wies, Siddharth Krishna, Nisarg Patel, Gloria M. Coruzzi, and Manpreet S. Katari.
Publication venues where Dennis Shasha has contributed multiple works are diverse and include Communications of the ACM, arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), Algorithms, and BMC Bioinformatics.
In addition to journal articles, Shasha has published books with recognized academic publishers. These include Statistics is Easy (2021, Synthesis lectures on mathematics and statistics) and Automated Verification of Concurrent Search Structures (2021, Morgan & Claypool Publishers).
The scientist was recognized as an ACM Fellow in 2013 for contributions spanning a broad range of data management topics.
K. Zhang;D. Shasha
Jim Gray;Pat Helland;Patrick O'Neil;Dennis Shasha
Yunyue Zhu;Dennis Shasha
Theodore Johnson;Dennis Shasha
Françoise Fabret;H. Arno Jacobsen;François Llirbat;Joăo Pereira
Dennis Shasha;Jason T. L. Wang;Rosalba Giugno
Jinyuan Li;Maxwell Krohn;David Mazières;Dennis Shasha
S. Baruah;G. Koren;D. Mao;B. Mishra
Dennis Shasha;Marc Snir
Helena Galhardas;Daniela Florescu;Dennis Shasha;Eric Simon
Kaizhong Zhang;Rick Statman;Dennis Shasha
Alan Fekete;Dimitrios Liarokapis;Elizabeth O'Neil;Patrick O'Neil
Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur
Yunyue Zhu;Dennis Shasha
Yunyue Zhu;Dennis Shasha
Rabin Michael O;Shasha Dennis E
G. Koren;D. Shasha
Rodrigo A Gutiérrez;Rodrigo A Gutiérrez;Laurence V Lejay;Laurence V Lejay;Alexis Dean;Francesca Chiaromonte
R. Giugno;D. Shasha
Laks V. S. Lakshmanan;Raymond T. Ng;Dennis Shasha
Theodore Johnson;Dennis Shasha
If you think any of the details on this page are incorrect, let us know.
Choosing the right pathway in Computer Science often means exploring a range of online degree programs. Many students begin with an online associate degree, which can be completed quickly and provides foundational knowledge for entry-level tech positions or further study.
For those interested in the business side of technology, online business degree programs accredited by recognized institutions offer flexibility and credibility. These programs can open doors to management roles in IT and tech startups.
Cost is another key consideration. Students aiming to balance affordability and quality might look for the cheapest bachelor degree options in Computer Science. Completing a bachelor’s online can significantly reduce expenses while advancing your career prospects.
Finally, if engineering interests you, choosing an engineer degree online can provide specialized skills for high-demand tech sectors. Exploring these various online pathways lets you tailor your education to your career goals in the digital world.
Osaka University
The University of Texas at Austin
University of Gothenburg
Boston University
Tsinghua University
Helmholtz-Zentrum Berlin für Materialien und Energie
Technion – Israel Institute of Technology
Princeton University
Columbia University
University of British Columbia
International Agency For Research On Cancer
Johns Hopkins University
National and Kapodistrian University of Athens
Duke University
University of Idaho
University at Buffalo, State University of New York
