Fabio Somenzi is affiliated with the University of Colorado Boulder in the United States. Their research primarily spans the field of Computer Science, with notable contributions across 53 publications. Within this broad discipline, they focus heavily on subfields including Artificial Intelligence, Computational Theory and Mathematics, Software, Molecular Biology, and Information Systems.
The scientist has contributed to various topics, most prominently Reinforcement Learning in Robotics and Formal Methods in Verification. Other areas of work include Evolutionary Algorithms and Applications, Software Testing and Debugging Techniques, Software Reliability and Analysis Research, Model-Driven Software Engineering Techniques, and Machine Learning and Algorithms.
Recent publications by Fabio Somenzi demonstrate ongoing work related to reinforcement learning and formal methods. Selected papers include:
The scientist frequently publishes in venues such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, Leibniz-Zentrum für Informatik (Schloss Dagstuhl), Formal Aspects of Computing, and IEEE Open Journal of Control Systems.
Fabio Somenzi collaborates with several researchers who appear regularly as co-authors. Notable frequent collaborators include Ashutosh Trivedi, Mateo Perez, Ernst Moritz Hahn, Sven Schewe, and Dominik Wojtczak, with collaboration counts ranging from 22 to 34 joint works.
R. I. Bahar;E. A. Frohm;C. M. Gaona;G. D. Hachtel
Robert K. Brayton;Gary D. Hachtel;Alberto L. Sangiovanni-Vincentelli;Fabio Somenzi
R. Iris Bahar;Erica A. Frohm;Charles M. Gaona;Gary D. Hachtel
Gary D. Hachtel;Fabio Somenzi
E. Macii;M. Pedram;F. Somenzi
Fabio Somenzi;Roderick Bloem
Shipra Panda;Fabio Somenzi
Shipra Panda;Fabio Somenzi;Bernard F. Plessier
Kavita Ravi;Fabio Somenzi
G.D. Hachtel;E. Macii;A. Pardo;F. Somenzi
Roderick Bloem;Harold N. Gabow;Fabio Somenzi
H. Cho;G.D. Hachtel;F. Somenzi
Kavita Ravi;Fabio Somenzi
H. Cho;G. Hachtel;S.-W. Jeong;B. Plessier
R.K. Brayton;F. Somenzi
Hyunwoo Cho;Gary D. Hachtel;Enrico Macii;Bernard Plessier
June-Kyung Rho;G.D. Hachtel;F. Somenzi;R.M. Jacoby
Gary D. Hachtel;Mariano Hermida;Abelardo Pardo;Massimo Poncino
Ernst Moritz Hahn;Mateo Perez;Sven Schewe;Fabio Somenzi
Bwolen Yang;Randal E. Bryant;David R. O'Hallaron;Armin Biere
Kavita Ravi;Kenneth L. McMillan;Thomas R. Shiple;Fabio Somenzi
If you think any of the details on this page are incorrect, let us know.
Exploring your education and career options in Computer Science starts with choosing the right college programs. Many universities offer flexible online formats that let you work while you study, opening up more pathways than ever before.
If you’re looking for advancement without a long time commitment, consider programs ranked among the easy masters degrees. These allow professionals to quickly boost credentials and specialize in areas like data science, artificial intelligence, or cybersecurity.
For those interested in reaching the highest academic levels, there are more options for cheap doctoral programs online. These can lead to careers in academia, research, or industry leadership—without the financial burden of traditional programs.
If time is a key factor, look for accelerated doctoral programs in education online. Many of these can be completed in a shorter period, allowing you to fast-track your career goals while balancing other commitments.
Sun Yat-sen University
University of Zaragoza
National Institute of Genetics
Toyo University
Frederick National Laboratory for Cancer Research
Ludwig-Maximilians-Universität München
Stanford University
Leiden University Medical Center
Northwestern University
Johns Hopkins University
IBM (United States)
George Mason University
Institute for Information Transmission Problems
University of Eastern Finland
Wageningen University & Research
University of California, Davis
