Misael Alpizar Santana
Papers
3
Total Citations
19
H-Index
3
About
Misael Alpizar Santana is a researcher working at the intersection of autonomous systems, formal methods, and deep learning, with a focus on making AI-driven systems safer and more reliable. His most significant contribution is the development of DeepDECS, a pioneering methodology for synthesizing correct-by-construction software controllers for autonomous systems that rely on deep neural network (DNN) classifiers for perception and decision-making. This work addresses one of the most pressing challenges in modern robotics and autonomy: bridging the gap between the impressive empirical performance of deep learning and the rigorous safety guarantees demanded by real-world deployment. DeepDECS has accumulated 13 citations across its 2022 and 2024 iterations, reflecting growing interest from the formal methods and autonomous systems communities. Alpizar Santana has also made notable contributions to multi-robot systems research, particularly through model-driven design space exploration approaches that help engineers navigate the complexity of deploying robot teams for demanding missions. With work spanning controller synthesis, simulation-based design, and safety verification, his research provides valuable foundations for students and practitioners seeking to build trustworthy autonomous systems in increasingly complex environments.
Research Focus
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Top Papers
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