The Thesis Review
[43] Swarat Chaudhuri - Logics and Algorithms for Software Model Checking
Jun 28, 2022
Swarat Chaudhuri, an Associate Professor at the University of Texas, delves into the fascinating intersection of programming languages and machine learning. He discusses the evolution of formal verification and the integration of model checking within AI systems. The conversation highlights advancements in neurosymbolic programming, enhancing reliability in software. Swarat also provides insights on developing reusable modules and emphasizes the importance of practical contributions in research, especially in AI safety and real-world applications.
01:06:18
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Quick takeaways
- Swarat Chaudhuri's research emphasizes the distinction between formal reasoning in programming and the uncertainty inherent in real-world reasoning.
- Chaudhuri discusses the integration of machine learning with formal methods to enhance software verification and the development of neurosymbolic systems.
Deep dives
Evolution of Research Interests
Swarat Chaudhuri's journey into research began with early exposure to academia, influenced by his parents who were professors. Initially drawn to neural networks, he pivoted to formal methods after advice from a mentor, shaping the trajectory of his academic career. His internships and undergraduate thesis solidified his interest in formal verification, leading to his PhD at the University of Pennsylvania. Though he felt certain about his focus during his PhD, he later recognized that his career path has spanned a diverse range of topics within computer science.
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