Aviral Shrivastava
School of Computing and Augmented Intelligence
Arizona State University
About Professor Aviral Shrivastava
Professor Aviral Shrivastava is a distinguished member of the faculty at Arizona State University, specifically within the School of Computing and Augmented Intelligence. Renowned for its innovative approach to computing education and research, Arizona State University is recognized as a leader in fostering interdisciplinary collaboration and cutting-edge technology development. The School of Computing and Augmented Intelligence excels in various research domains, with a strong emphasis on the integration of artificial intelligence and computing systems, creating an intellectually stimulating environment that encourages exploration and innovation among students and faculty alike.
🧬Research Focus
Professor Shrivastava's research primarily focuses on the intersection of compilers, machine learning accelerators, cyber-physical systems, and quantum computing, contributing significantly to the advancement of these fields. His work on hardware-software co-design and embedded systems aims to optimize machine learning models, making them efficient and resilient for deployment in real-world applications, including autonomous vehicles and connected systems. By exploring novel techniques for reliability-aware computing and defending machine learning models against adversarial attacks, Professor Shrivastava's research is at the forefront of developing practical solutions for complex challenges in the rapidly evolving technological landscape.
🎓Student Fit & Career
Graduate students who thrive under Professor Shrivastava's mentorship are typically those with a strong foundation in computer science, electrical engineering, or related fields, paired with a keen interest in machine learning and system design. Ideal candidates are intellectually curious, innovative, and eager to tackle real-world problems through advanced research. Pursuing graduate research in his lab can lead to diverse career paths, including positions in academia, industry research and development, or specialized roles in emerging technology sectors, where they can apply their skills in compilers, machine learning systems, and cyber-physical systems.
Research Areas
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