Shail Dave is a final-year Ph.D. candidate, majoring in Computer Engineering, at the School of Computing and Augmented Intelligence (SCAI) since 2017. Before joining the doctoral program, he earned a master’s at ASU in Computer Engineering in 2016. He is currently affiliated with Compiler Microarchitecture Lab / Make Programming Simple Lab and Center for Embedded Systems, working with Prof. Aviral Shrivastava on “Agile and Sustainable, Accelerated Computing”.
Shail’s research aims at processing compute-intensive applications on hardware accelerators in a resource-efficient manner. In specific, it develops agile design tools and techniques for efficient accelerator designs, including for dense/sparse tensor computations of Machine/Deep Learning models with irregular/varying shapes. These include compilation and mapping optimizations, execution cost modeling and bottleneck characterization, and explorations of hardware/software codesigns, including through systematic heuristics and machine learning. His research is regularly published in and referred by the top ACM/IEEE conferences and journals in these domains (design automation, embedded systems, and computer architecture). His research has also been featured in premier forums (ARM Research Summits, NSF/Intel annual CAPA days, Future Chips Forum, etc.). Read more about his vision paper on “Accelerator Design 2.0” here (summary talk) and a comprehensive literature survey here. His research and vision has directly contributed to development and participation in highly competitive national projects and such project proposals (including projects funded by SRC AI Hardware program, NSF/Intel CAPA center) and a new topical course at ASU (on Topics in Machine Learning Accelerator Design).
Shail’s industry experiences include compiler optimizations for wide-scale commodity embedded systems, as well as RTL design and verification for FPGAs and ASICs. He also has experience in piloting novel research projects and infrastructuresboth in collaboration with expert industry/academic researchers and internships (Intel Parallel Computing Lab, ARM Research, MathWorks Research, Space Application Center–ISRO), especially for cutting-edge accelerator design and system stack development.
Shail is a recipient of several competitive honors and awards. He also regularly participates in various professional and community services, including reviewing for top conferences and journals in his research areas, the program or organizing committee for top conferences and workshops, and various mentorship programs and activities. Learn more at https://sites.google.com/view/shail.