Student Information
Graduate StudentComputer Engineering (Computer Systems)
Ira A Fulton Engineering
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 techniques and infrastructures enable the efficient processing of critical applications such as machine/deep learning on hardware accelerators in an agile and sustainable manner. More specifically, his research develops compilation and mapping optimizations for accelerators, execution cost modeling and bottleneck characterization of accelerators, language for automated accelerator designs, efficient dense/sparse tensor computations, accelerator simulators, and exploration of hardware/software codesigns 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, Annual Days of NSF/Intel CAPA Research Center, Future Chips Forum, etc.). Read more about his vision paper on "Accelerator Design 2.0" here (Summary Talk) and a comprehensive literature survey on machine learning accelerator systems 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 Semiconductor Resarch Association's 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 digital design and verification for FPGA-based accelerators and ASICs. He is also experienced in piloting novel research projects and infrastructures, both 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 serves in various professional and community activities, including reviewing for top ACM/IEEE conferences and journals in his research areas (DAC, ESWEEK, RTSS, Sensors, TECS, TODAES), the program or organizing committee for these top conferences and workshops (ESWEEK, ASPLOS-LATTE), and various mentorship programs and activities.
- Ph.D. Candidate, School of Computing and AI, Ira A. Fulton Schools of Engineering, ASU - 2017-Present
- Master of Science, Computer Engineering, Arizona State University, 2016
- Bachelors of Engineering, Electronics and Communication Engineering, L. D. College of Engineering, Ahmedabad 2014
