Sunil Shukla
Papers
1
Total Citations
101
H-Index
1
About
Dr. Sunil Shukla is a leading researcher in the field of approximate computing, a transformative paradigm that trades precise computation for significant gains in energy efficiency and performance, particularly suited for data-intensive and cognitive applications. His seminal work, "Approximate Computing: Challenges and Opportunities" (2016), has garnered over 100 citations, serving as a foundational reference that systematically maps the landscape of approximation techniques. In this influential paper, Dr. Shukla demonstrates how multiple approximation methods can be synergistically applied to domains like data analytics, enabling systems to extract deep insights from vast datasets while dramatically reducing power consumption. His contributions have helped bridge the gap between theoretical approximation models and practical, real-world deployment, addressing critical challenges in error tolerance and quality of service. By pioneering frameworks that balance accuracy with efficiency, Dr. Shukla’s research is shaping the next generation of energy-aware computing systems, making him a key figure in advancing sustainable and scalable architectures for modern data-driven applications.
Research Focus
Key Achievements
Top Papers
- 1Approximate computing: Challenges and opportunities101 citations · 2016