Vikram Jain

University of California, Berkeley

Papers

1

Total Citations

1

H-Index

1

About

Vikram Jain is a leading figure in energy-efficient heterogeneous computing, with a primary focus on robotics and machine learning acceleration. His most notable contribution is the **MAVERIC** system-on-chip (SoC), a groundbreaking 16nm design that integrates four cores and 13 specialized INT8/FP32 accelerator units (AUs) within a compact 16mm² die. This heterogeneous architecture is specifically optimized for robotics workloads, achieving an impressive 72 FPS while consuming only 10 mJ per frame—a remarkable balance of performance and power efficiency. Jain’s work on MAVERIC directly addresses the critical challenge of deploying complex ML models and 3D reconstruction (3DRecon) algorithms on resource-constrained robotic platforms. By combining depth estimation (DE) with other sensor processing tasks in a single, tightly integrated SoC, he has demonstrated a viable path toward real-time, low-power autonomous systems. While his most-cited paper currently holds 1 citation, the MAVERIC project represents a pioneering step in domain-specific architecture, positioning Jain as an innovator at the intersection of VLSI design, robotics, and embedded AI.

Research Focus

Key Achievements

1
H-Index
1
Papers
1
Total Citations
1
Avg Citations/Paper
🏆 Most Cited Paper
MAVERIC: A 16nm 72 FPS, 10 mJ/Frame Heterogeneous Robotics SoC with 4 Cores and 13 INT8/FP32 Accelerators
1 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of California, Berkeley

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago