Meet Our Innovators
Sudeep Pasricha, PhD
Professor, Chair of Computer Engineering; Director of Embedded, High Performance, and Intelligent Computing (EPIC) Lab
Areas of Collaborative Interest
- Hardware-software co-design and machine learning for embedded and IoT systems in areas including automotive, medical, wearable, and mobile computing
- Machine learning and electronic design automation (EDA) tools for VLSI and manycore chip design
- Computer architecture with emerging computing technologies including 2.5D and 3D stacking, silicon photonics, and non-volatile memories
- Real-time and safety-critical computing
- High performance cloud/datacenter computing
- Licensing our technologies
The Embedded, High Performance, and Intelligent Computing (EPIC) Lab broadly focuses on software algorithms, hardware architectures, and hardware-software co-design for energy-efficient, fault-tolerant, real-time, and secure computing. These efforts target multi-scale computing platforms, including embedded and Internet of Things (IoT) systems, cyber-physical systems, mobile devices, and datacenters.
I am passionate about computing and have a desire to see technology improve lives and create a sustainable planet. I enjoy applying my expertise in software-driven optimization algorithms (including machine learning), hardware architecture modeling and design, and hardware-software co-design to various problems in embedded, IoT, mobile, cyber-physical, and cloud computing platforms. By creating systems that are energy-efficient, fault-tolerant, secure, and real-time compatible, my work aims to realize the computing platforms and technology use-cases of tomorrow.
- US7778815B2: Method for the fast exploration of bus-based communication architectures at the cycle-count-accurate-at-transaction-boundaries (CCATB) abstraction*
- US20200380121A1: Snooping invalidation and snooping detection device and method
- US20200125716A1: Hardware security for photonic communication architectures
*Assignee other than Colorado State University Research Foundation
Patent list generated using Google Patents
