The MIT Energy-Efficient Circuits and Systems Group led by Prof. Anantha Chandrakasan is involved with the design and implementation of various integrated systems ranging from Application of ICs for Health, Hardware Security, Lower Power Edge Computing, and High Frequency Electronics. Research spans across multiple levels of abstraction ranging from innovative new process technologies and circuit styles to architectures, algorithms, and software technologies. A key focus of this group is developing energy efficient integrated solutions for Internet of Things (IOT) devices
Our Research
The sheer number and diversity of IoT devices, along with their limited resources, makes IoT security a challenge quite different from securing traditional computing systems.
Research spans across multiple levels of abstraction ranging from innovative new process technologies and circuit styles to architectures, algorithms, and software technologies.
Our group’s approach to biomedical electronics starts with developing a deep understanding of physiological or biological processes, which leads to new insights on how to develop an energy-efficient implementation of the system.
In the News
Jan 08, 2026
The Committed to Caring (C2C) program recognizes the outstanding professors who extend this dedication beyond the classroom, nurturing resilience, curiosity, and compassion in a new generation of innovators. The latest cohort of C2C honorees exemplify these values, demonstrating the lasting impact that faculty can have on students’ academic and personal journeys.
https://news.mit.edu/2026/mit-faculty-committed-to-caring-0108
Jan 23, 2026
For a small number of promising graduate students, the IEEE Solid-State Circuits Society Predoctoral Achievement Award provides an honorarium as well as reimbursement of select expenses incurred by the awardee for attending the next International Solid-State Circuits Conference (ISSCC.)
https://sscs.ieee.org/membership/awards/predoctoral-achievement-award/
Oct 25, 2025
WiCAS BPA Winners
Title:A 23-µJ-per-frame Fully-Integrated U-Net-Based TinyML Processor for Real-Time and Autonomous Medical Image Segmentation
Authors: Zhiye Song (MIT), Ulkuhan Guler (Worcester Poly), and Anantha Chandrakasan (MIT)
https://2025.ieee-biocas.org/award-ceremony/
Chips and Systems
A 0.7 cm2 , 3.5 GHz, −31 dBm Sensitivity Battery-Free 5G Energy-Harvester Backscatterer With 20 s Cold-Start Wake-Up Time for IoT-Enabled Warehouses
Jun, 2023
A secure digital in-memory compute (IMC) macro with protections for side-channel and bus probing attacks
Jun, 2023
An energy-efficient neural network accelerator with improved resilience against fault attacks
Jun, 2023
12.5 A Packageless Anti-Tampering Tag Utilizing Unclonable Sub-THz Wave Scattering at the Chip-Item Interface
Jun, 2023
A Fully-Integrated Energy-Scalable Transformer Accelerator Supporting Adaptive Model Configuration and Word Elimination for Language Understanding on Edge Devices
Jun, 2023
Secure and stable wireless communication for an ingestible device
Jun, 2023