Adaptive Computing and Embedded Systems (ACES) Lab
Adaptive Computing and Embedded Systems (ACES) Lab
June 2024: ACES Lab alumna, Dr. Bita Rouhani (PhD 2018 UCSD, Best ECE Dissertation Award), is a recipient of the DAC Under-40 Innovators Award 2024.
June 2024: ACES Lab graduate, Dr. Shehzeen Hussain, receives the 2024 UCSD Best Dissertation Award in ECE. Shehzeen’s outstanding thesis made foundational contributions to demystifying safe AI and developing efficient generative models.
Sept 2023: ACES Lab alumna, Dr. Azalia Mirhoseini starts her new job as an Assistant Professor of Computer Science at Stanford University. Her lab focuses on developing capable, reliable, and efficient AI systems for solving high-impact, real-world problems.
Jan 2023: ACES Lab alumna, Dr. Zahra Ghodsi starts her new job as an Assistant Professor of Electrical and Computer Engineering at Purdue University. Her lab focuses on building secure frameworks for emerging intelligent devices and applications, applied cryptography, AI, and systems.
ACES Lab's current research addresses several aspects of secure and efficient computing, with a focus on robust machine learning under resource constraints, hardware and system security, AI-based optimization, intellectual property (IP) protection, as well as cryptographically secure privacy-preserving computing.
Our lab has made foundational contributions to all of these domains, including invention of the concepts of logic obfuscation/logic locking for both sequential and combinational logic that enabled the first active unique control of chips post-silicon, novel statistical methods for assessing chip security, the first automated co-design of data/algorithm/software/hardware for energy-efficient and compact deep learning, invention of co-design methods for creation of low-overhead robust and safe AI, the first trigger inversion methodology for detection of AI poisoning attacks, creation of the first method for watermarking/tracing deep learning models and generative output and attestation on trusted platforms, AI-based generic solvers for combinatorial optimization with constraints, creation of physical proofs of provenance, as well as novel co-design and optimization of algorithm and hardware/software, including co-design with cryptographic constructs for privacy-preserving computing.
Our work has linked seemingly disparate fields of logic synthesis and cryptographically secure computing requiring Boolean logic/vector computing, creating many new opportunities for researchers and leading to practical methods for managing function nonlinearities in the ciphertext domain.
Principal Investigator:
Farinaz Koushanfar, Ph.D.
Professor, UCSD Electrical and Computer Engineering
4502 Franklin Antonio Hall
UC San Diego, MC 0407
9500 Gilman Dr
La Jolla, CA 92093-0407
Email: fkoushanfar@ucsd.edu
Phone: (858) 246-0251
Fax: (858) 534-2486
Admin assistant:
Ms. Wyn Hughes
Electrical and Computer Engineering
9500 Gilman Drive, MC 0407
Jacobs Hall, Room 2907
La Jolla, CA 92093-0407
Email: whughes@ucsd.edu
Phone: (858) 434-3294