Farinaz Koushanfar
Professor
Builds secure and efficient embedded systems, including privacy-preserving and trustworthy machine learning hardware and protocols.
Farinaz Koushanfar's lab at UCSD works on efficient training & inference, accelerators, chips & architecture and trustworthy & safe ML. 48 papers since 2023, 18 at top venues, mostly DAC and CCS. 8 PhD students. 20 alumni. Applications close .
At a glance
- papers, 2023–2026
- 13/ year
- at T1 venues
- 38%
- PhD students
- 8
- MS students
- 0
- alumni listed
- 20
Papers by yearfrom DBLP, 2023–2026
- 6 papers2026 · T1 1 · collecting
- 7 papers2025 · T1 4
- 17 papers2024 · T1 5
- 18 papers2023 · T1 8
T1 venuesOtherVenues: DAC, CCS, ICCAD, NDSS, ICML
Research focuspaper titles that use each topic's words
- Efficient training & inference6 papers
- Accelerators, chips & architecture2 papers
- secure1 paper
- Trustworthy & safe ML0 papers
- embedded systems0 papers
Paper list
From DBLP.
20266 papers
- ISQEDAgentic AI for Chip Design Verification: Failure Modes, Metrics, and Coverage Closure (opens in a new tab)
- ACM Trans. Design Autom. Electr. Syst.AutoMarks: A GNN-based Automated Physical Design Watermarking Framework (opens in a new tab)
- ISQEDClosing the Loop: Overcoming the Tool-Feedback Gap in Agentic Hardware Design (opens in a new tab)
- STMEnsuring Privacy and Integrity in Dynamic Settings: Updatable Vector Commitments and Zero-Knowledge Sets (opens in a new tab)
- WWW (T1)PAC to the Future: Zero-Knowledge Proofs of PAC Private Systems (opens in a new tab)
- Trans. Mach. Learn. Res.Test-Time Adaptation for Unsupervised Combinatorial Optimization (opens in a new tab)
20257 papers
- SPEveGuard: Defeating Vibration-based Side-Channel Eavesdropping with Audio Adversarial Perturbations (opens in a new tab)
- ICCAD (T1)Gotta Hash 'Em All! Accelerating Hash Functions for Zero-Knowledge Proof Applications (opens in a new tab)
- IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.ICMarks: A Robust Watermarking Framework for Integrated Circuit Physical Design IP Protection (opens in a new tab)
- ICCAD (T1)Invited Paper: Optimizing Privacy-Preserving Primitives to Support LLM-Scale Applications (opens in a new tab)
- CICCKey, Value, Compress: A Systematic Exploration of KV Cache Compression Techniques (opens in a new tab)
- NDSS (T1)Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication Systems (opens in a new tab)
- CCS (T1)ZORRO: Zero-Knowledge Robustness and Privacy for Split Learning (opens in a new tab)
202417 papers
- ICCAD (T1)AMAZE: Accelerated MiMC Hardware Architecture for Zero-Knowledge Applications on the Edge (opens in a new tab)
- MLCADAutomated Physical Design Watermarking Leveraging Graph Neural Networks (opens in a new tab)
- Nat. Mac. Intell.Distributed constrained combinatorial optimization leveraging hypergraph neural networks (opens in a new tab)
- DAC (T1)EmMark: Robust Watermarks for IP Protection of Embedded Quantized Large Language Models (opens in a new tab)
- ACM Trans. Multim. Comput. Commun. Appl.FaceSigns: Semi-fragile Watermarks for Media Authentication (opens in a new tab)
- IEEE Des. TestIntellectual Property Protection of Deep-Learning Systems via Hardware/Software Co-Design (opens in a new tab)
- IEEE Trans. Emerg. Top. Comput.Near-Memory Computing With Compressed Embedding Table for Personalized Recommendation (opens in a new tab)
- USENIX Security (T1)REMARK-LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models (opens in a new tab)
- ACM Trans. Embed. Comput. Syst.Scalable Binary Neural Network Applications in Oblivious Inference (opens in a new tab)
- ICML (T1)SelfVC: Voice Conversion With Iterative Refinement using Self Transformations (opens in a new tab)
- IEEE Trans. Emerg. Top. Comput.SenseHash: Computing on Sensor Values Mystified at the Origin (opens in a new tab)
- IACR Cryptol. ePrint Arch.SoK: Model Reverse Engineering Threats for Neural Network Hardware (opens in a new tab)
202318 papers
- IEEE Trans. Inf. Forensics Secur.Abusing Commodity DRAMs in IoT Devices to Remotely Spy on Temperature (opens in a new tab)
- ACM J. Emerg. Technol. Comput. Syst.AccHashtag: Accelerated Hashing for Detecting Fault-Injection Attacks on Embedded Neural Networks (opens in a new tab)
- DAC (T1)AdaGL: Adaptive Learning for Agile Distributed Training of Gigantic GNNs (opens in a new tab)
- FPGAAdapting Skip Connections for Resource-Efficient FPGA Inference (opens in a new tab)
- ACM Trans. Embed. Comput. Syst.AdaTest: Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection (opens in a new tab)
- Pattern RecognitionAdversarial scratches: Deployable attacks to CNN classifiers (opens in a new tab)
- AllertonFederated Certainty Equivalence Control for Linear Gaussian Systems with Unknown Decoupled Dynamics and Quadratic Common Cost (opens in a new tab)
- DTRAPGALU: A Genetic Algorithm Framework for Logic Unlocking (opens in a new tab)
- CCS (T1)HELiKs: HE Linear Algebra Kernels for Secure Inference (opens in a new tab)
- CCS (T1)Lanturn: Measuring Economic Security of Smart Contracts Through Adaptive Learning (opens in a new tab)
- DSNReFace: Adversarial Transformation Networks for Real-time Attacks on Face Recognition Systems (opens in a new tab)
- NDSS (T1)RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compression (opens in a new tab)
Where alumni went20 listed
Apply to UCSDFall 2027
UCSD CSE Computer Science PhD
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- Single round
- Opens
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- English
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Not yet confirmed for this intake.
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