Hi, I am Amrita Roy Chowdhury. I am a CRA/CCC Computing Innovation postdoctoral fellow at the University of California, San Diego and my advisor is Prof. Kamalika Chaudhuri. I completed my PhD from the University of Wisconsin-Madison under Prof. Somesh Jha. Before that, I obtained my Bachelor of Engineering in Computer Science from the Indian Institute of Engineering Science and Technology, Shibpur where I was awarded the President of India Gold Medal.
I am on the academic job market!
Materials: CV Research Statement Teaching Statement
I analyze, design and build systems that enable safe data analytics in a decentralized setting without ever "seeing'' the data. My research empower individuals with full-stack data privacy solutions that deliver functionally-rich systems that are not only provably private but also tailored to meet application-specific constraints, ensuring their seamless deployment in the real-world. I do this via principled exploration of the synergy between differential privacy and cryptography, exposing their rich and multi-faceted interconnections in both theory and practice.
Recent News
Dec 23: Our work on prompt sanitization for LLMs will be presented at PPAI '24.
Nov 23: I will be giving a talk at the security seminar at UPenn.
Nov 23: I will be giving a talk at the Naval Postgraduate School.
Oct 23: I will be serving on the program committee for SaTML'24 and EuroS&P'24.
Oct 23: I will be giving a talk at the EnCORE Institute student social.
Sept 23: Check out our white paper on the security risks of GenAI based on the discussions from our workshop!
Sept 23: I will be a panelist for the Rising Stars in Data Science information session.
Aug 23: I will be an Area Chair for WebConf'24.
July 23: I will be giving a talk at the PriSec-ML seminar.
June 23: I helped organize the GenAI Risks Workshop. Stay tuned for some exciting updates!
Old News
June 23: I will be serving on the program committee for TPDP'23.
May 23: I will be giving a talk at the UCSD security seminar.
April 23: I will be giving a talk at Google.
March 23: I will be giving a talk at the FLOW seminar.
Feb 23: I won the award for the best poster at ITA'23.
Feb 23: I will be giving a talk at the Naval Applications of Machine Learning workshop.
Jan 23: I will be serving on the program committee for FORC '23, CCS '23 and FAccT '23.
Dec 22: I will be giving a talk at Cisco Research.
Nov 22: ShadowNet will be appearing at IEEE S&P 2023. Check out our talk!
Oct 22: I will be giving a talk at Amazon.
Oct 22: I will be giving a talk at Tufts University.
Sept 22: I will be co-organizing the PPML workshop this year co-located with FOCS. See you there!
Aug 22: EIFFeL will be appearing at CCS, 2022. Check this video for a 2-min summary!
Aug 22: I will be giving a talk at UC Berkeley AI4ALL.
July 22: Our work on strengthening order preserving encryption with differential privacy will be appearing at CCS, 2022.
May 22: I will be serving on the program committee for the first ever IEEE Conference on Secure and Trustworthy Machine Learning (IEEE SatML, 2023). Submit all your best work!
Apr 22: I will be serving on the program committee for ICDE, 2023.
March 22: I will be serving on the program committee for IEEE S&P, 2023 and VLDB, 2023.
Jan 22: Our work on the privacy implications of shuffling will be appearing at ICLR, 2022.
Dec 21: I will be serving on the program committee for CCS, 2022.
Nov 21: I have been selected for UChicago Rising Stars in Data Science.
Oct 21: I have been selected for Rising Stars in EECS, MIT.
Oct 21: I will be serving on the program committee for PPAI, 2022.
July 21: I have been selected as a CRA/CCC Computing Innovation Fellow, 2021. I will be working with Prof. Kamalika Chaudhuri at UCSD.
May 21: I will be serving on the program committee for USENIX Security, 2022.
May 21: I will be serving on the program committee for TPDP. Please submit all your awesome work!
Apr. 21: Honored to be selected as a finalist for the Facebook Fellowship, 2021 (top 3.5% out of over 2000 students worldwide).
Apr. 21: I will be interning at Facebook AI Research, NYC under Laurens Van der Maaten.
Feb. 21: Our work on eTAP, a privacy-enhancing trigger-action-platform, will be appearing at IEEE S&P, 2021.
Oct. 20: Selected for Rising Stars in EECS, UC Berkeley.
Oct. 20: I will be giving a talk to the Cryptography Group at MSR, Redmond.
Sept. 20: Our work on Kalεido, a system for real-time privacy-preserving processing of eye-tracking data, will be appearing at USENIX Security, 2021.
Preprints
On the Reliability of Membership Inference Attacks, Amrita Roy Chowdhury*, Zhifeng Kong*, Kamalika Chaudhuri, *Equal Contribution, Code
Robustness of Locally Differentially Private Graph Analysis Against Poisoning, Amrita Roy Chowdhury*, Jacob Imola*, Kamalika Chaudhuri, *Equal Contribution
Per User Histogram in the Shuffle Model of Differential Privacy, Amrita Roy Chowdhury*, Jacob Imola*, Aashish Kolluri*, *Equal Contribution
Conference Publications
FairProof: Confidential and Certifiable Fairness for Neural Networks, Chhavi Yadav, Amrita Roy Chowdhury, Dan Boneh, Kamalika Chaudhuri, ICML 2024
ShadowNet: A Secure and Efficient System for On-device Model Inference, Zhichuang Sun, Ruimin Sun, Changming Liu, Amrita Roy Chowdhury, Somesh Jha, Long Lu, IEEE S&P 2023, Talk, Code
EIFFeL: Ensuring Integrity for Federated Learning, Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten, CCS 2022, Best Poster at ITA '23
Strengthening Order Preserving Encryption with Differential Privacy, Amrita Roy Chowdhury, Bolin Ding, Somesh Jha, Weiran Liu, Jingren Zhou, CCS 2022
Privacy Implications of Shuffling, Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha, ICLR 2022, Code
Data Privacy in Trigger-Action IoT Systems, Yunang Chen, Amrita Roy Chowdhury, Ruizhe Wang, Andrei Sabelfeld, Rahul Chatterjee, Earlence Fernandes, IEEE S&P 2021, Code
Kalεido: Real-Time Privacy Control for Eye-Tracking Systems, Jingjie Li, Amrita Roy Chowdhury, Younghyun Kim, Kassem Fawaz, USENIX Security 2021, Media Coverage
Cryptε: Crypto-Assisted Differential Privacy on Untrusted Servers, Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha, SIGMOD 2020, Code
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models, Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha, ICML 2020
Concise Explanations of Neural Networks using Adversarial Training, Prasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Somesh Jha, Xi Wu, ICML 2020
Prεεch: A System for Privacy-Preserving Speech Transcription, Shimaa Ahmed, Amrita Roy Chowdhury, Kassem Fawaz, Parmeswaran Ramanathan, USENIX Security 2020, Demo
PPU: Privacy-Aware Purchasing Unit for Residential Customers in Smart Electric Grids, Amrita Roy Chowdhury, Parmeswaran Ramanathan, VLSI Design 2018
LMAC: A Lightweight Message Authentication Code for Wireless Sensor Network, Amrita Roy Chowdhury, Sipra DasBit, IEEE GLOBECOM 2015
LOCHA: A Light-Weight One-way Cryptographic Hash Algorithm for Wireless Sensor Network, Amrita Roy Chowdhury, Tanusree Chatterjee, Sipra DasBit, ANT 2014
Other Peer-Reviewed Publications
Prεεmpt: Sanitizing Sensitive Prompts for LLMs, Amrita Roy Chowdhury, David Glukhov, Divyam Anshumaan, Prasad Chalasani, Nicolas Papernot, Somesh Jha, Mihir Bellare, PPAI Workshop '24
Per User Histogram in the Shuffle Model of Differential Privacy, Amrita Roy Chowdhury*, Jacob Imola*, Aashish Kolluri*, TPDP Workshop '23 and Usenix Security '23 Poster, *Equal Contribution
Forgeability and Membership Inference Attacks, Zhifeng Kong*, Amrita Roy Chowdhury*, Kamalika Chaudhuri, AISec Workshop, CCS '22, *Equal contribution
Strengthening Order Preserving Encryption with Differential Privacy, Amrita Roy Chowdhury, Bolin Ding, Somesh Jha, Weiram Liu, Zingren Zhou, TPDP Workshop, ICML '22
Robust Locally Differentially Private Graph Analysis, Jacob Imola*, Amrita Roy Chowdhury*, Kamalika Chaudhuri, TPDP Workshop, ICML '22, *Equal contribution
A Shuffling Framework for Local Differential Privacy, Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha , TPDP Workshop, ICML '21 and PPML Workshop, CCS '21
Local Inferential Privacy through Data Shuffling, Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha, SoCal ML & NLP Symposium '21
Cryptε: Crypto-Assisted Differential Privacy on Untrusted Servers, Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha, PriML Workshop, NeurIPS '19
Journal Paper
Identifying and Mitigating the Security Risks of Generative AI
Clark Barrett, Brad Boyd, Elie Burzstein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang (Alphabetical Order) Foundations and Trends in Privacy and Security, Vol. 6: No. 1, pp 1-52
Miscellaneous
5 completely unsolicited facts about me --
If Ι were to describe myself and my work in a single sentence, I would say "I am indistinguishable from an anthropomorphic squirrel, who has humbugged her way into the Bluε Stockings Sociεty, for a PPT adversary."
I have an inordinate and perfervid predilection for circumlocutory and highfalutin verbiage. QED.
I would be well-disposed to having a dispassionate disquisition on whether to pet a Portuguese man o' war or a Porpita porpita at 3:07 am in the morning.
I would feature in the Forbes Billionaires List if the unit of currency were Scoville heat units consumed.
I would tell you all about my thoughts on "Why we should care for the Encephalartos woodii?", but I'm afraid I have exhausted my privacy budget.
Contact
If you would like to know more about my work OR challenge me to a tongue-twister battle, then drop me an email at aroychowdhury@ucsd.edu .