Anand D. Sarwate
A. Walter Tyson Assistant Professor
Department of Electrical and Computer Engineering
Rutgers, The State University of New Jersey
Associate Member, Dept. of Statistics
Associate Member, Dept. of Computer Science
Associate Member, WINLAB
Affiliate Member, DIMACS
CoRE Building Rm. 517
Phone: +18484458516
Email: anand.sarwate@rutgers.edu
Office Hours (Fall 2017):
Monday 1011 (CoRE 503)
Wednesday 1112 (CoRE 503)
A. Walter Tyson Assistant Professor
Department of Electrical and Computer Engineering
Rutgers, The State University of New Jersey
Associate Member, Dept. of Statistics
Associate Member, Dept. of Computer Science
Associate Member, WINLAB
Affiliate Member, DIMACS
CoRE Building Rm. 517
Phone: +18484458516
Email: anand.sarwate@rutgers.edu
Office Hours (Fall 2017):
Monday 1011 (CoRE 503)
Wednesday 1112 (CoRE 503)
Recent news
 I am on a pretenure sabbatical at the Simons Institute for the Theory of Computing for the program on Data Privacy: Foundations and Applications during Spring 2019.

Recent Papers accepted/in press:
K. Nikolakakis, D. Kalogerias, A.D. Sarwate, Learning Tree Structures from Noisy Data, AISTATS 2019, to appear April 2019.
Baker et al., Decentralized Temporal Independent Component Analysis: Leveraging {fMRI} Data in Collaborative Settings, NeuroImage, February 2019.
H. Imtiaz, A.D. Sarwate, Distributed DifferentiallyPrivate Algorithms for Matrix and Tensor Factorization, IEEE Journal of Selected Topics in Signal Processing (JSTSP) December 2018.
K. Kalantari, L. Sankar, A.D. Sarwate, Robust PrivacyUtility Tradeoffs under Differential Privacy and Hamming Distortion, IEEE Transactions on Information Forensics and Security, November 2018.
Z. Shakeri, A.D. Sarwate, W.U. Bajwa, Identifiability of KroneckerStructured Dictionaries for Tensor Data, IEEE Journal of Selected Topics in Signal Processing (JSTSP) October 2018.  I have been named the A. Walter Tyson Assistant Professor for 2018.
 Kamalika Chaudhuri posted our tutorial from NIPS 2017 on Differentially Private Machine Learning: Theory, Algorithms, and Applications.
Some recent publications
Distributed learning and optimization
 B. Baker, A. Abrol, R.F. Silva, E. Damaraju, A.D. Sarwate, V.D. Calhoun, S.M. Plis, Decentralized Temporal Independent Component Analysis: Leveraging fMRI Data in Collaborative Settings, NeuroImage 186: pp. 557569, February 2019. [BibTeX entry]
 A. Lalitha, T. Javidi, A.D. Sarwate, Social Learning and Distributed Hypothesis Testing, IEEE Transactions on Information Theory 64(9): pp. 61616179, September 2018. [BibTeX entry]
 A. Bijral, A.D. Sarwate, N. Srebro, Data Dependent Convergence For Consensus Stochastic Optimization, IEEE Transactions on Automatic Control 62(9): pp. 44834498, September 2017. [BibTeX entry]
 M. Ghassemi, A.D. Sarwate, Distributed Proportional Stochastic Coordinate Descent with Social Sampling, Proceedings of the 53rd Annual Allerton Conference on Communication, Control, and Computing, pp. 1724, October 2015. [BibTeX entry]
Privacy
 H. Imtiaz, A.D. Sarwate, Distributed DifferentiallyPrivate Algorithms for Matrix and Tensor Factorization, IEEE Journal of Selected Topics in Signal Processing 12(6): pp. 14491464, December 2018. [BibTeX entry]
 D. Bittner, A.D. Sarwate, R. Wright, Using Noisy Binary Search for Differentially Private Anomaly Detection, Proceedings of the 2nd International Symposium on Cyber Security Cryptography and Machine Learning (CSCML 2018), jun 2018. [BibTeX entry]
 S. Xiong, A.D. Sarwate, N.B. Mandayam, Defending Against PacketSize SideChannel Attacks in IoT Networks, Proceedings of the 43rd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018), April 2018. [BibTeX entry]
 M. Ghassemi, A.D. Sarwate, R. Wright, Differentially Private Online Active Learning with Applications to Anomaly Detection, Proceedings of the 9th ACM Workshop on Artificial Intelligence and Security, pp. 117128, October 2016. [BibTeX entry]
 C. Huang, L. Sankar, A.D. Sarwate, Designing Incentive Schemes For PrivacySensitive Users, Journal of Privacy and Confidentiality 7(1): pp. 99127, March 2016. [BibTeX entry]
Machine learning
 K.E. Nikolakakis, D.S. Kalogerias, A.D. Sarwate, Predictive Learning on SignValued Hidden Markov Trees, ArXiV report number arXiv:1812.04700 [stat.ML], December, 2018. [BibTeX entry]
 Z. Shakeri, A.D. Sarwate, W.U. Bajwa, Identifiability of KroneckerStructured Dictionaries for Tensor Data, IEEE Journal of Selected Topics in Signal Processing 12(5): pp. 10471062, October 2018. [BibTeX entry]
 M. Ghassemi, Z. Shakeri, A.D. Sarwate, W.U. Bajwa, STARK: Structured Dictionary Learning Through Rankone Tensor Recovery, ArXiV report number arXiv:1711.04887 [stat.ML], November, 2017. [BibTeX entry]
 M. Ghassemi, N. Goela, A.D. Sarwate, Global Optimality in Inductive Matrix Completion, Proceedings of the 43rd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018), April 2018. [BibTeX entry]
 T. Hazan, F. Orabona, A.D. Sarwate, S. Maji, T. Jaakkola, High Dimensional Inference with Random Maximum APosteriori Perturbations, ArXiV report number arXiv:1602.03571 [cs.LG], February, 2016. [BibTeX entry]
 S. Song, K. Chaudhuri, A.D. Sarwate, Learning from Data with Heterogeneous Noise using SGD, ArXiV report number arXiv:1412.5617 [cs.LG], December, 2014. [BibTeX entry]
Information Theory
 G.R. Kurri, V.M. Prabhakaran, A.D. Sarwate, Coordination Using Individually Shared Randomness, ArXiV report number arXiv:1805.03193 [cs.IT], may, 2018. [BibTeX entry]
 Y. Zhang, S. Vatedka, S. Jaggi, A. Sarwate, Quadratically Constrained Myopic Adversarial Channels, ArXiV report number arXiv:1801.05951 [cs.IT], January, 2018. [BibTeX entry]
 Z. Shakeri, A.D. Sarwate, W.U. Bajwa, Identifiability of Kroneckerstructured Dictionaries for Tensor Data, IEEE Journal of Selected Topics in Signal Processing : to appear 2018. [BibTeX entry]
 Z. Shakeri, W.U. Bajwa, A.D. Sarwate, Minimax Lower Bounds on Dictionary Learning for Tensor Data, ArXiV report number arXiv:1608.02792 [cs.IT], August, 2016. [BibTeX entry]
 B.K. Dey, S. Jaggi, M. Langberg, A.D. Sarwate, The benefit of a 1bit jumpstart, and the necessity of stochastic encoding, in jamming channels, ArXiV report number arXiv:1602.02384 [cs.IT], February, 2016. [BibTeX entry]
Support
Some of my research is supported by grants
from generous agencies. Many thanks to them!
[NSF] SaTC1617849:
TWC: Small: PERMIT: PrivacyEnabled Resource Management for IoT Networks
(PI: Anand D. Sarwate, CoPI: Narayan B. Mandayam)
[Verisign] gift through DIMACS Center
to work on applied and theoretical privacy
(PIs: Rebecca Wright, Anand D. Sarwate)
[DHS] through CCICADA Center:
DPAD: Differentially Private Anomaly Detection
(PIs: Rebecca Wright, Anand D. Sarwate)
[DARPA] Brandeis,
subcontract with Galois, Inc.:
Jana: Ensuring Secure, Private and Flexible Data Access
(PI: David Archer (Galois)  subaward to Rutgers: Rebecca Wright (PI), CoPIs: Anand D. Sarwate, David Cash)
[NSF] CCF1525276:
CIF: Small: Active data screening for efficient feature learning
(PI: Waheed Bajwa, CoPI: Anand D. Sarwate)
[NIH] 1R01DA04048701A1:
COINSTAC: Decentralized, Scalable Analysis of Loosely Coupled Data
(PI: Vince Calhoun (MRN)  subaward to Rutgers: Anand D. Sarwate (PI))
[NSF] CCF1453432
CAREER: Privacypreserving learning for distributed data
(PI: Anand D. Sarwate)
[NSF] CCF1218331/CCF1440033:
CIF: Small: Collaborative Research: Inference by social sampling
(PI: Anand Sarwate)