|I am an assistant professor in the Department of Computer Science and Department of Mathematics at the National University of Singapore, and an affiliate with the Institute of Data Science. I am also a recipient of the National Research Foundation (NRF) Fellowship.
Prior to joining, I was a post-doc in LIONS, EPFL (Sept. 2014 - Sept. 2017), and a PhD student at the University of Cambridge (Oct. 2011 - Aug. 2014).
My research interests are in the areas of information theory, machine learning, and high-dimensional statistics. Please see my research and publications pages for details.
- COM2 #03-46 (Comp. Sci.), S17 #07-01 (Maths)
- +65 6516 1179 (Comp. Sci.), +65 6516 2952 (Maths)
- "scarlett" followed by "@comp.nus.edu.sg"
- (June 2020) Paper The Generalized Lasso with Nonlinear Observations and Generative Priors uploaded to arxiv
- (June 2020) Survey monograph Information-Theoretic Foundations of Mismatched Decoding accepted to Foundations and Trends in Communications and Information Theory
- (June 2020) Paper A Fast Binary Splitting Approach to Non-Adaptive Group Testing accepted to RANDOM 2020
- (June 2020) Paper Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors accepted to ICML 2020
- (May 2020) Paper Information-Theoretic Lower Bounds for Compressive Sensing with Generative Models published in IEEE Journal on Selected Areas in Information Theory (JSAIT)
- (April 2020) Paper Improved Bounds and Algorithms for Sparsity-Constrained Group Testing (and ISIT version) uploaded
- (Feb. 2020) Paper A Characteristic Function Approach to Deep Implicit Generative Modeling accepted to CVPR 2020
- (Jan. 2020) Papers Tight Regret Bounds for Noisy Optimization of a Brownian Motion and On the All-Or-Nothing Behavior of Bernoulli Group Testing uploaded to arxiv
- (Jan. 2020) Paper Noisy Non-Adaptive Group Testing: A (Near-)Definite Defectives Approach accepted to IEEE Transactions on Information Theory
- (Jan. 2020) Papers Corruption-Tolerant Gaussian Process Bandit Optimization and Learning Gaussian Graphical Models via Multiplicative Weights accepted to AISTATS 2020
- (Dec. 2019) Survey monograph Group Testing: An Information Theory Perspective published in Foundations and Trends in Communications and Information Theory
- (Nov. 2019) Paper A MaxSAT-Based Framework for Group Testing accepted to AAAI 2020
- (Sept. 2019) Paper Learning Erdős-Rényi Random Graphs via Edge Detecting Queries accepted to NeurIPS 2019
- (July 2019) I have uploaded some tutorial slides on information-theoretic bounds for problems in statistics and machine learning
- (July 2019) Three papers presented at ISIT 2019: (i) Overlapping Multi-Bandit Best-Arm Identification; (ii) An Efficient Algorithm for Capacity-Approaching Noisy Adaptive Group Testing; (iii) A Recursive Cost-Constrained Construction that Attains the Expurgated Exponent
- (June 2019) Papers Noisy Adaptive Group Testing: Bounds and Algorithms and Generalized Random Gilbert-Varshamov Codes published in IEEE Transactions on Information Theory
- (April 2019) Paper Sublinear-Time Non-Adaptive Group Testing with O(k log n) Tests via Bit-Mixing Coding uploaded to arxiv
- (March 2019) Paper Cross-Sender Bit Mixing Coding accepted to Conference on Information Processing in Sensor Networks (IPSN)
- (Feb. 2019) Paper Performance of Group Testing Algorithms With Near-Constant Tests-per-Item published in IEEE Transactions on Information Theory
- (Jan. 2019) Paper Support Recovery in the Phase Retrieval Model: Information-Theoretic Fundamental Limits uploaded to arxiv
- (Dec. 2018) Paper Adversarially Robust Optimization with Gaussian Processes presented as a spotlight talk at NeurIPS 2018
- (Nov. 2018) I have been awarded the National Research Foundation (NRF) Fellowship for the project Robust Statistical Model Under Model Uncertainty
- (Oct. 2018) I have been awarded the NUS Early Career Research Award for the project Information-Theoretic Methods in Data Science
- (Aug. 2018) Tutorial article An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation uploaded, to appear in a book titled Information-Theoretic Methods in Data Science (expected 2019 publication)
- (July 2018) Paper Tight Regret Bounds for Bayesian Optimization in One Dimension presented at ICML 2018