Lalitha Sankar
Lalitha Sankar is an Associate Professor in the School of Electrical, Computer, and Energy Engineering at Arizona State University. She was an Assistant Professor at ASU from 2012 to 2016. Prior to that she was a Research Scholar in the Department of Electrical Engineering at Princeton University working with H. Vincent Poor. She was also a Science and Technology Teaching and Research Fellow supported by the Council on Science and Technology at Princeton University.
She graduated with a Ph.D from Rutgers University, where she worked with Narayan Mandayam while collaborating with Gerhard Kramer (then at Bell Labs). Prior to that, Sankar was a Senior Member of Technical Staff at AT&T Shannon Labs, Florham Park, NJ, where she worked on design, development and prototyping of next-generation wired and wireless systems such as multi-band software radios and DSL modems. This was preceded by a year developing signal processing algorithms for the first digital camera prototype developed at Polaroid Corporation Engineering R&D in Cambridge, MA. Lalitha has a master’s degree from the Department of Electrical Engineering at the University of Maryland, Baltimore County and a bachelor’s degree in engineering physics is from the Indian Institute of Technology, Bombay, India.
Lalitha Sankar is a recipient of the 2014 NSF CAREER award. She received the best paper award from the IEEE Globecom 2011 for her paper on side-information privacy with R. Tandon and H. V. Poor. For her doctoral work, she received the 2007-2008 Electrical Engineering Academic Achievement Award from Rutgers University. For a more detailed CV, please click here.
News
7/21/2020
A Doctoral Position is available in Synchrophasor Data Science
More details can be found here
Research interests
- Cyber-security, privacy, and the big data problem in the smart grid
- Privacy in Large Datasets (Databases), Smart Grid, Healthcare Records, Social Networks
- Game-theoretic models for Privacy
- Information Secrecy in Wireless Networks
- Network Information Theory
- Relaying and User-Cooperative Communications
- Resource Allocation for Wireless Networks
- Cooperative Game Theory as applied to Wireless Networks
Contact
Lalitha Sankar
Assistant Professor
Arizona State University
School of Electrical, Computer, and Energy Engineering
Engineering Research Center
551 E. Tyler Mall, Room 585,
Tempe, AZ 85281 [map]
Phone: 480-965-4953
lalithasankar@asu.edu
Publications & Patents
Discoveries related to the study the utility and privacy in databases.
Teaching
Overview of courses and topics taught at Arizona State University and as a Princeton CST Fellow.
Collaborators
Working together to take research to the next level.
FACT: Federated Analytics based Contact Tracing for COVID-19
Overview The spread of the Corona Virus Disease 2019 (COVID-19), a highly-infectious disease caused by a newly discovered coronavirus, has reached pandemic levels across the globe. As of April 28, 2020, over 3.1M people worldwide have been infected with almost 220k...
A Class of Parameterized Loss Functions for Classification: Optimization Tradeoffs and Robustness Characteristics
We analyze the optimization landscape of a recently introduced tunable class of loss functions called α-loss, α∈(0,∞], in the logistic model. This family encapsulates the exponential loss (α=1/2), the log-loss (α=1), and the 0-1 loss (α=∞) and contains compelling properties that enable the practitioner to discern among a host of operating conditions relevant to emerging learning methods. Specifically, we study the evolution of the optimization landscape of α-loss with respect to α using tools drawn from the study of strictly-locally-quasi-convex functions in addition to geometric techniques. We interpret these results in terms of optimization complexity via normalized gradient descent.
High-Dimensional Spatio-Temporal Data Science for a Resilient Power Grid: Towards Real-Time Integration of Synchrophasor Data
The potential real-time situational awareness enabled by phasor measurements has been impeded by the massive scale of the time-series PMU data and have limited its use to passive, post-event forensics. The Institute meets this need for PMU-based real-time decision-making by examining five critical problems: (i) ensure data quality against bad, missing, or stale data; (ii) exploit the fine granularity of PMU data to track real-time changes in network parameters; (iii) detect, identify, localize, and visualize oscillation and failure events; (iv) assess and visualize cybersecurity threats and countermeasures specific to PMUs; and (v) create synthetic PMU datasets for testing and validation.
A Verifiable Framework for Cyber-Physical Attacks and Countermeasures in a Resilient Electric Power Grid
Introduction The US represent 18% of the world consumption as of 2015. 3200 electric utility companies 17,000 power plants 800 GW peak demand 165,000 miles of high-voltage lines 140 million meters $ 1 trillion in assets Electric network ca be divided into three...
Game-theoretic Analysis of Cooperation in Wireless Networks
In large wireless networks, heterogeneous users with competing interests may not cooperate to share their resources without incentives. Using information rate as the incentive for every link in a network of multiple interfering links, we use coalitional game theory to...
Relay and User Cooperative Networks
While cooperation can increase diversity in wireless networks, the tradeoff at every node of using resources for self vs. cooperative transmissions can make dedicated relays desirable. In my doctoral work, I compare the diversity gains achieved by inter-user...
Network Information Theory
The capacity region of multi-terminal networks remains a long-standing open problem, with the exception of a few classes of networks. With increasing demand for wireless data networks, developing fundamental performance limits is both essential and imperative to...
Information Security in Relay Networks
In contrast to and in addition to the traditional link layer cryptographic schemes, a relay can exploit the noisy physical channel to assist in ensuring the secrecy of data packets from untrusted eavesdropping nodes. In [1], we develop optimal source and relay...
Fading Wireless Networks: Sum-Capacity and Resource Allocation
Wireless networks are characterized by two distinct features: fading and interference. Signal designs for wireless networks need to be optimized for channel variations for efficient allocation of radio resources. I develop optimal signal designs and scheduling...
Application of Information Theory to the Database Privacy Problem
Information technology and electronic communications have been rapidly applied to every sphere of human activity, including commerce, medicine and social networking. The concomitant emergence of myriad large centralized searchable data repositories has made "leakage"...
Two New Privacy Challenges in the Smart Grid : Information- and Game-theoretic Approaches
One of the hallmarks of the smart grid is a vastly expanded information collection and monitoring system using sensing, communication, and control technologies including GPS-synchronized phasor measurement units (PMUs) in the high voltage transmission networks and...