Assistant Professor,

Electrical & Computer Engineering; and

the Center for Neural Basis of Cognition

B-202 Hamerschlag Hall

Carnegie Mellon University

Ph: (412) 268-3644

pgrover at andrew dot cmu dot edu

Broadly, I am interested in an understanding of information that goes beyond just communication. Our lab seeks to attain this understanding through a mix of thought and laboratory experiments. Current topics of interest include fundamental and practical understanding of circuits for processing and communicating information; flow of information in neuronal systems; and understanding information and its use by exploring the union of control and communication.

*Our new Lab Webpage is up!* We are looking for 1-2 undergraduate students, 1-2 MS students, and 1-2 Ph.D. students. Drop me an email if you're interested!

Postdoctoral researcher (2011-12) in Electrical Engineering, Stanford University.

PhD, UC Berkeley, Dec 2010.

B. Tech, M.Tech, IIT Kanpur ('03, '05), Schooling: Vidyashram, Jaipur

You can find my CV here.

*Do consider submitting to the JSAC special issue on Wireless Comm via Energy Harvesting and Wireless Power!
*

Postdoctoral researcher (2011-12) in Electrical Engineering, Stanford University.

PhD, UC Berkeley, Dec 2010.

B. Tech, M.Tech, IIT Kanpur ('03, '05), Schooling: Vidyashram, Jaipur

You can find my CV here.

Theoretical underpinnings and practical designs of “green” radios”

The goal is to

Conclusions derived from our “Node Model” and “Wire Model” are as follows:

- [Node model] There is a fundamental tradeoff between transmit and encoding/decoding power. When computational nodes dominate processing power, to minimize total power, one must fundamentally stay away from capacity.
- [Node model] Capacity-approaching LDPC codes optimize over transmit power, but require large decoding power. Regular LDPC codes are order-optimal in the Node Model.
- [Wire model] When wires dominate the circuit power consumption, the total power diverges to infinity significantly faster than that for the node model. Further, the optimal choice of transmit power also increases unboundedly as the error probability is lowered.

Our results have the potential to drastically reduce power consumed in short-distance wireless (e.g. 60 GHz band) and wired (e.g. multi-Gbps communication in data-centers) communication.

[ITW '07] Pulkit Grover,

[ISIT '09] Pulkit Grover and Anant Sahai,

[JSAC '11] Pulkit Grover, Kristen Ann Woyach and Anant Sahai,

[CISS '11] Pulkit Grover and Anant Sahai,

[ISIT '12] Pulkit Grover, Andrea Goldsmith and Anant Sahai.

[DAC '11] Karthik Ganesan and Pulkit Grover,

[SiPS '11] Karthik Ganesan, Pulkit Grover, and Jan Rabaey,

[Globecom '12] Karthik Ganesan, Yang Wen, Pulkit Grover, Andrea Goldsmith and Jan Rabaey,

Control and communication in cyber-physical systems”

The “observers” cannot act on the system, and therefore they communicate their observations to the “controllers.” The “controllers” cannot observe the state directly, and thus rely on the signals sent by the “observers” to decide on their actions. In a realistic control system, these simplified control agents may be extremely limiting. However, analytically, they have been simpler to understand because they disallow

The crux of this issue is captured in a deceptively simple problem called the Witsenhausen counterexample, which has been

[CDC '08] Pulkit Grover and Anant Sahai,

[IJSCC '10] Pulkit Grover and Anant Sahai,

[ITW '10] Pulkit Grover, Aaron B. Wagner and Anant Sahai,

[ConCom '09] Pulkit Grover, Anant Sahai and Se Yong Park,

[Allerton '09] Pulkit Grover, Se Yong Park and Anant Sahai,

[ISIT '10] Pulkit Grover and Anant Sahai,

[TAC '10 Sub.] Pulkit Grover, Anant Sahai and Se Yong Park,

PhD

UG/MS

The epithet “students” is unfair to all of the above who have taught me a lot during our collaborations.

My favorite picture.