I am an Assistant Professor in the Electrical and Computer Engineering Department at UW-Madison, with affiliated appointments in the Departments of Mathematics and Statistics. I am a fellow of the Grainger Institute for Engineering. My research interests lie in the areas of information theory, machine learning, and network science.
From 2015-2016, I was a postdoctoral fellow at the Warren Center for Network and Data Sciences at the University of Pennsylvania. I was hosted jointly by the Statistics and CIS departments. I completed my PhD in the EECS Department at UC Berkeley in 2015, where I was advised by Professor Venkat Anantharam.
I graduated with a Bachelor of Technology (B. Tech) degree in Electrical Engineering from IIT Bombay in 2010. I was advised by Professors Abhay Karandikar and Sibi Raj B Pillai. I also spent three exciting months at the Department of Information Engineering, Chinese University of Hong Kong, working with Professor Chandra Nair in 2009.
My office address is 4611 Engineering Hall. I can be reached by email at vjog at wisc dot edu.
Fall 2016: ECE 730, "Modern Probability Theory and Stochastic Processes"
Spring 2017: ECE 729, "Theory of Information Processing and Transmission"
Fall 2017: ECE 730, "Modern Probability Theory and Stochastic Processes"
Spring 2017: ECE 203, "Signals, Information, and Computation" (shadowing Prof. Barry Van Veen)
Fall 2018: ECE 203, "Signals, Information, and Computation"
- Adrian Tovar Lopez (Department of Mathematics)
- Jing Hao (Department of Mathematics, advised by Prof. Nigel Boston)
- Ankit Pensia (Department of Computer Sciences, co-advised with Prof. Po-Ling Loh)
- Jinnian Zhang (Department of Electrical and Computer Engineering)
- Bhumesh Kumar (Department of Electrical and Computer Engineering)
MS in Electrical and Computer Engineering
- Muni Sreenivas Pydi (co-advised with Prof. Po-Ling Loh)
Machine Learning and Signal Processing accelerated program
- To MLSP students on campus: Please email me if you would like to do your MLSP project at the intersection of Machine Learning and Medical Imaging.
- Yogesh Balaje Mahendran
- Generalization error bounds using the Wasserstein metric. Adrian Tovar Lopez and Varun Jog. (To be presented at ITW 2018.)
- Convexity of mutual information along the Ornstein-Uhlenbeck flow. Andre Wibisono and Varun Jog. (To be presented at ISITA 2018.)
- Graph-Based Ascent Algorithms for Function Maximization. Muni Pydi Sreenivas, Varun Jog, and Po-Ling Loh. (Submitted, February 2018.)
- Convexity of mutual information in the heat flow. Andre Wibisono and Varun Jog. ISIT 2018.
- Generalization bounds for noisy, iterative algorithms. Ankit Pensia, Varun Jog, Po-Ling Loh. ISIT 2018.
- An entropy inequality for symmetric random variables. Jing Hao and Varun Jog. ISIT 2018.
- A convolution inequality for entropy over Z_2. Varun Jog. ISIT 2017.
- Information and estimation in Fokker-Planck channels. Andre Wibisono, Varun Jog, Po-Ling Loh. ISIT 2017.
- Computing and maximizing influence in linear threshold and triggering models. Justin Khim, Varun Jog, Po-Ling Loh. NIPS 2016.
- Information-theoretic bounds for exact recovery in weighted stochastic block models using the Renyi divergence. Varun Jog, Po-Ling Loh. Allerton Conference, 2015.
- On the geometry of convex typical sets. Varun Jog, Venkat Anantharam. Best student paper award at ISIT 2015.
- On model misspecification and KL separation for Gaussian graphical models. Varun Jog, Po-Ling Loh. ISIT 2015.
- A geometric analysis of the AWGN channel with a (sigma, rho)-power constraint. Varun Jog, Venkat Anantharam. ISIT 2015.
- An energy harvesting AWGN channel with a finite battery. Varun Jog, Venkat Anantharam. ISIT 2014.
- Convex relative entropy decay in Markov chains. Varun Jog, Venkat Anantharam. CISS 2014.
- The entropy power inequality and Mrs. Gerber's lemma for groups of order 2^n. Varun Jog, Venkat Anantharam. ISIT 2013.
- An information inequality for the BSSC channel. Varun Jog, Chandra Nair. ITA 2010.
- Optimal rates for community estimation in the weighted stochastic block model. Min Xu, Varun Jog, and Po-Ling Loh. Submitted, 2017.
- Intrinsic entropies of log-concave distributions. Varun Jog, Venkat Anantharam. IEEE Transactions on Information Theory, 2017.
- Persistence of centrality in random growing trees. Varun Jog, Po-Ling Loh. Random Structures and Algorithms, 2017.
- Computationally efficient influence maximization in stochastic and adversarial models: Algorithms and analysis. Justin Khim, Varun Jog, Po-Ling Loh. Submitted, 2017.
- Analysis of centrality in sublinear preferential attachment trees via the Crump-Mode-Jagers branching process. Varun Jog, Po-Ling Loh. IEEE Transactions on Network Science and Engineering, 2016.
- A geometric analysis of the AWGN channel with a (sigma, rho)-power constraint. Varun Jog, Venkat Anantharam. IEEE Transactions on Information Theory, 2016.
- The entropy power inequality and Mrs. Gerber's lemma for groups of order 2^n. Varun Jog, Venkat Anantharam. IEEE Transactions on Information Theory, 2014.
- An information inequality and evaluation of Marton's inner bound for binary input broadcast channels. Yanlin Geng, Varun Jog, Chandra Nair, Vincent Zizhou Wang. IEEE Transactions on Information Theory, 2013.
- (10/18) I will speak at an invited session titled "Graph theory and machine learning" at Allerton Conference.
- (08/18) Congrats to Geoffrey Lau and Kamini Jodha for graduating with a Master's Degree in Machine Learning and Signal Processing! Geoffrey, Kamini, and Jinnian worked with General Electric Healthcare and Dr. Alan McMillan, and successfully completed their summer project of identifying anatomical boundaries in MR images using deep learning.
- (08/18) ML4MI pilot grant awarded! Thanks to the Department of Radiology and the Grainger Institute of Engineering for supporting my collaboration with Dr. Alan McMillan.
- (07/18) Thanks to NSF for funding my EAGER proposal with Po-Ling Loh (co-PI)!
- (06/18) Talk at IMS-APRM, Singapore.
- (05/18) I was a discussion leader representing the College of Engineering at the Wisconsin Institute for Healthcare Science & Engineering (WIHSE) annual conference.
- (05/18) I spoke at the UW Math Talent Search's Honors Day event! My talk was titled "Little bits of information".
- (04/18) I was a panelist at the IFDS student workshop to discuss "Collaborative Data Science Research: Trends and Advice."
- (04/18) Congratulations to Yogesh for winning the Hilldale Undergraduate/Faculty Research Fellowship! Yogesh will be collaborating with Prof. Dhavan Shah's group to analyze the spread of misinformation in social networks.
- (03/18) Probability and Combinatorics Workshop at Bellairs Research Institute, Barbados.
- (03/18) Three papers from our group accepted to ISIT 2018!
- (02-03/18) Visit to Isaac Newton Institute at Cambridge. Talks at INI, University of Cambridge, and Bristol University.
- (02/18) Talk at ITA 2018.
- Prof. Jiamian Hu and I will be co-organizing the TGIF Seminar series in Fall 2018
- I am co-organizing the Machine Learning for Medical Imaging (ML4MI) initiative at UW-Madison, along with Prof. Po-Ling Loh (ECE) and Prof. Diego Hernando (Departments of Radiology and Medical Physics)
- James Melbourne and I are guest editors for the special issue on entropy inequalities for the Entropy Journal