Victoria Kostina
About Me 

I joined Caltech as an Assistant Professor of Electrical Engineering in the fall of 2014. Previously, I worked as a postdoctoral researcher with Prof. Sergio Verdú. I completed my PhD at Princeton University in September 2013. I spent the spring of 2015 as a Research Fellow at Simons Institute for the Theory of Computing. I hold a Bachelor's degree from Moscow institute of Physics and Technology, where I was affiliated with the Institute for Information Transmission Problems of the Russian Academy of Sciences, and a Master's degree from University of Ottawa. My research interests lie in information theory, theory of random processes, coding, wireless communications, and control. I am particularly interested in fundamental limits of delaysensitive communications. 
Openings
I am looking for strong students and postdocs to join my research group in the fall of 2017.
Prospective students: I apologize I am unable to respond to all inquiries — please do apply online and mention my name as a possible research advisor. I supervise students from both the Electrical Engineering (EE) and the Computing and Mathematical Sciences (CMS) PhD programs.
Prospective postdocs: please apply through the Center for the Mathematics of Information (CMI) postdoctoral fellowship program and mention my name in the application.
Research
Preprints
 A. Marsiglietti and V. Kostina, "A lower bound on the differential entropy of logconcave random vectors with applications”, arXiv:1704.07766, Apr. 2017.
 V. Kostina and B. Hassibi, "Ratecost tradeoffs in control. Part I: lower bounds", arXiv:1612.02126, Dec. 2016.
 V. Kostina and B. Hassibi, "Ratecost tradeoffs in control. Part II: achievable scheme", arXiv:1612.02128, Dec. 2016.
Journal Articles
 V. Kostina, "Data compression with low distortion and finite blocklength", IEEE Transactions on Information Theory, accepted Jan. 2017.
 V. Kostina, Y. Polyanskiy and S. Verdú, "Joint sourcechannel coding with feedback", IEEE Transactions on Information Theory, accepted Dec. 2016.
 V. Kostina and S. Verdú, "Nonasymptotic noisy lossy source coding", IEEE Transactions on Information Theory, vol. 62, no. 11, pp. 61116123, Nov. 2016.
 V. Kostina, Y. Polyanskiy and S. Verdú, "Variablelength compression allowing errors", IEEE Transactions on Information Theory, vol. 61, no. 9, pp. 43164330, Aug. 2015.
 V. Kostina and S. Verdú, "Channels with cost constraints: strong converse and dispersion", IEEE Transactions on Information Theory, vol. 61, no. 5, pp. 24152429, May 2015.
 S. Loyka, V. Kostina, and F. Gagnon, "On convexity of error rates in digital communications", IEEE Transactions on Information Theory, vol. 59, no. 10, pp. 65016516, Oct. 2013.
 V. Kostina and S. Verdú, "Lossy joint sourcechannel coding in the finite blocklength regime", IEEE Transactions on Information Theory, vol. 59, no. 5, pp. 25452575, May 2013.
 V. Kostina and S. Verdú, "Fixedlength lossy compression in the finite blocklength regime", IEEE Transactions on Information Theory, vol. 58, no. 6, pp. 33093338, June 2012.
 V. Kostina and S. Loyka, "Optimum power and rate allocation for coded VBLAST: Instantaneous optimization", IEEE Transactions on Communications, vol. 59, no. 10, pp. 28412850, Oct. 2011.
 V. Kostina and S. Loyka, "Optimum power and rate allocation for coded VBLAST: Average optimization", IEEE Transactions on Communications, vol. 59, no. 3, pp. 877887, Mar. 2011.
 S. Loyka, V. Kostina, and F. Gagnon, "Error rates of the maximumlikelihood detector for arbitrary constellations: convex/concave behavior and applications", IEEE Transactions on Information Theory, vol. 56, no. 4, pp. 19481960, Apr. 2010.
 V. Kostina and S. Loyka, "On optimum power allocation for the VBLAST", IEEE Transactions on Communications, vol. 56, no. 6, pp. 9991012, June 2008.
Ph.D. Dissertation
 V. Kostina, "Lossy data compression: nonasymptotic fundamental limits", Ph.D. dissertation, Princeton University, Sep. 2013. Princeton Electrical Engineering Best Dissertation Award.
Conference Papers
 A. Marsiglietti and V. Kostina, "A lower bound on the differential entropy for logconcave random variables with applications to ratedistortion theory", in Proceedings 2017 IEEE International Symposium on Information Theory, Aachen, Germany, June 2017, to appear.
 V. Kostina and E. Tuncel, "The RateDistortion Function for Successive Refinement of Abstract Sources", in Proceedings 2017 IEEE International Symposium on Information Theory, Aachen, Germany, June 2017, to appear.
 M. Ebrahimi, F. Lahouti, V. Kostina, "Coded Random Access Design for Constrained Outage", in Proceedings 2017 IEEE International Symposium on Information Theory, Aachen, Germany, June 2017, to appear.
 P. Noorzad, M. Effros, M. Langberg, V. Kostina, "The Birthday Problem and ZeroError Channel Coding", in Proceedings 2017 IEEE International Symposium on Information Theory, Aachen, Germany, June 2017, to appear.
 A. Khina, G. Pettersson, V. Kostina, and B. Hassibi, "Multirate control over AWGN channels: an analog joint sourcechannel coding perspective”, in Proceedings 2016 IEEE Conference on Decision and Control, Las Vegas, NV, Dec. 2016.
 V. Kostina and B. Hassibi, “Ratecost tradeoffs in control”, in Proceedings 54th Annual Allerton Conference on Communication, Control and Computing, Monticello, IL, Oct. 2016.
 V. Kostina, “When is Shannon’s lower bound tight?”, in Proceedings 54th Annual Allerton Conference on Communication, Control and Computing, Monticello, IL, Oct. 2016.
 V. Kostina, Y. Peres, M. Z. Rácz, G. Ranade, “Ratelimited control of systems with uncertain gain”, in Proceedings 54th Annual Allerton Conference on Communication, Control and Computing, Monticello, IL, Oct. 2016.
 V. Kostina, "Data compression with low distortion and finite blocklength", in Proceedings 53rd Annual Allerton Conference on Communication, Control and Computing, Monticello, IL, Oct. 2015.
 V. Kostina, Y. Polyanskiy and S. Verdú, "Joint sourcechannel coding with feedback", in Proceedings 2015 IEEE International Symposium on Information Theory, Hong Kong, June 2015.
 V. Kostina, Y. Polyanskiy and S. Verdú, "Transmitting k samples over the Gaussian channel: energydistortion tradeoff", in Proceedings 2015 IEEE Information Theory Workshop, Jerusalem, Israel, Apr. 2015.
 V. Kostina and S. Verdú, "The output distribution of good lossy source codes", in Proceedings 2015 Information Theory and Applications Workshop, La Jolla, CA, Feb. 2015.
 V. Kostina, Y. Polyanskiy, and S. Verdú, "Variablelength compression allowing errors", in Proceedings 2014 IEEE International Symposium on Information Theory, Honolulu, HI, July 2014.
 V. Kostina and S. Verdú, "Nonasymptotic noisy lossy source coding", in Proceedings 2013 IEEE Information Theory Workshop, Seville, Spain, Sep. 2013.
 V. Kostina and S. Verdú, "Channels with cost constraints: strong converse and dispersion", in Proceedings 2013 IEEE International Symposium on Information Theory, Istanbul, Turkey, July 2013.
 S. Loyka, V. Kostina, and F. Gagnon, "Convexity of error rates in digital communications under nonGaussian noise", in Proceedings 2013 IEEE International Symposium on Information Theory, Istanbul, Turkey, July 2013.
 V. Kostina and S. Verdú, "To code or not to code: Revisited", Proceedings 2012 IEEE Information Theory Workshop, Lausanne, Switzerland, Sep. 2012, pp. 59.
 V. Kostina and S. Verdú, "Lossy joint sourcechannel coding in the finite blocklength regime", in Proceedings 2012 IEEE International Symposium on Information Theory, Cambridge, MA, July 2012, pp. 15531557.
 V. Kostina and S. Verdú, "A new converse in ratedistortion theory", Proceedings 46th Annual Conference on Information Sciences and Systems, Princeton, NJ, Mar. 2012, pp. 16.
 V. Kostina and S. Loyka, "Performance analysis of coded VBLAST with optimum power and rate allocation", in Proceedings 2011 IEEE International Symposium on Information Theory, Saint Petersburg, Russia, Aug. 2011, pp. 18511855.
 V. Kostina and S. Verdú, "Fixedlength lossy compression in the finite blocklength regime: discrete memoryless sources", in Proceedings 2011 IEEE International Symposium on Information Theory, Saint Petersburg, Russia, Aug. 2011, pp. 4145.
 V. Kostina, M. F. Duarte, S. Jafarpour, and R. Calderbank, "The value of redundant measurement in compressed sensing", in Proceedings 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Prague, Czech Republic, May 2011, pp. 36563659.
 V. Kostina and S. Verdú, "Fixedlength lossy compression in the finite blocklength regime: Gaussian source", in Proceedings 2011 IEEE Information Theory Workshop, Paraty, Brazil, Oct. 2011, pp. 457461.
 S. Loyka, F. Gagnon, and V. Kostina, "Error rates of capacityachieving codes are convex", in Proceedings 2010 IEEE International Symposium on Information Theory, Austin, TX, June 2010, pp. 325329.
 A. Lorbert, D. Eis, V. Kostina, D. M. Blei, and P. J. Ramadge, "Exploiting covariate similarity in sparse regression via the pairwise elastic net", in Proceedings 13th International Conference on Artificial Intelligence and Statistics, vol. 9, Chia Laguna, Sardinia, Italy, May 2010, pp. 477484.
 S. Loyka, V. Kostina, and F. Gagnon, "Bit error rate is convex at high SNR", in Proceedings 2009 IEEE International Zurich Seminar on Communications, ETH Zurich, Switzerland, Mar. 2010, pp. 4144.
 V. Kostina and S. Loyka, "Optimum power allocation for coded VBLAST", in Proceedings 2009 IEEE International Conference on Communications, Dresden, Germany, June 2009.
 V. Kostina and S. Loyka, "Performance analysis of VBLAST with optimum power allocation", in Proceedings 2007 IEEE Global Telecommunications Conference, Washington, DC, Nov. 2007, pp. 15081513.
 S. Loyka, V. Kostina, and F. Gagnon, "Symbol error rates of maximumlikelihood detector: Convex/concave behavior and applications", in Proceedings 2007 IEEE International Symposium on Information Theory, Nice, France, June 2007, pp. 25012505.
 V. Kostina and S. Loyka, "Transmit power allocation for the VBLAST algorithm", in Proceedings 23rd Queen's Biennial Symposium on Communications, Kingston, Canada, May 2006, pp. 165168.
 V. Kostina and S. Loyka, "On optimization of the VBLAST algorithm", in Proceedings 2006 IEEE International Zurich Seminar on Communications, ETH Zurich, Switzerland, Feb. 2006, pp. 110113.
Matlab Toolbox
 SPECTRE: Short Packet Communication Toolbox provides numerical routines to compute bounds and approximations for some popular channel and source models in finite blocklength information theory.
Teaching

EE 167: Introduction to Data Compression and Storage Spring 2017
The course will introduce the students to the basic principles and techniques of codes for data compression and storage. The students will master the basic algorithms used for lossless and lossy compression of digital and analog data and the major ideas behind coding for flash memories. Topics include the Huffman code, the arithmetic code, LempelZiv dictionary techniques, scalar and vector quantizers, transform coding; codes for constrained storage systems. Prerequisites: Ma 3 or ACM 116. 
EE/Ma/CS 127: ErrorCorrecting Codes Winter 2016, Winter 2017
Prerequisites: Ma 2. This course develops from first principles the theory and practical implementation of the most important techniques for combating errors in digital transmission or storage systems. Topics include algebraic block codes, e.g., Hamming, BCH, ReedSolomon (including a selfcontained introduction to the theory of finite fields); and the modern theory of sparse graph codes with iterative decoding, e.g., LDPC codes, turbo codes. The students will become acquainted with encoding and decoding algorithms, design principles, and performance evaluation of codes. 
EE 120: Topics in Information Theory Spring 2016
This class introduces information measures such as entropy, information divergence, mutual information, information density from a probabilistic point of view, and discusses the relations of those quantities to problems in data compression and transmission, statistical inference, language modeling, game theory, and control. Topics include information projection, data processing inequalities, sucient statistics, hypothesis testing, singleshot approach in information theory, large deviations. Prerequisites: undergraduate calculus and probability; desirable but not required: EE 126. 
EE 150: Nonasymptotic Information Theory Fall 2014
Delayconstrained theory of information: singleshot results, information spectrum methods. Informationtheoretic limits for sources and channels with memory and/or general alphabets. Advantages of variablelength, feedback, and joint sourcechannel coding in the nonasymptotic regime. Error exponents, source, and channel dispersion. Prerequisite: EE/Ma 126.
Contact
Email:  vkostina AT caltech.edu 
Office:  Moore 162A 
Mailing address: 
1200 E California Blvd MC 13693 Pasadena CA 91125 
Phone number:  (626) 3951320 
Admin Assistant: 
Katie Pichotta Moore 162B (626) 3954715 
Last updated Apr. 27, 2017.