Dmitri Pavlichin

Research Areas

Information theory and statistics. Estimation when the sample size is not large enough for classical techniques to perform well; Fluctuations of Markov chains and neutral genetic drift; Analogies between data compression and physical processes; Optimally symmetrizing probability distributions.

• • • Approximate profile maximum likelihood, Dmitri Pavlichin, Jiantao Jiao, and Tsachy Weissman. Journal of Machine Learning Research (JMLR) 2019 [paper].

    • Quantum channel capacities per unit cost, David Ding, Dmitri Pavlichin, and Mark Wilde. IEEE Transactions on Information Theory 2018 [paper].

    • Minimum power to maintain a nonequilibrium distribution of a Markov chain, Dmitri Pavlichin, Yihui Quek, and Tsachy Weissman 2018 [paper].

    • Chained Kullback-Leibler divergences, Dmitri Pavlichin and Tsachy Weissman. International Symposium on Information Theory (ISIT) 2016 [paper].

    • Nearest symmetric distributions, Dmitri Pavlichin. International Symposium on Information Theory (ISIT) 2016 [paper].

Data compression of genomic and tabular datasets.

• • • Compressing tabular data via pairwise dependencies, Dmitri Pavlichin, Amir Ingber, and Tsachy Weissman. Poster at Data Compression Conference (DCC) 2017 [paper].

    • The human genome contracts again, Dmitri Pavlichin, Golan Yona, and Tsachy Weissman. Bioinformatics 2013 [paper] (a new compression ratio record at the time).

Indexing and searching genomic data. Data structures and algorithms for indexing large, heterogeneous collections of genomic data, and making public genomic resources searchable in a common way.

• • • Profiling SARS-CoV-2 mutation fingerprints that range from the viral pangenome to individual infection quasispecies, Billy T. Lau, Dmitri Pavlichin, Anna Hooker, Alison Almeda, Giwon Shin, Jiamin Chen, ChunHong Huang, Benjamin A. Pinsky, HoJoon Lee, Hanlee P. Ji, 2020. In submission [paper].

    • Unique K-mer sequences for validating cancer-related substitution, insertion and deletion mutations, HoJoon Lee, Ahmed Shuaibi, John M. Bell, Dmitri Pavlichin, Hanlee P. Ji, 2020. In submission [paper].

    • Provisional patent Improved K-mer Storage and Retrieval for Next-Generation Sequencing, Hanlee P. Ji, HoJoon Lee, Tsachy Weissman, and Dmitri Pavlichin. Submitted in July 2020 [Stanford Office of Technology Licensing page]

Quantum optics and single molecule biophysics. Modeling, simulation, experimental data analysis, and engineering of small, noisy systems (ribozymes and quantum optical systems). Stochastic computing, an information-theoretic analysis of the proposed schemes, and how to systematically turn anything, say a pizza, into a communication channel.

• PhD Disssertation: Photonic circuits and probabilistic computing, Dmitri Pavlichin, 2014 [pdf].

• Photonic circuits for iterative decoding of a class of low-density parity-check codes, Dmitri Pavlichin and Hideo Mabuchi. New Journal of Physics, 2014 [paper].

• Specification of photonic circuits using quantum hardware description language, Nikolas Tezak, Armand Niederberger, Dmitri Pavlichin, Gopal Sarma, and Hideo Mabuchi. Phil. Trans. Royal Soc. A, 2012 [paper].

• Single Molecule Analysis Research Tool (SMART): an integrated approach for analyzing single molecule data, Max Greenfeld, Hideo Mabuchi, and Daniel Herschlag. PLoS One, 2012 [paper].

• Design of nanophotonic circuits for autonomous subsystem quantum error correction, Joseph Kerckhoff, Dmitri Pavlichin, Hamidreza Chalabi, and Hideo Mabuchi. New Journal of Physics 2011 [paper].

For a complete list of my publications see my CV or Google Scholar profile.