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Flavio du Pin Calmon

Assistant Professor

I am an Assistant Professor of Electrical Engineering at Harvard's John A. Paulson School of Engineering and Applied Sciences. Before joining Harvard I was a social good post-doctoral fellow at IBM Research in Yorktown Heights, New York. I received my Ph.D. in Electrical Engineering and Computer Science at MIT. My main research interests are information theory, inference, and statistics, with applications to privacy, fairness, machine learning, and communications engineering.

Research

My research has three intertwined goals: (i) develop theory and models that capture the fundamental limits of estimation and learning from data, (ii) construct fair and private learning algorithms with performance guarantees based on these limits, and (iii) use this methodology as a design driver for future information processing and content distribution systems. In order to achieve these goals I use theoretical tools from information theory, statistics, cryptography and machine learning.

I consider myself a scientist who is an engineer at heart, so I enjoy doing fundamental research that serves as a design driver for practical applications. I have a broad set of interests which include information theory, statistics, communications and optimization. You can find more details in the publications below.

Recent announcements

  • March, 2019 — Google Faculty Research Award.

    Ok Google, thank you so very much for your generous gift (see under "Machine Learning and Data Mining").

  • Dec, 2018 — NSF CAREER Award!

    I am very grateful for the support of the National Science Foundation for our research on information-theoretic foundations of fair machine learning (check out this GSAS feature). You can learn more details about the award at the Harvard SEAS website.

  • Nov, 2018 —IBM Open Collaborative Research Award.

    Thank you IBM!

  • Nov, 2018 —NVidia GPUs grant.

    Thank you NVidia for the two Titan XP GPUs awarded to our group.

  • April, 2018 —Lemann Brazil Research Fund Award.

    We are excited to organize a course on ML at FEEC/Unicamp in August 2019! You can find more details here.

  • Research Group

    I am very fortunate to work with an amazing group of students, post-docs, and visitors.
  • Hao Wang (PhD, G3)
  • Hsiang Hsu (PhD, G2)
  • Wael Alghmadi (PhD, G2)
  • Berk Ustun (CRCS Post-Doc)
  • Javier Zazo (CRCS Post-Doc)
  • Lisa Vo (Harvard College)
  • Filip Michalsky (ME in Computational Science & Engineering)
  • Claire (Zheng) Yang (ME in Computational Science & Engineering)
  • José Cândido Silveira Santos Filho (Visiting Faculty)
  • Papers

    Pre-prints

  • On the robustness of information-theoretic privacy measures and mechanisms,
    M. Diaz, H. Wang, F. P. Calmon, and L. Sankar
  • Privacy with estimation guarantees
    H. Wang, L. Vo, F. P. Calmon, M. Médard, K. R. Duffy, and M. Varia
  • Tunable measures for information leakage and applications to privacy-utility tradeoffs
    J. Liao, O. Kosut, L. Sankar, and F. P. Calmon
  • Deep Orthogonal Representations: Fundamental Properties and Applications
    H. Hsu, S. Salamatian, and F. P. Calmon
  • Hiding symbols and functions: New metrics and constructions for information-theoretic security
    F. P. Calmon, M. Médard, M. Varia, K. R. Duffy, M. M. Christiansen, and L. M. Zeger
  • 2019

  • Correspondence Analysis Using Neural Networks
    H. Hsiang, S. Salamatian, F. P. Calmon
    The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS).
  • 2018

  • Avoiding disparate impact with counterfactual distributions
    H. Wang, B. Ustun, F. P. Calmon
    NeurIPS Workshop on Ethical, Social and Governance Issues in AI.
  • Correspondence analysis of government expenditure patterns
    H. Hsu, F. P. Calmon, J. C. S. Santos Filho, A. P. Calmon, and S. Salamatian
    NeurIPS Workshop on Machine Learning for the Developing World (ML4D).
  • Data Pre-Processing for Discrimination Prevention: Information-Theoretic Optimization and Analysis
    F. P. Calmon, D. Wei, B. Vinzamuri, K. N. Ramamurthy, and K. R. Varshney
    IEEE Journal of Selected Topics in Signal Processing, vol. 12, no. 5, pp. 1106-1119, Oct. 2018.
  • The utility cost of robust privacy guarantees
    H. Wang, M. Diaz, F. P. Calmon, and L. Sankar
    Proc. IEEE Int. Symp. on Inf. Theory (ISIT), pp. 706-710, 2018
  • On the direction of discrimination: An information-theoretic analysis of disparate impact in machine learning
    H. Wang, B. Ustun, and F. P. Calmon
    Proc. IEEE Int. Symp. on Inf. Theory (ISIT), pp. 1216-1220, 2018
  • Generalizing Bottleneck Problems
    H. Hsu, S. Asoodeh, S. Salamatian, and F. P. Calmon
    Proc. IEEE Int. Symp. on Inf. Theory (ISIT), pp. 531-535, 2018
  • A Tunable Measure for Information Leakage
    J. Liao, O. Kosut, L. Sankar, and F. P. Calmon
    Proc. IEEE Int. Symp. on Inf. Theory (ISIT), pp. 701-705, 2018
  • Hypothesis testing under mutual information privacy constraints in the high privacy regime
    J. Liao, L. Sankar, V. Y. F. Tan, and F. P. Calmon
    IEEE Trans. Inf. Forensics Security, vol. 13, no. 4, pp. 1058–1071, 2018
  • Strong data processing inequalities for input constrained additive noise channels
    F. P. Calmon, Y. Polyanskiy, and Y. Wu
    IEEE Trans. Inf. Theory, vol. 64, no. 3, pp. 1879-1892, 2018
  • 2017

  • Optimized pre-processing for discrimination prevention
    F. P. Calmon, D. Wei, B. Vinzamuri, K. N. Ramamurthy, and K. R. Varshney
    NIPS 2017
  • An estimation-theoretic view of privacy
    H. Wang and F. P. Calmon
    Proc. 55th Annual Allerton Conference on Communication, Control, and Computing, 2017
  • Principal inertia components and applications
    F. P. Calmon, A. Makhdoumi, M. Médard, M. Varia, M. Christiansen, and K. R. Duffy
    IEEE Trans. Inf. Theory, vol. 63, no. 8, pp. 5011–5038, 2017
  • Mutual outage probability
    F. P. Calmon, Á. A. M. de Medeiros, and M. D. Yacoub
    IEEE Trans. Wireless Commun., vol. 16, no. 5, pp. 3138–3150, 2017
  • Hypothesis testing under maximal leakage privacy constraints
    J. Liao, L. Sankar, F. P. Calmon, and V. Y. Tan
    IEEE Int. Symp. on Inf. Theory (ISIT), 2017, pp. 779–783
  • Prior to 2017

  • Correcting forecasts with multifactor neural attention
    M. Riemer, A. Vempaty, F. P. Calmon, F. Heath, R. Hull, and E. Khabiri
    ICML 2016
  • Hypothesis testing in the high privacy limit
    J. Liao, L. Sankar, V. Y. F. Tan, and F. P. Calmon
    Proc. 54th Annual Allerton Conference on Communication, Control, and Computing, 2016
  • Multi-user guesswork and brute force security
    M. M. Christiansen, K. R. Duffy, F. P. Calmon, and M. Médard
    IEEE Trans. Inf. Theory, vol. 61, no. 12, pp. 6876 – 6886, Dec 2015
  • Information-theoretic metrics for security and privacy
    F. P. Calmon
    Ph.D. Thesis, MIT, 2015
  • Managing your private and public data: Bringing down inference attacks against your privacy
    S. Salamatian, A. Zhang, F. Calmon, S. Bhamidipati, N. Fawaz, B. Kveton, P. Oliveira, and N. Taft
    IEEE J. Sel. Topics Signal Proces., vol. 9, no. 7, pp. 1240–1255, 2015
  • Fundamental limits of perfect privacy
    F. P. Calmon, A. Makhdoumi, and M. Médard
    Proc. IEEE Int. Symp. on Inf. Theory (ISIT), pp. 1796–1800, 2015
  • Strong Data Processing Inequalities in Power-Constrained Gaussian Channels
    F. P. Calmon, Y. Polyanskiy, and Y. Wu
    Proc. IEEE Int. Symp. on Inf. Theory (ISIT), pp. 2558–2562, 2015
  • Forgot your password: Correlation dilution
    A. Makhdoumi, F. P. Calmon, and M. Médard
    Proc. IEEE Int. Symp. on Inf. Theory (ISIT), pp. 2944–2948, 2015
  • An exploration of the role of principal inertia components in information theory
    F. P. Calmon, M. Varia, and M. Médard
    Proc. IEEE Inf. Theory Workshop, Nov. 2014
  • On information-theoretic metrics for symmetric-key encryption and privacy
    F. P. Calmon, M. Varia, and M. Médard
    Proc. 52nd Annual Allerton Conference on Communication, Control, and Computing, 2014
  • Bounds on inference
    F. P. Calmon, M. Varia, M. Médard, M. M. Christiansen, K. R. Duffy, and S. Tessaro
    Proc. 51st Annual Allerton Conference on Communication, Control, and Computing, 2013
  • Brute force searching, the typical set and guesswork
    M. M. Christiansen, K. R. Duffy, F. P. Calmon, and M. Médard
    Proc. IEEE Int. Symp. on Inf. Theory (ISIT), 2013, pp. 1257–1261
  • Guessing a password over a wireless channel (on the effect of noise non-uniformity)
    M. M. Christiansen, K. R. Duffy, F. P. Calmon, and M. Médard
    Proc. Asilomar Conference on Signals, Systems and Computers, 2013, pp. 51–55
  • How to hide the elephant-or the donkey-in the room: Practical privacy against statistical inference for large data
    S. Salamatian, A. Zhang, F. P. Calmon, S. Bhamidipati, N. Fawaz, B. Kveton, P. Oliveira, and N. Taft
    Proc. IEEE GlobalSIP, 2013
  • Multi-path TCP with network coding for mobile devices in heterogeneous networks
    J. Cloud, F. P. Calmon, W. Zeng, G. Pau, L. M. Zeger, and M. Médard
    Proc. IEEE 78th Vehicular Technology Conference, 2013, pp. 1–5
  • A framework for privacy against statistical inference
    F. P. Calmon and N. Fawaz
    Proc. 50th Annual Allerton Conference on Communication, Control, and Computing, 2012
  • Speeding multicast by acknowledgment reduction technique (SMART) enabling robustness of QoE to the number of users
    A. Rezaee, F. P. Calmon, L. M. Zeger, and M. Médard
    IEEE J. Sel. Areas Commun., vol. 30, no. 7, pp. 1270 –1280, Aug. 2012
  • Lists that are smaller than their parts: A coding approach to tunable secrecy
    F. P. Calmon, M. Médard, L. Zeger, J. Barros, M. M. Christiansen, and K. R. Duffy
    Proc. 50th Annual Allerton Conference on Communication, Control, and Computing, 2012
  • Equivalent models for multi-terminal channels
    F. P. Calmon, M. Médard, and M. Effros
    Proc. IEEE Inf. Theory Workshop, Oct. 2011.
  • MRCS – selecting maximal ratio combined signals: a practical hybrid diversity combining scheme
    F. P. Calmon and M. D. Yacoub
    IEEE Trans. Wireless Commun., vol. 8, no. 7, pp. 3425–3429, Jul. 2009
  • A general exact formulation for the outage probability in interference-limited systems
    F. P. Calmon and M. D. Yacoub
    Proc. IEEE Global Telecommunications Conference (GLOBECOM), Nov. 2008
  • Patents

    Teaching

    Spring 2019: Signals and Systems (ES 156)

    Spring 2018: Signals and Systems (ES 156)

    Fall 2017: Information Theory (ES 250)

    Contact

    Email: flavio (at) seas (dot) harvard (dot) edu

    Office:
    33 Oxford St.
    Office MD 347
    Cambridge, MA
    02138