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<h1>Azadeh Khaleghi</h1>
<td align="justify">
<p> I am a Professor of Statistics at <a href="https://www.ensae.fr"> École Nationale de la Statistique et de l'Administration Économique (ENSAE)</a> - <a href="https://crest.science">Centre de Recherche en Économie et Statistique (CREST)</a>.
My research interests are in the mathematical foundations of Statistics and Machine Learning. My main focus is on devising nonparametric models for long-memory time series and Multi-Armed Bandits. I am also interested in studying the possibilities and limitations of Algorithmic Fairness.</p>
<div><h2> Contact Details</h2></div>
<span style="font-size: larger;">azadeh dot khaleghi at ensae dot fr</span><br><br>
<span style="font-size: larger;">École Nationale de la Statistique et de l'Administration Économique</span><br>
5, avenue Henry Le Chatelier 91120 Palaiseau
<p class="small"><a href="https://scholar.google.co.uk/citations?user=VnTMs_EAAAAJ&hl=en"><i>Google Scholar</i></a></p>
</td>
<td> </td>
<td>
<a href="IMGLINKTARGET"><img src="shapeimage_2.png" alt="alt text" width="WIDTHpx" height="HEIGHTpx"/></a> </td>
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<div><h2> Notable Awards & Grants</h2></div>
<ul>
<p><li> <a href="https://guillaume-lecue.faculty.essec.edu/graph4health">GRAPH4HEALTH</a> ANR Project 2023 - <i> from healthcare accessibility to health outcomes: a stats & ML approach</i></li></p>
<p><li> Google Faculty Research Award, 2019/20</li></p>
<p><li> London Mathematical Society (LMS) Scheme 4 Grant, 2019 </li></p>
<p><li> Adobe Research Grant, 2018</li></p>
<p><li> London Mathematical Society (LMS) Scheme 1 Grant, 2017</li></p>
<p><li> E.M. Gold Best Paper Award at the 24th International Conference on Algorithmic Learning Theory (ALT), 2013</li></p>
</ul>
<div><h2> PhD Opportunities</h2>
I am currently accepting applications for the following PhD project:
<ul>
<li><p><a href="https://adum.fr/as/ed/voirproposition.pl?site=adumR&matricule_prop=60634#version">Nonparametric Estimation for Dependent Processes with application to modern Machine Learning models</a>.
The ideal candidate would be expected to have a strong background in mathematical statistics and be comfortable with measure theory and functional analysis. Proficiency in programming is a plus. Please feel free to contact me for more details.</p>
</li>
</ul>
<div ><h2> Selected Publications & Preprints</h1></div>
<div align="justify">
<ul>
<li><p><b>A. Khaleghi</b>, <a href="https://ieeexplore.ieee.org/document/10851303"> On Restless Linear Bandits</a>, IEEE Transactions on Information Theory, 2025. </p>
</li>
<li><p><a href="https://grunewalder.blog">S. Grünewälder</a>, <b>A. Khaleghi</b>, <a href="http://arxiv.org/abs/2402.07296"> Estimating the Mixing Coefficients of Geometrically Ergodic Markov Processes</a>, 2024. </p>
</li>
<li><p> <a href="https://www.lancaster.ac.uk/maths/people/gordon-blower">G. Blower</a>, <b>A. Khaleghi</b>, M. Kuchemann-Scales, <a href="https://doi.org/10.1063/5.0169792">Hasimoto frames and the Gibbs measure of periodic nonlinear Schrödinger Equation</a>, Journal of Mathematical Physics, vol. 65, issue 2, 2024. [<a title="Publications_files/nstclust.pdf" href="Publications_files/HasimotoJMP.pdf">pdf</a>]</p></li>
<li><p> <b>A. Khaleghi</b>, <a href="http://www.econ.upf.edu/~lugosi/">G. Lugosi</a>, <a href="https://ieeexplore.ieee.org/document/10050550">Inferring the mixing properties of an ergodic process</a>, IEEE Transactions on Information Theory, vol. 69, no. 6, pp. 4014-4026, 2023. [<a title="Publications_files/nstclust.pdf" href="Publications_files/EstimatingMixing.pdf">pdf</a>]</p></li>
<li><p><a href="https://grunewalder.blog">S. Grünewälder</a>, <b>A. Khaleghi</b>, <a href="https://www.jmlr.org/papers/volume22/20-1311/20-1311.pdf">Oblivious Data for Fairness with Kernels</a>, Journal of Machine Learning Research, (208): 1-36, 2021. [<a href="https://github.com/azalk/Oblivious.git">code</a>]
</p>
<li><p><b>A. Khaleghi</b>, D. Ryabko, <a href="https://ieeexplore.ieee.org/document/9174045">Clustering piecewise stationary processes</a>, In Proceedings of the IEEE International Symposium
on Information Theory, 2020.
[<a title="Publications_files/nstclust.pdf" href="Publications_files/nstclust.pdf">pdf</a>]
</p></li>
<li><p><a href="https://grunewalder.blog">S. Grünewälder</a>, <b>A. Khaleghi</b>, <a href="http://www.jmlr.org/papers/volume20/17-547/17-547.pdf">Approximations of the Restless Bandit Problem</a>, Journal of Machine Learning Research, 20:1-37, 2019. [<a title="Publications_files/mixing_bandits.pdf" href="Publications_files/mixing_bandits.pdf">pdf</a>]</p>
</li>
<li><p><b>A. Khaleghi</b>, D. Ryabko, J. Mary, P. Preux, <a title="http://www.jmlr.org/papers/volume17/khaleghi16a/khaleghi16a.pdf" href="http://www.jmlr.org/papers/volume17/khaleghi16a/khaleghi16a.pdf" class="style_2">Consistent Algorithms for Clustering Time Series</a>, Journal of Machine Learning Research, 17(3):1-32, 2016.
[<a title="Publications_files/khaleghi16a.pdf" href="Publications_files/khaleghi16a.pdf">pdf</a>]
</p></li>
<li><p><b>A. Khaleghi</b>, D. Ryabko, <a title="http://www.sciencedirect.com/science/article/pii/S0304397515009470" href="http://www.sciencedirect.com/science/article/pii/S0304397515009470" class="style_2">Nonparametric Multiple Change Point Estimation in Highly Dependent Time Series</a>, Theoretical Computer Science, 620:119-133, 2016.
[<a title="Publications_files/P22.pdf" href="Publications_files/P22.pdf">pdf</a>]
<dl>
<dd>- A shorter version of this article received <a title="http://www-alg.ist.hokudai.ac.jp/~thomas/ALT13/gold.html" href="http://www-alg.ist.hokudai.ac.jp/~thomas/ALT13/gold.html">the E.M. Gold Award for the best paper</a> at the 24th International Conference on Algorithmic Learning Theory.</dd>
</dl>
<!--(<i>The conference version of this article <a title="http://www-alg.ist.hokudai.ac.jp/~thomas/ALT13/gold.html" href="http://www-alg.ist.hokudai.ac.jp/~thomas/ALT13/gold.html"> received the E.M. Gold Award for the best paper</a> at the 24th International Conference on Algorithmic Learning Theory.</i>)</p></li>-->
<li><p><b>A. Khaleghi</b>, D. Ryabko, <a title="http://jmlr.org/proceedings/papers/v32/khaleghi14.html" href="http://jmlr.org/proceedings/papers/v32/khaleghi14.html" class="style_2"> Asymptotically Consistent Estimation of the Number of Change Points in Highly Dependent Time Series</a> In Proceedings of the International Conference on Machine Learning, 2014. [<a title="Publications_files/ICML_mce_Clust.pdf" href="Publications_files/ICML_mce_Clust.pdf">pdf</a>][<a href="https://github.com/azalk/GoChest">code</a>] </p>
</li>
<!--<li><p><b>A. Khaleghi</b>, D. Ryabko, <a title="http://link.springer.com/chapter/10.1007/978-3-642-40935-6_27" href="http://link.springer.com/chapter/10.1007/978-3-642-40935-6_27" class="style_2">Nonparametric Change Point Estimation in Highly Dependent Time Series</a>, In Proceedings of Algorithmic Learning Theory (ALT), LNCS 8139, pages 382-396, Singapore, 2013.[<a title="Publications_files/P22.pdf" href="Publications_files/P22.pdf">pdf</a>] (<a title="http://www-alg.ist.hokudai.ac.jp/~thomas/ALT13/gold.html" href="http://www-alg.ist.hokudai.ac.jp/~thomas/ALT13/gold.html">Received the E.M. Gold Award for the best student paper</a>.)</p>
</li>-->
<li><p><b>A. Khaleghi</b>, D. Ryabko, <a title="http://papers.nips.cc/paper/4623-locating-changes-in-highly-dependent-data-with-unknown-number-of-change-points" href="http://papers.nips.cc/paper/4623-locating-changes-in-highly-dependent-data-with-unknown-number-of-change-points" class="style_2">Locating Changes in Highly-Dependent Data with an Unknown Number of Change-Points</a>, In Proceedings of Neural Information Processing Systems, 2012. [<a title="Publications_files/mce_nips.pdf" href="Publications_files/mce_nips.pdf">pdf</a>] [<a title="Publications_files/poster_nips12.pdf" href="Publications_files/poster_nips12.pdf">poster</a>][<a href="https://github.com/azalk/GoChest">code</a>]</p>
</li>
<li><p><b>A. Khaleghi</b>, D. Ryabko, J. Mary, P. Preux, <a title="http://jmlr.csail.mit.edu/proceedings/papers/v22/khaleghi12/khaleghi12.pdf" href="http://jmlr.csail.mit.edu/proceedings/papers/v22/khaleghi12/khaleghi12.pdf" class="style_2">Online Clustering of Processes</a>, In Proceedings of Artificial Intelligence & Statistics, 2012.[<a title="Publications_files/ocp.pdf" href="Publications_files/ocp.pdf">pdf</a>] [<a title="Publications_files/ocp_poster.pdf" href="Publications_files/ocp_poster.pdf">poster</a>]</p>
</li>
<li><p><b>A. Khaleghi</b>, <a href="https://danilosilva.sites.ufsc.br/index.html">D. Silva</a>, <a href="https://www.comm.utoronto.ca/frank/">F. R. Kschischang</a>, <a title="http://www.springerlink.com/content/87465723623m54mu/?p=cf71630add774246ad79c906bc49e966&pi=3" href="https://link.springer.com/chapter/10.1007/978-3-642-10868-6_1" class="style_2">Subspace Codes</a>, Lecture Notes in Computer Science, 2009. [<a title="Publications_files/subspace_1.pdf" href="Publications_files/subspace_1.pdf">pdf</a>]</p>
</li>
<li><p><b>A. Khaleghi</b>, <a href="https://www.comm.utoronto.ca/frank/">F. R. Kschischang</a>, <a title="http://dx.doi.org/10.1109/CWIT.2009.5069509" href="http://dx.doi.org/10.1109/CWIT.2009.5069509" class="style_2"> Projective Space Codes for the Injection Metric</a>, In Proceedings of the Canadian Workshop on Information Theory 2009. [<a title="Publications_files/subspace.pdf" href="Publications_files/subspace.pdf">pdf</a>][</span><a title="Publications_files/poster.pdf" href="Publications_files/poster.pdf" style="line-height: 14px; " class="style_6">poster</a><span style="line-height: 14px; " class="style_6">]</p>
</li>
</ul>
</div>
<div><h2> Software</h2></div>
<li><b>A. Khaleghi</b>, L. Zierahn, <a href="https://cran.r-project.org/web/packages/RChest/index.html"><i>RChest</i></a> and <a href="https://pypi.org/project/PyChest/"><i>PyChest</i></a>: An <b>R</b> package available on CRAN, (respectively a <b>Python</b> Package available on PyPi) for locating distributional changes in piece-wise stationary timeseries with long-range dependencies, (2021).
<p><dt> - <i>Corresponding Paper: <b>A. Khaleghi</b>, L. Zierahn, <a href="https://arxiv.org/abs/2112.10565">PyChEst: a Python package for the consistent retrospective estimation of distributional changes in piece-wise stationary time series</a>, arXiv:2112.10565.
</i></dt>
</li>
<dt> - <i>The <a href="https://github.com/azalk/GoChest">Github repository</a> contains a <b>Go</b> implementation which is also interfaced with <b>Python</b>.</i></dt></ul>
</ul></p>
<li><p><a href="https://github.com/azalk/Oblivious">Github repository</a> for the implementation of our `algorithmically fair' classification and regression methods proposed in <a href="https://arxiv.org/abs/2002.02901">this paper</a>.</p>
</li>
<div><h2> Dissertations</h2></div>
<div><pre>
</pre></div></div>
<ul>
<li><p>On Some Unsupervised Learning Problems for Highly Dependent Time Series, PhD Thesis, INRIA Lille - Université de Lille I, 2013. [<a title="Publications_files/Thesis.pdf" href="Publications_files/Thesis.pdf">pdf</a>]</p>
</li>
<li><p>Projective Space Codes for the Injection Metric, MSc Thesis, University of Toronto, 2009. [<a title="Publications_files/UT-thesis.pdf" href="Publications_files/UT-thesis.pdf">pdf</a>]</p>
</li>
</ul>
<div><h2>Teaching</h2></div>
<div class="blockcontent">
</div></div>
<ul>
<p><li> Statistics 1 (SE2C1EN) ENSAE, 2022 - present </li></p>
<p><li> Apprentissage Statistique appliqué (SE308) ENSAE, 2022 - present </li></p>
<p><li>Machine Learning (MATH336) Lancaster University, 2016 - 2022 </li></p>
<p><li>Probability & Stochastic Processes (MATH580/STOR602) Lancaster University, 2015 - 2021 </li></p>
<p><li>Project Skills (MATH390/MATH240) Lancaster University, 2015 - 2022 </li></p>
</ul>
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