The Tien Mai
About
My current postdoc projects focus on spatio-temporal statistics where the main research projects are from:
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Center for Geophysical Forecasting (SFI -CGF) (https://www.ntnu.edu/cgf)
Prior joining NTNU, I did a postdoc in statistical genetics with Jukka Corander at department of Biostatistics, University of Oslo.
Together with Natoya Jourdain, we are organizing the NTNU WGSS seminar (working group in statistical science seminar) from Spring 2022 !
Research topics:
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State-space model: Kalman filtering
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Statistical machine learning:
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High-dimension sparse regression,
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Transfer learning and Lifelong learning,
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Matrix completion, low-rank matrix estimation,
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Bayesian inference and PAC-Bayesian analysis,
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Biostatistics:
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drug sensivetivity prediction with multi-omics data,
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genetic characteristics of phenotype(s): heritability, genetic co-variability,
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bacterial GWAS: estimation and prediction.
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Education:
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PhD in statistics:
CREST-ENSAE-ParisTech/Paris Saclay (Oct 2015 - June 2017)
University College Dublin, Ireland (Jan 2014 - Sep 2015)
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Master in Mathematics & Informatics, Université Paris 13, France (2013).
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B.Sc in Mathematics, HCM City-University of Pedagogy, Vietnam (2011)
Publications:
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Mai, T. T. (2022). "Efficient adaptive MCMC implementation for Pseudo-Bayesian quantum tomography." Computational Statistics. (accepted)
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T. T. Mai, P. Alquier (2022). "Understanding the Population Structure Correction Regression", Proceedings of the 4th International Conference on Statistics: Theory and Applications (ICSTA), Paper No. 114. A long version is available on arXiv:2102.05655.
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Mai, T. T. (2022). ``PAC-Bayesian Matrix Completion with a Spectral Scaled Student Prior." The 4th Symposium on Advances in Approximate Bayesian Inference. online 01 February 2022
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Mai, T. T. (2022). ``On regret bounds for continual single index learning." In: Arai, K. (eds) Intelligent Computing. SAI 2022. Lecture Notes in Networks and Systems, vol 506. Springer, Cham. https://doi.org/10.1007/978-3-031-10461-9_37
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Jaroy, E.G., Emblem, R., Reims, H.M. Mai T.T. , G. T. Risa, R. Ougland. 2022 "Evaluation of diagnostic factors used to refer children with constipation for rectal biopsies". International Journal of Colorectal Disease 37, pages 597–605 (2022). https://doi.org/10.1007/s00384-021-04069-4
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Mai, T.T., Turner, P. and Corander, J., (2021). "Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting". BMC Bioinformatics 22 (1), 1-16 (arXiv:1910.11743).
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Mai T.T., Rønneberg L., Zhao Z., Zucknick M., Corander J. (2020) "Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank Structure". In: Cazzaniga P., Besozzi D., Merelli I., Manzoni L. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2019. Lecture Notes in Computer Science, vol 12313. Springer, Cham. https://doi.org/10.1007/978-3-030-63061-4_7
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T.T. Mai & P.Alquier (2017). "Pseudo-Bayesian Quantum Tomography with Rank-adaptation", Journal of Statistical Planning and Inference, Vol.184, 62–76. (arXiv:1605.05933)
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T.T. Mai & P.Alquier (2015). "A Bayesian approach for noisy matrix completion: Optimal rate under general sampling distribution". Electronic Journal of Statistics, Vol.9, no.1:823-841. (arXiv:1408.5820)
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P.Alquier, T.Tien Mai, and M.Pontil (2017), "Regret bounds for Lifelong learning". The 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, Florida, USA. PMLR 54:261-269, 2017
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Mai, T.T., Rønneberg, L., Zhao, Z., Zucknick, M., & Corander, J. (2019). "Composite local low-rank structure in learning drug sensitivity". CIBB 2019 the 16th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (arXiv).
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J.A. Lees, T. T. Mai, M. Galardini, N. E. Wheeler, S. T. Horsfield, J. Parkhill & J. Corander. (2020). "Improved prediction of bacterial genotype-phenotype associations using interpretable pangenome-spanning regressions". mBio Vol.11 (4):e01344-20. https://doi.org/10.1128/mBio.01344-20.
Publications
2022
- Mai, The Tien. (2022) An efficient adaptive MCMC algorithm for Pseudo-Bayesian quantum tomography. Computational statistics (Zeitschrift).
- Mai, The Tien. (2022) On Regret Bounds for Continual Single-Index Learning. Lecture Notes in Networks and Systems. volum 506.
- Mai, The Tien; Alquier, P.. (2022) Understanding the Population Structure Correction Regression. Proceedings of the 4th International Conference on Statistics: Theory and Applications (ICSTA'22).
2021
- Jarøy, Emilie Grimnes; Emblem, Ragnhild; Reims, Henrik Mikael; Mai, The Tien; Risa, Gabriel T.; Ougland, Rune. (2021) Evaluation of diagnostic factors used to refer children with constipation for rectal biopsies. International Journal of Colorectal Disease.
- Mai, The Tien; Turner, Paul; Corander, Jukka. (2021) Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting. BMC Bioinformatics. volum 22 (1).
2020
- Lees, J.A.; Mai, The Tien; Corander, Jukka. (2020) Improved prediction of bacterial genotype-phenotype associations using interpretable pangenome-spanning regressions. mBio. volum 11.
- Mai, The Tien; Rønneberg, Leiv; Zucknick, Manuela; Corander, Jukka; Zhao, Zhi. (2020) Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank Structure. Lecture Notes in Computer Science (LNCS). volum 12313.
2017
- Mai, The Tien; Alquier, P.. (2017) Pseudo-Bayesian quantum tomography with rank-adaptation. Journal of Statistical Planning and Inference. volum 184.
2016
- Alquier, P.; Mai, The Tien; Pontil, M. (2016) Regret bounds for lifelong learning. Proceedings of Machine Learning Research (PMLR). volum 54.
2015
- Mai, The Tien; alquier, pierre. (2015) A Bayesian approach for noisy matrix completion: Optimal rate under general sampling distribution. Electronic Journal of Statistics. volum 9 (1).
Journal publications
- Mai, The Tien. (2022) An efficient adaptive MCMC algorithm for Pseudo-Bayesian quantum tomography. Computational statistics (Zeitschrift).
- Mai, The Tien. (2022) On Regret Bounds for Continual Single-Index Learning. Lecture Notes in Networks and Systems. volum 506.
- Mai, The Tien; Alquier, P.. (2022) Understanding the Population Structure Correction Regression. Proceedings of the 4th International Conference on Statistics: Theory and Applications (ICSTA'22).
- Jarøy, Emilie Grimnes; Emblem, Ragnhild; Reims, Henrik Mikael; Mai, The Tien; Risa, Gabriel T.; Ougland, Rune. (2021) Evaluation of diagnostic factors used to refer children with constipation for rectal biopsies. International Journal of Colorectal Disease.
- Mai, The Tien; Turner, Paul; Corander, Jukka. (2021) Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting. BMC Bioinformatics. volum 22 (1).
- Lees, J.A.; Mai, The Tien; Corander, Jukka. (2020) Improved prediction of bacterial genotype-phenotype associations using interpretable pangenome-spanning regressions. mBio. volum 11.
- Mai, The Tien; Rønneberg, Leiv; Zucknick, Manuela; Corander, Jukka; Zhao, Zhi. (2020) Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank Structure. Lecture Notes in Computer Science (LNCS). volum 12313.
- Mai, The Tien; Alquier, P.. (2017) Pseudo-Bayesian quantum tomography with rank-adaptation. Journal of Statistical Planning and Inference. volum 184.
- Alquier, P.; Mai, The Tien; Pontil, M. (2016) Regret bounds for lifelong learning. Proceedings of Machine Learning Research (PMLR). volum 54.
- Mai, The Tien; alquier, pierre. (2015) A Bayesian approach for noisy matrix completion: Optimal rate under general sampling distribution. Electronic Journal of Statistics. volum 9 (1).