Faculty at School of Natural Sciences

Niteesh Sahni

Niteesh Sahni

Associate Professor


Contact Information

Functional analysis, Operator Theory, Dynamical Systems

PhD, University of Delhi, 2014

MPhil, University of Delhi, 2003

MSc, University of Delhi, 2001

BSc Honours, Sri Venkateswara College, University of Delhi, 1999

  • July 2021 till present: Associate Professor, Department of Mathematics, Shiv Nadar University.
  • June 2011 till June 2021: Assistant Professor, Department of Mathematics, Shiv Nadar University.
  • 2004-2011: Senior Lecturer, Mathematical Sciences Foundation, New Delhi.

2013 Gave an invited talk on ?Invariance in Hardy-Hilbert spaces? at the 100th Indian Science Congress in 2012. Adjunct Department:?Institute for Innovations & Inventions with Mathematics and IT (IIIMIT)

My research focuses on areas in Applied Machine Learning which focuses on identifying anomalies in Financial data, Material science data, Medical and Satellite images, and making explainable predictive models. This work involves an interplay of Machine Learning and Complex Networks. Currently I am also involved in modeling Happiness and Loneliness using the above tools.

I also have a keen interest in Harmonic analysis, wherein I have studied invariant subspaces of the Shift operator on certain Banach spaces of analytic functions including the classical Hardy Spaces, the BMOA space, and the Generalized Hardy spaces with rotationally symmetric norms. The techniques developed in this research have allowed to obtain meaningful extensions, of famous theorems of Beurling, Helson-Lowdenslager, and De-Banges with far simpler proofs, and sharper characterizations.

Besides teaching a variety of core and elective courses in Mathematics over the years at SNU, I have also developed and taught 4 machine learning and Artificial intelligence courses. The highlights being Machine learning through R, Deep Learning, Learning from Data, and Bayesian Network Learning. Two of these courses are also cross-linked with Computer Science department. All these courses are offered as University wide electives and attract handsome number of students from engineering and social sciences.

 

  • Member, syllabus drafting committee (NEP-UGCF), Department of Mathematics, University of Delhi.

  • Apoorva Singh & Niteesh Sahni, Helson-Lowdenslager and de Branges type theorems in the setting of continuous rotationally symmetric norms, Banach J. Math. Anal. 17, 55, Springer, 2023.
  • Apoorva Singh & Niteesh Sahni, Multiplication by finite Blaschke factors on a general class of Hardy spaces, Advances in Operator Theory 7(62), Springer, 2022.
  • Anand, J., Sahni, N. & Srivastava, S. On extension of Beurling–Helson–Lowdenslager theorem. Advances in Operator Theory 6(62), Springer, 2021.
  • Niteesh Sahni and Charu Sharma, A mutual information based R-vine copula strategy to estimate VaR in high frequency stock market data, Plos One 16(6), 2021.
  • A. Tiwari, N. Sahni, S. Dixit, and S. Bordas, Machine learning approaches to identify and design low thermal conductivity,oxides for thermoelectric applications, Data Centric Engineering, Cambridge University Press, 2020.
  • N. Sahni, A. Kumar, and D. Singh, Invariance under finite Blaschke factors on BMOA, New York J. Math., 2017.
  • N. Sahni, A. Kumar, and D. Singh, Invariance under bounded analytic functions: generalizing shifts, New York J. Math., 2016.
  • Niteesh Sahni and Dinesh Singh, Lax-Halmos type theorems in Hp spaces, Houston J. of Math., 2015.
  • Niteesh Sahni and Dinesh Singh, Multiplication by Monomials on BMOA, Houston Journal of Math., 2014.
     
  • L.M. Saha and Niteesh Sahni, Chaotic Evolutions in a Modified Coupled Logistic Type Predator-Prey Model, Applied Mathematical Sciences, 2012.
     
  • L.M. Saha, Til Prasad Sharma, and Niteesh Sahni,   Measuring Chaos in Some Discrete Nonlinear Systems, IJET, 2012.
     
  • Niteesh Sahni and Dinesh Singh, Invariant Subspaces of Certain Sub-Hilbert Spaces of H2, Proc. Japan Acad., 2011.

  • Conducted a workshop for University and College teachers of Mathematics on “Mathematical Data Science & Applications” at the Miranda House College, University of Delhi, from June 15-21, 2023.
  • Taught a module titled “Applied Machine Learning: A Mathematical Overview” at the refresher course on Mathematics/ Operational Research/ Statistics and Computer Science (IDC) on the theme “Mathematics with an Emphasis on Topology, Analysis and Applications” held from September 2–15, 2022 for University and College teachers organized by Centre for Professional Development in Higher Education (CPDHE)-UGC-MHRD Centre (Delhi University).
  • Talk on Invariance in Hardy spaces at 100th Indian Science Congress, Kolkata, 2013.
  • Talk on Nevanlinna-Pick Interpolation in Hardy spaces at the International Workshop on Operator Theory and Applications, IISC, Bangalore, 2014.
  • Lecture on Introductory Functional Analysis at Annual Foundation School (NBHM), 2016.
  • Workshop on Excel in Mathematical Finance at Islamic University of Science & Technology, Kashmir, 2014-15.

  • Dec. 2017 till present: Undergraduate Advisor & Chair of Department Undergraduate Committee, Department of Mathematics, SNIOE.
  • April 2015-June 2017: Chair of the University Timetabling Committee, SNIOE.