Reshma Rastogi
Reshma Rastogi
Assistant Professor
Department of Computer Science
Room No.314,Akbar Bhawan,Chankyapuri,New Delhi- 110021,India
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Ms.Reshma Khemchandani received Ph.D. in Mathematical Programming Applications in Machine Learning from Indian Institute of Technology, Delhi in 2008. Her recent interest includes Machine learning,Financial Mathematics and Optimization.Earlier she had a Bachelor's Degree in Sciences (Mathematics) from Maitreyi College, University of Delhi, in 2001 and Post Graduation in Mathematics in 2003 from Indian Institute of Technology, Delhi. She worked for approximately Six years with Royal Bank of Scotland Algorithmic Trading Group, Gurgaon. She has published 16 research papers ( Machine Learning and Finance ) in International journals and 6 research papers in refereed conference proceedings.She has co-authored book on Financial Mathematics- An Introduction: S.Chandra, S.Dharmaraja, A.Mehra, R.Khemchandani, Narosa Publication, 2012. Currently, she is Assistant Professor in the Faculty of Mathematics and Computer Science at South Asian University, New Delhi,India.


  • PhD in Mathematical Programming Applications in Machine Learning from Indian Institute of Technology Delhi , in 2008

Recent Publications

  • Color image classification and retrieval through ternary decision structure based multi-category TWSVM. Neurocomputing 165:444-455 (2015)

  • "Efficient Trading Frontier: A shortage Function Approach", Optimization: A Journal of Mathematical Programming and Operations Research, Vol.63, issue 10, pp 1533-1548, 2014

  • "Single assest optimal trading strategies with stochastic dominance constraints ". Annals of Operations Research, DOI 10.1007/s 10479-014-1697-0, 2014.

  • "Optimal Execution with weighted impact function : a quadratic programming approach", Optimization Letters, Vol. 7 (3), pp. 575-592, 2013

  • " Proximal Support Tensor Machines ", International Journal of Machine Learning and Cybernetics, Vol. 4(6), pp 703-712, 2013.

  • " TSVR for Simultaneous learning of function and its derivative ", International Journal of machine Learning and Cybernetics , Vol.4(1), pp51-63, 2013.

  • " Proximal Support Tensor Machines".International Journal of machine Learning and Cybernetics, DOI: 10.1007/s 13042-012-0132-6, 2012
  • " TSVR for simultaneous learning of function and its derivative", International journal of machine Learning and Cybernetics, DOI: 10.1007/s13042-012-0072-1,2012
  • " Knowledge based least Squares Twin support vector machines" Information Sciences, Vol. 180(23), pp 4606-4618,2010
  • " Learning the optimal kernel for Fisher discriminant analysis via second order cone programming", European Journal of Operational Research,Vol. 203 (3), pp.692-697,2010
  • " Knowledge Based Proximal Support Vector Machines" , European journal of Operational Research, Vol. 195, pp. 914-923, 2009
  • " Optimal Kernel selection in twin support vector Machines", Optimization Letters, Vol. 3(1): pp. 77-88, 2009
  • "Regularized Least Squares Fuzzy Support Vector Regression for Financial Time Series Forecasting." Expert Systems with Applications, Vol.36,pp. 132-138,2009
  • " Linear Potential Proximal Support Vector machines for Data Classification" ,Optimization Methods and Software, Vol.23, pp.491-500, 2008
  • " Regularized Least Squares Support Vector Regression for the simultaneous learning of a function and its derivatives ",Information Sciences, Vol. 178, pp. 3402-3414, 2008
  • " Generalized eigenvalue proximal support vector regressor", Expert Systems and its Applications, Vol.38(10), pp. 13136-13142, 2011
  • " Twin Support vector machines for pattern Classification" IEEE Trans. on Pattern Recognition and Machine Intelligence, Vol. 29, pp. 905-911, 2007  

Research Interests

  • Machine Learning
  • Optimization
  • Optimal Trading Strategies
  • Image Processing

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