Ninan Sajeeth Philip

AI, DL and Machine Learning Consultant

Don't be shy to share ideas. You will never exhaust them, instead will only multiply. - a personal view


List of Publications

September 27, 2022

In International Journals

  1. Boosting the Differences: A Fast Bayesian classifier neural network, Ninan Sajeeth Philip and K. Babu Joseph, Intelligent Data Analysis, 4(2000) 463-473, IOS Press, NL.

  2. Adaptive Basis Function for Artificial Neural Networks, Ninan Sajeeth Philip and K. Babu Joseph, Neurocomputing, Vol.47, 1-4, (Aug 2002), pp.21-34 Elsevier, NL

  3. A Neural Network Tool for Analyzing Trends in Rainfall, Ninan Sajeeth Philip and K. Babu Joseph, Computers and Geosciences, (2003), Vol. 29, no. 2, pp. 215-223, Elsevier, Canada.

  4. A difference boosting neural network for automated classification, N.S. Philip, Yogesh Wadadekar, Ajit Kembhavi, K. Babu Joseph, Astronomy and Astrophysics, (2002), 385(3): 1119–1133.

  5. Automated Galaxy Morphology: A Fourier Approach, S.C. Odewahn , S.H. Cohen, R.A. Windhorst, N.S. Philip, (2002), Astrophysical Journal, 568, 539.

  6. Modelling Chaotic Behavior of Stock Indices Using Intelligent Paradigms Ajith Abraham, Ninan Sajeeth Philip and P. Saratchandran, International Journal of Neural, Parallel & Scientific Computations, (2003), Volume 11, issues 1 & 2, pp 143 to 160.

  7. Rainfall Forecasting Using Soft Computing Models and Multivariate Adaptive Regression Splines, Ajith Abraham, Ninan Sajeeth Philip and Dan Steinberg, IEEE SMC Transactions: Special, 2001. [a collaborative project where all of us are co-principal investigators.]

  8. Soft Computing Models for Weather Forecasting, Ajith Abraham, Ninan Sajeeth Philip submitted to SCS Journal. (www.scs.org)

  9. Effect of substrate temperature on structural, optical and electrical properties of spray pyrolytically grown nanocrystalline SnO 2 thin films, 2007, Physica Status Solidi(a), 204(10), 3305.2

  10. Nanostructural and surface morphological evolution of chemically sprayed SnO 2 thin films, Applied Surface Science 254 (2008) 2179 - 2186.

  11. Results from the supernova photometric classification challenge, Richard Kessler et al., Publications of the Astronomical Society of the Pacific, 2010, 122, 1415

  12. A Learning Algorithm based on High School Teaching Wisdom, Ninan Sajeeth Philip, Paladyn Journal of Behavioral Robotics, 2010, 1(3), 160

  13. A Photometric Catalogue of Quasar and Other Point Sources in the Sloan Digital Sky Survey, Sheelu Abraham, Ninan Sajeeth Philip, Ajit Kembhavi, Yogesh G. Wadadekar and Rita Sinha, MNRAS, 2012, 419, p80-94.

  14. A wavelet-based algorithm for the identification of oscillatory event-related potential components; Arun Kumar Aniyan, Ninan Sajeeth Philip, Vincent J Samar,James A Desjardins, Sidney J Segalowitz; Journal of neuroscience methods;2014; 233; pp63-72

  15. Spectral variability of IRAS 18325-5926 and constraints on the geometry of the scattering medium S Tripathi, R Misra, GC Dewangan, J Cheeran, S Abraham, NS Philip The Astrophysical Journal 773 (2), 130

  16. Episodic High-velocity Outflows from V899 Mon: A Constraint On The Outflow Mechanisms; J. P. Ninan, D. K. Ojha, N. S. Philip; The Astrophysical Journal, Volume 825, Issue 1, article id. 65, 7 pp. (2016).

  17. UV and X-ray variability of the narrow-line Seyfert 1 galaxy Ark 564; Savithri H. Ezhikode, Gulab C. Dewangan, Ranjeev Misra, Shruti Tripathi, Ninan Sajeeth Philip, Ajit K. Kembhavi; Research in Astronomy and Astrophysics, Volume 16, Issue 7, article id. 008 (2016).

  18. Information Retrieval and Recommendation System for Astronomical Observatories; Nikhil Mukund, Saurabh Thakur, Sheelu Abraham, Arun K. Aniyan, Sanjit Mitra, Ninan Sajeeth Philip, Kaustubh Vaghmare and D. P. Acharjya; ApJS, 235, 1, 2018

  19. Transient Classification in LIGO data using Difference Boosting Neural Network; Nikhil Mukund, Sheelu Abraham, Shivaraj Kandhasamy, Sanjit Mitra, Ninan Sajeeth Philip; (eprint arXiv:1610.00429), Phys. Rev. D 95, 104059 – Published 31 May 2017

  20. Determining the torus covering factors for a sample of type 1 AGN in the local Universe; Savithri H Ezhikode, Poshak Gandhi, Chris Done, Martin Ward, Gulab C. Dewangan, Ranjeev Misra, Ninan Sajeeth Philip; Monthly Notices of the Royal Astronomical Society, 472, 3492-3511, 2017

  21. Information Retrieval and Recommendation System for Astronomical Observatories, Nikhil Mukund, Saurabh Thakur, Sheelu Abraham, Arun K. Aniyan, Sanjit Mitra, Ninan Sajeeth Philip, Kaustubh Vaghmare and D. P. Acharjya, ApJS, 235, 22, 2018

  22. Detection of Bars in Galaxies using a Deep Convolutional Neural Network; Sheelu Abraham, Arun K. Aniyan, Ajit Kembhavi & Ninan Sajeeth Philip; Monthly Notices of the Royal Astronomical Society, Volume 477, Issue 1, 11 June 2018, Pages 894 – 903

  23. Correlation between relativistic reflection fraction and photon index in NuSTAR sample of Seyfert 1 AGN SH Ezhikode, GC Dewangan, R Misra, NS Philip Monthly Notices of the Royal Astronomical Society 495 (3),2020, 3373-3386

  24. CASSPER: A Semantic Segmentation based Particle Picking Algorithm for Single Particle Cryo-Electron Microscopy, Nature Communications, Blesson George, Anshul Assaiya, Robin J Roy, Ajit Kembhavi, Radha Chauhan, Geetha Paul, Janesh Kumar, Ninan S Philip, Nature Communications biology, 2021

  25. Ion acoustic shock waves with drifting ions in a five-component cometary plasma, Neethu Theresa Willington, Anu Varghese, A.C. Saritha, Ninan Sajeeth Philip, Chandu Venugopal, Advances in Space Research,2021

Conferences and Book Volumes

  1. Chaos for Stream Cipher, in proc. of Recent Advances in Computing and Communications, ADCOM2000, Tata McGraw-Hill, (2000) pp 35-42.

  2. A Bayesian Approach for star-galaxy classification, N.S.Philip, K.Babu Joseph,Ajit Kembhavi, Yogesh Wadadekar, in proc. Automated Data Analysis in Astronomy, Narosa Publishing house, (2000) pp.125-132

  3. On the predictability of Rainfall in Kerala: an application of ABF Neural Network, Lecture Notes in Computer Science(LNCS 2074), Springer Verlag, Germany, (2001) pp 400-408

  4. Distorted English Alphabet Identification: An application of Difference Boosting Algorithm, In proc. of Recent Advances in Computing and Communications, ADCOM2000, Tata McGraw-Hill, (2000) pp 139-143 [Referee’s Best Paper Selection]

  5. Will we have a wet summer? Soft computing models for Long-term rainfall forecasting, Ajith Abraham, N.S. Philip, K. Babu Joseph,In proc. of 15th European Simulation Multiconference (ESM2001), Modeling and Simulation 2001, Prague (2001), pp 1044-1048. [Best Paper Award Selection]

  6. Studies in Artificial Neural Network Modeling, Ph.D Thesis (Nov. 2001).

  7. Performance Analysis of Connectionist Paradigms for Modeling Chaotic Behavior of Stock Indices, Ajith Abraham, Ninan Sajith Philip, Baikunth Nath, P. Saratchandran, Second International Workshop on Intelligent Systems Design and Applications, (ISDA’02), Computational Intelligence and Applications, Dynamic Publishers Inc., USA, ISBN 096403980X, pp. 181-186, Atlanta, USA, 2002.

  8. Optimal Selection of Training Data for the Difference Boosting Neural Networks, ADASS-2003, Strasbourg, France, October 2003.

  9. Optimal Section of Training Data for the Difference Boosting Neural Networks, iAstro-2003, Nice, France, October 2003.

  10. What is there in a Training Sample? Ninan Sajeeth Philip, 2009 World Conference on Nature and Biologically Inspired Computing (NaBIC-2009), IEEE, ISBN: 978-1-4244-5612-3.

  11. “Photometric Classification of Quasars from the Sloan Survey” Rita Sinha, N. S. Philip, Ajit Kembhavi, Ashish Mahabal, IAU HIGHLIGHTS OF ASTRONOMY, Volume 14: Special Session 3: The Virtual Observatory in Action: New Science, New Technology, and Next Generation Facilities

  12. Photometric identification of Quasar candidates, Sheelu Abraham and Ninan Sajeeth Philip, Astronomical Data Analysis Software and Systems XIX, ASP Conference Series, 2010, 434,pp 147-156

  13. Classification by Boosting Differences in Input Vectors, N.S. Philip, Ashish Mahabal, S. Abraham, R. Williams, S.G. Djorgovski, A. Drake, C. Donald and M. Graham, International Workshop on Stellar Libraries, Proceedings of a conference held 5-9 December 2011 at University of Delhi, India. Edited by Philippe Pruganiel & Harinder P. Singh. ISBN: 978-81-922926-4-9. Astronomical Society of India Conference Series, Vol. 6, 2011, p. 151

  14. Feature Selection Strategies for Classifying High Dimensional Astronomical Data Sets, CiroDonalek, Arun Kumar A., Ashish Mahabal et al., Proceedings of Scalable Machine Learning: Theory and Applications, IEEE BigData 2013, Santa Clara, CA, USA


Selected Public Talks