|Name||Dr. Gitanjali Devi|
|Nature of Post||SANCTIONED|
|Date of Joining||1995-07-15|
|Present Address||190 Savitri Villa, Chandmari Colony, M.R.D. Road, Ghy-781003|
|Education Qualification||M.Sc, M.Phill, Ph.D|
|Areas of Interest/Specialisation||Mechanics, Classical Dynamics, Electrostatics, Artificial Neural Network|
|Career Profile||Working in LCB college since 1995 (Lecturer 1995-2012, Assistant Professor 2013-Now)||Subjects taughts||Physics: Mechanics, Electrostatics, Thermodynamics, Kinetics, Magnetism and electricity, SHM, Relativity, Classica; Dynamics, etc|
|RESEARCH & PUBLICATIONS|
|1. Prediction of Location of High Energy Shower Cores using Artificial Neural Networks, International Journal of Engineering and Applied Sciences, Volume 7, No.1, pp.-20-26, 2011.
2. ANN based Multi Classifier System for Prediction of High Energy Shower Pri mary Energy and Core Location, International Journal of Information and Mathematical Sciences, Vol 6, No. 3, pp. 176- 185, 2010.
3. Certain Data Dimension Reduction Techniques for application with ANN based MCS for Study of High Energy Shower, International Journal of Engineering and Natural Sciences, vol. 4, no.3, 2010.
4. Prediction of High Energy Particle Shower Sizes and Core Location using Ar tificial Neural Networks, Springer Indian Journal of Physics, ISSN: 0019-5480 (print version), ISSN: 0974-9845 (electronic version) (accepted for publica tion).
5. Prediction of High Energy Shower Primary Energy and Core Location using Classifier System, International Journal of Artificial Intelligence and Knowledge Discovery, vol.1, Issue 2, April, 2011, (e-ISSN-2231-0312).
6. Estimation of Lateral Distribution of High energy Showers using Artificial Neural Network, Journal of Physics: Conference Series, Volume 409, 23rd European Cosmic Ray Symposium (and 32nd Russian Cosmic Ray Conference) 3–7 July 2012, Moscow, Russia
7. Devi, G., Sharma, M., Sarma, P. et al. Flood Frequency Modeling and Prediction of Beki and Pagladia Rivers Using Deep Learning Approach. Neural Process Lett (2022). https://doi.org/10.1007/s11063-022-10773-1|
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