Academics

Bio

Dr. Vijay Kumar Kalyani is a mathematician with expertise in artificial neural networking, mathematical modeling, and mathematical seismology. He obtained his PhD in 1988 from IIT-Indian School of Mines, Dhanbad, where he studied the propagation of elastic waves through media having irregularities. Dr. Kalyani has published 24 research papers in various journals and received the ISM Gold Medal for securing the top position in the M.Phil course. He has supervised one PhD thesis and 12 postgraduate theses. Dr. Kalyani's research has received 161 citations with an h-index of 7, i-10 Index of 8, and Scopus Index of 6.

Research Area
Mathematical Seismology, Artificial Neural Networking, Mathematical Modeling

Publication
1. RC Tripathi, VK Kalyani, LC Ram, SK Jha, Prediction of wheat yield from pond ash amended field by artificial neural networks, Journal of Hazardous, Toxic, and Radioactive Waste 19 (4), 2015 
2. VK Kalyani, Pallavika, SK Chakraborty, Finite-difference time-domain method for modelling of seismic wave propagation in viscoelastic media, Applied Mathematics and Computation 237, 133-145, 2014 IF: 3.472 
3. S Chaudhuri, VK Kalyani, TG Charan, S Kumari, A Sinha, Improved collector for beneficiation of low-volatile medium ash clean coal fines by froth flotation, International Journal of Coal Preparation and Utilization 34 (6), 321-331, 2014 IF:2.034 
4. TG Charan, VK Kalyani, KK Sharma, L Kumar, S Kumari, A Sinha, Use of an artificial neural network to evaluate the oleo-flotation process to treat coal fines, International Journal of Coal Preparation and Utilization 34 (5), 229-238, 2014, IF: 2.034 
5. US Chattopadhyay, VK Kalyani, R Venugopal, TG Charan, Application of response surface methodology in effective recovery of settling pond coal fines by froth flotation, 
International Journal of Coal Preparation and Utilization 35 (4), 206-215, 2015, IF:2.034
6. RC Tripathi, VK Kalyani, SK Jha, NK Srivastava, SK Thakur, Impact of Plant Nutrients on Prediction of Wheat Crop Yield from Pond Ash Amended Field by Artificial Neural Networks, The Journal of Solid Waste Technology and Management 45 (1), 76-83, 2019, IF:0.41

Google Scholar Link
https://scholar.google.co.in/citations?hl=en&user=kc-ksosAAAAJ

Scopus Link

https://www.scopus.com/authid/detail.uri?authorId=9270127300

Orcid Link
https://orcid.org/0000-0003-1795-9632