Suchismita Goswami is a PhD student in Computational and Data Science (CDS). Her research interests include data mining, statistical inference, statistical graphics, time series analysis, Bayesian statistics, survival analysis and social networks.
Suchismita received a Bachelor of Science in mathematics (Hons.) from the University of Calcutta and earned a Master of Science in Applied Math and Statistics (Operation research) from the State University of New York, Stony Brook. In addition, she received her MS degree in Statistical Science from GMU with GPA 3.90. Currently, she is working on social networks using statistical modeling.
She recently presented her work on data mining in a conference and published her findings in peer reviewed scientific journal. Her publication and presentation are given below.
S. Goswami and E. Wegman, “Comparison of different classification methods on glass identification for forensic research,” Journal of Statistical Science and Application, April 2016, Vol. 4, No. 03-04, 65-84, doi: 10.17265/2328-224X/2015.0304.001
“Comparison of different classification methods on glass identification for forensic research”, 45th SYMPOSIUM ON THE INTERFACE: Computing Science and Statistics, Morgantown, WV, June 10–13, 2015