Education

2007 Tribhuvan University (Nepal), B.A.
2011 Tribhuvan University (Nepal), M.A.
2016 Florida Atlantic University, M.S.
2022 Florida Atlantic University, P.h.D

Courses Taught

Introduction to Data Science
Applied Data Science
Introduction to Statistics
Applied Statistics
College Algebra

Career Specialties

Binod Rimal's research interest includes sequence modeling, machine learning/deep learning, natural language processing and statistical modeling. He is interested in teaching courses in statistics, data science and machine learning.

Professional and Community Activities

Rimal is active in several research projects in deep neural networks, stock trading and statistical modeling. He has presented his research at national and international conferences. Some of the recent papers are listed below:

1. Predicting stock market index using LSTM. Machine Learning with Applications, 9, 100320 (2022).
2. LSTM-SDM: An integrated framework of LSTM implementation for sequential data modeling. Software Impacts, 14, 100396 (2022).
3. Predicting NEPSE index price using deep learning models. Machine Learning with Applications, 9, 100385 (2022).
4. A New Generalized Cauchy Distribution with an Application to Annual One Day Maximum Rainfall Data. Statistics, Optimization & Information Computing, 9(1), 123-136 (2021).

Honors and Awards

Research Innovation and Scholarly Excellence (RISE) Grants at UT: RISE 23-24 GR3359.