HITESH SAPKOTA Resume

*** ****** ******* **. *****: adkc2n@r.postjobfree.com

Scottsville, NY, 14546 Phone: 585-***-****

Research Interests: Reinforcement Learning, Bayesian Learning, Multiple Instance Learning, Uncertainty Quantification, Deep Learning. EDUCATION

2017 - Present Ph.D. in Computing and Information Sciences Rochester Institute of Technology, Rochester, NY, USA. 2012 - 2015 Bachelor in Electronics and Communication Engineering Tribhuvan University, Institute of Engineering, Lalitpur, Nepal Graduated in December, 2015 (with 81%).

RELEVANT COURSEWORK

Statistical Data Mining, Deep Learning, Artificial Intelligence, Foundation of Intelligence System, Data Science for Software Engineering, Quantitative Foundation, and Big Data. EXPERIENCE

2017 AUG - Present Rochester Institute of Technology, Research Assistant. Current research focuses on devising Bayesian

Multiple Instance Learning Approach for (1) Anomaly Detection and (2) Cancer Region Detection in Medical Images. 2016 SEP - 2017 JUL Kathmandu University, Teaching Assistant. Taught various electronics/computer related subjects. Supervised various electronics/computer related projects. ACADEMIC AWARDS

RIT Ph.D. Merit Scholarship. (2017 - Today). Financial support for Ph.D. at the Rochester Institute of Technology.

Ncell Scholarship and Excellence Award. (2014). For excellent academic performance in the exam of Bachelor in Engineering, Electronics and Communication. Awarded by the Ncell at the Institute of Engineering, Pulchowk Campus. ACADEMIC PROJECTS

2015 Automatic Vehicle Number Plate Detection Using MLP. Keywords: ANN, Filtering, Segmentation.

2016 Face Detection/Identification using PCA and LDA. Keywords: Dimensionality Reduction, Matrix Factorization, Eigen Face. 2018 Developers’ Sentiment Prediction in Open Source Software Projects.

Keywords: Word2Vec, Recurrent Neural Network, K-means Clustering. 2018 Personalized Natural Language Explanation for Recommending Sharing Policy in Online Social Media.

Keywords: Explainable AI, Natural Language Processing, Word2Vec, Clustering. 2018 Exploration and Analysis of the Usage Challenge for Data Science Libraries.

Keywords: Hierarchical Topic modeling, HMM, Recommender System. 2018 English/Dutch Text Classification using Adaptive Boosting. Keywords: Decision Tree, Decision Stump, Adaptive Learning, Classification. 2019 Image Caption Generation using Adaptive Attention. Keywords: LSTM, CNN, Img2Vec, RNN.

2020 Video Anomaly Detection Using Bayesian Multiple Instance Learning. Keywords: MIL, CNN, LSTM, DRO, DKL, GP, GMM.

PUBLICATIONS

Alshangiti, M., Sapkota, H., Murukannaiah P.K., Liu X., Yu, Qi. Why is Developing Machine Learning Applications Challenging? A Study on Stack Overflow Posts. ESEM 2019.

Sapkota, H., Murukannaiah P.K., Wang Y. A Network Centric Approach for Estimating Trust between Open Source Software Developers. PLOS ONE 2019. Sapkota H., Ying Y., Chen F., Yu Q. Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning. AISTATS2021. (To Appear). TECHNICAL SKILLS

Languages/Programming:Python, Java, MATLAB, C/C++, R. Deep Learning Packages:Keras, Tensorflow, PyTorch, Caffe.