I am a postdoctoral scientist at the University of Pennsylvania. At Penn, I am working on developing computational and machine learning tools for materials of energy applications. I have received my Ph.D. in Physics from Temple University in 2018, where my focused research area was computational condensed matter physics. I have done one-year Postdoctoral training at Georgia Tech prior to joining Penn. At Georgia Tech I used several machine learning and deep learning techniques to predict polymer materials properties. In specific, I have developed a new machine learning methodology that extracts useful information from less accurate data to predict the correct answer. I am a very efficient programmer in C, C++, and Python. I am a regular user of different machine learning and big data packages like sklearn, TensorFlow, Keras, Pytorch, MongoDB, Spark, etc. I am interested in applying my skills and knowledge for the betterment of human life.