Danial Ebrat
Machine Learning Engineer @ Musora Media Inc.
Research Assistant @ University of Windsor
Ph.D. Student of Computer Science @ University of Windsor
About Me
I’m a Ph.D. student of computer science with over nine years of industrial experience in Artificial intelligence, Data science, and machine learning, and information technology. I have led various AI projects associated with time series and large-scale data and participated in multidisciplinary national projects. I’m passionate about new technologies and challenges, which cause growth and learning opportunities, especially in interdisciplinary projects, leading to the collaboration and teamwork of diverse experts from different backgrounds. Currently, my focus is on large language models, deep reinforcement learning, recommendation systems, and AI music.
Besides my work, my studies generally lie in the intersection of Music and Computer Science and its collaboration with various fields. I create AI solutions related to Music, Audio, and Speech, mostly to connect non-musicians to Music with a better perspective. I found out that Music and poetry have a significant impact on kids, and I would like to expand my research to study the psychological aspects of Music and poetry on kids some day. Therefore, I'm interested in connecting Deep learning and AI with Psychology and Neuroscience in general or specifically related to Music.
Personal Life
it’s obvious that I’m passionate about music! I like to sing and play guitar, especially with my daughter. Moreover, I had the honor of being in the choir of the Mehrzad Khajeamiri concert Group. I write poems and lyrics, some of which are available here, and you can follow our music band page (Ariana music band).
occasionally, I share my experiences through my YouTube channel as well by talking about various topics, mostly related to AI. Furthermore, I enjoy designing logos and websites, which can be found here. Finally, board Games, video games, audiobooks, and soccer are inseparable parts of my life!
Resume
Education
2022-Present
Ph.D. Computer Science
University of Windsor2018-2021
M.Sc. Computer Science _ Data Mining
Amirkabir University of Technology (Tehran Polytechnic)Thesis Title: "Persian modal music (Dastgah) Detection using Deep Neural Networks "
Abstract:
In this research, several deep neural networks are implemented to recognize Persian modal music in seven high correlated categories. The best model which achieved 92 percent overall accuracy is using an architecture inspired by Autoencoder including BiLSTM and BiGRU layers. This model is trained by using Nava dataset which has 1786 records and up to 50 hours of worth of music played solo by Kamanche, Tar, Setar, Ney, and Santoor(Dulcimer). Features that have been studied through this research, contain MFCC, Chroma feature and Mel spectrogram. The results indicate that MFCC carries more valuable information about Persian modal music than other features. Moreover, The architecture which is inspired by autoencoders is powerful in distinguishing high correlated data like Persian modal music. It also shows that because of the precise order in Iranian Dastgah Music, Bidirectional Recurrent networks are more efficient than any other network that has been implemented in this research. (Github link)