I am a college freshman interested in computer science and music technology. Some of my current interests include digital signal processing, data science and machine learning, computer vision, robotics, jazz, and electronic music. I have over 5 years of programming experience and I am also an electronic music producer with releases on several indie labels. My resume is available here.
Adversarial Reinforcement Learning for Music Generation
ISMIR 2018 Late-Breaking Session
|Programming Languages||JS, Python, Go, Bash, C++, Java, Max/MSP|
|Frameworks and Technologies||OpenCV, Arduino, Keras, Numpy, JUCE, Vue, Unreal Engine 4|
|Creative Software||Ableton Live, After Effects, Photoshop, Logic Pro|
|Other||Git, AWS, GCP, Slack, Trello|
Software Team Manager responsible for maintaining the club's online code presence, managing the software aspects of current projects, and participating in weekly meetings with the rest of the club's executive board.
Built a live, real-time audio processor with C++ and JUCE that uses an FFT comparison heuristic to replace input audio with audio from existing songs, producing a unique "remixing" effect. In addition, used Max to control video playback based on frequency and amplitude of input audio. The entire project was completed within 18 hours. Won first place in the U-M Project Music 2018 Makeathon. Featured in U-M Engineering Newsletter.
As part of FRC team, trained a custom model for an object detection framework (YOLOv3) on game pieces. Used a novel method for sensor fusion to maintain a field model using optical flow in conjunction with YOLOv3, onboard LiDAR, and IMU to estimate pose of robot and game pieces on the field. Model was used for an autonomous routine to manipulate the nearest game piece.
Regularly produce electronic compositions under the alias Kanooli. Developed branding strategy and accompanying website, and have accumulated over 200k plays through releases on several indie music labels with large audiences.
Developed Telegram chat bot used by the majority of students at my high school to assist students with the frequently changing class schedule and upcoming homework assignments.
Used markov chains and LSTM neural networks to generate music from a dataset of scraped MIDI files.