Rhythm
Rhythm2

Hi! I'm a Master's student in Computer Science, specializing in Machine Learning at the Georgia Institute of Technology. I'm currently a Graduate Research Assistant at the Georgia Tech Research Institute in the Methods & Analysis Development Branch, working on an open source RDF framework for contructing knowledge graphs and performing machine learning and information extraction applied on the semantic web.

Before coming to Georgia Tech, I worked as an ML Engineer at AT&T Labs where I developed natural language and vision models to solve various problems. I also developed backend infrastructure and full stack applications to deliver and serve models reliably in production.

I earned my Bachelor's degree in Computer Engineering from Purdue University, where I focused on the areas of operating systems and cloud computing for applications within embedded microcontrollers and low power devices.

In my free time, I enjoy powerlifting and playing the classical guitar. My biggest creative outlet is video editing. To me, every frame and musical beat is important for beautiful story telling.

I'm currently looking for a full-time role starting June 2021!

Interests:

  • Systems for Machine Learning

  • High Performance Computing

  • Machine Learning

  • Data Science and Analytics

  • Databases and Knowledge Graphs

My resume is available here. Feel free to reach out to me at msyed32@gatech.edu!


August 2015 - May 2019
July 2019 - August 2020
August 2019 - Present
August 2020 - Present

Projects
Autonomous Driving Simulation using Deep Reinforcement Learning
Deep Learning, Reinforcement Learning

Replicated a method of autonomous steering in a race car game using supervised imitation learning, reward induction, and reinforcement learning with a double Q learning network (DDQN)

Presentation Paper
MoReco: A Tag-Based Movie Recommendation System
Machine Learning, Data Visualization

Developed a recommender engine using cosine similarity that displays movies based on user selected tags on a web interface created in D3.js

Code Paper
Bayesian Inference Based Blur Removal from Images
Computational Photography, Bayesian Statistics

Created a pipeline to eliminate camera blur from images using Bayesian Inferencing and natural image statistics

Code Presentation
Seam Carving for Content Aware Image Resizing
Computational Photography, Dynamic Programming

Implemented an algorithm that computes the gradient energy function of images and enables resizing without loss or distortion of key features in the scene

Code Paper Demo
Health Monitoring Wearable with Sleep Detection
Real-Time Operating System, Cloud Computing & Analytics

Developed an embedded activity tracker using a real-time operating system and AWS (DynamoDB, IOT, Cognito)

Code Presentation Demo
Indoor Localization System
Internet of Things, Cloud Computing

Developed a system of indoor positioning in an ultra-wideband space using embedded systems and IOT. Enabled over-the-air firmware updates and autonomous navigation of drones

Abstract Demo