Coding? Pretty exciting, eh? Tell me about it!
Hello, I'm Yogesh, a software engineer based in Los Angeles, CA, and an Electrical Engineering Graduate student at the University of Southern California. I'm an ambitious and self-motivated graduate with a strong inclination towards Computer Vision/Perception in Autonomous Driving. I'm an avid learner with a practical mindset. My team and I are Ford sponsor award winners at CalHacks 6.0 Hackathon organized at UC Berkley for developing a platform called IDEAS (Intelligent Driver Enhanced Assistance System) in 36 hours.
I work with Prof. Jyotirmoy Deshmukh at USC CPS-VIDA as a Graduate Researcher where I developed first open-source ROS wrapper for DeepSORT Multi-Object tracking algorithm publishing unique object ID's on Jetson Xavier Platform.
I like to create things that involve a camera, LiDAR, and a car. The fusion makes it undeniably beautiful, especially the world it creates around it. The future of this fusion is near, and I'm excited to a part of it.
I like programming, reading, travelling, and cooking. I've played national-level tennis and I'm a drummer. I follow tennis, cricket, and formula-1 racing.
P.S. Don't forget to checkout my work behind the supercool background gif you saw above.
I'm working with Prof. Jyotirmoy Deshmukh where we are developing monitoring algorithms for data
streams that are generated by perception algorithms. The goal of the research is to incorporate safe
Parallel to our research, we are building USC's first autonomous delivery robot prototype from start to finish. It's a 1/10th size outdoor robot equipped with sensors and capable of real-time perception (object detection, multi-object tracking) and mapping.
Languages : C, C++, Python, Matlab
Sensors : Zed 3D Camera, Hokuyo LiDAR, Vecternav IMU
System on Chip : Jetson Xavier, Jetson TX2
Other : PCL, ROS, TensorFlow, Keras
Frenzy Labs, Inc is a LA based startup that develops self-labeling image technology that trains computer vision systems to detect exact products in complex visual scenes. They scale high-quality image datasets in a fraction of the time incurred by enterprises today and reduce manual labeling workforces by 99%.
Languages : Python, HTML5
Libraries : Flask, Redis, CSS, TensorFlow, Keras, OpenCV
Coursework & Projects :
Stack - C++, ROS, Darknet, Python, Jetson XavierView Project
Stack - C++, PCL, Point Cloud DataView Project
Stack - C++, ROS, Darknet, Python, Jetson TX2View Project
Stack - ROS, Python, Jetson Xavier, TensorFlow, Yolov3View Project
Stack - MATLAB, SimulinkView Project
Stack - Java, Python, OpenCV, JSON requests, APIs - Google Cloud Vision, Google Maps, Spotify, Ford SDLView Project
Stack - C++View Project
Stack - Python, Keras, OpenCVView Project
Trained a CNN image classifier on 50k CIFAR-10 images using two different architectures.
Stack - Python, Keras, PyTorchView Project
Performed Sentiment Analysis on 53k reviews which includes Amazon, IMDB and Yelp.
Stack - Python, Sci-kit Learn, Numpy, Pandas, NLTKView Project
Simulated the working of RRT motion planning which finds a route between the start node and goal node
Stack - Python
Demonstrated the working of the Kalman Filter to estimate the state of the system. Utilized a constant jerk model to simulate the working of Kalman Filter.
Stack - Python
Stack - Python, OpenCV, PID Controls
10,000 diverse images with pixel-level and rich instance-level annotations. Stack - Python, DeepLabv3+, Jetson XavierView Project