PyTorch VAE
A collection of 18+ VAE implementations in PyTorch Lightning
A scalable way to compare the layer representations of neural networks
Summary
I am a Machine Learning Engineer with 5 years of experience developing ML/DL models as well as conducting research on deep neural networks. I love working closely with hardware - developing DL models that are performant on the designated hardware and being Bayesian about it. I was a MEXT scholar during my Master's in JAIST, Japan, where my research was on spectral normalization for deep neural networks. Previously, I worked on embedded systems and signal processing. For one for my then projects, I had to learn statistical signal processing, which segued into my current interest in Machine Learning. Over the course of my professional career, I have been successful in applying Deep Learning for industrial anomaly detection, 3D PointCloud processing, Sim2Real, and multi-task learning.
Experience
|
Bodygram, Tokyo
Nov 2022 - Present |
Machine Learning Engineer |
|---|---|
|
Developing Deep-Learning solutions for accurate human body measurement and understanding.
#ROS2 #Pytorch/libtorch #OpenCV #ONNX #PCL #Sim2Real |
|
|
DeepX Inc, Tokyo
Feb 2022 - Nov 2023 |
Senior Computer Vision Engineer |
|
Developed Deep-Learning solutions for automating heavy construction vehicles like excavators and trucks. Worked predominantly on 3D computer vision, and point-clouds. Tasks include object detection, segmentation, tracking, and Sim2Real.
#ROS2 #Pytorch/libtorch #OpenCV #ONNX #PCL #Sim2Real |
|
|
NABLAS Inc, Tokyo
Oct 2019 - Jan 2022 |
Research Engineer |
|
Built DL solutions for industrial anomaly detection with real-world constraints.
Developed a zero-shot anomaly detection solution and optimized it for deployment on an NVIDIA edge-device. #Pytorch #OpenCV #ONNX #Docker |
|
|
RIKEN AIP, Tokyo
Feb 2019 - May 2019 |
Visiting Researcher |
| Worked predominantly on Gaussian Processes - a variational technique for scaling them to a magnitude more data points. #TensorFlow #GPy #Numerical Optimization | |
|
IIT Madras ADI-DSP Lab, India Jun 2015 - Feb 2017 |
Project Associate |
|
Main focus was on signal processing - giving lectures and tutorials on the ADSP-BF609 DSP chip.
Build the first prototype (now commercialized) for a low cost addressable fire alarm. #Numerical Optimization #Signal Filtering #C++ |
Education
|
Japan Advanced Institute of Science and Technology (JAIST), Japan
Oct 2017 - Dec 2019 |
Master's Degree in Informatics |
|---|---|
|
Outstanding Student Award 2019 JAIST President's award 2019 Thesis: Mean Spectral Normalization for Deep Neural Networks. |
|
|
SRM University, India
Apr 2012 - Apr 2015 |
Bachelor's Degree in Mechatronics |
| CGPA - 8.9/10. Thesis: Autonomous robot swarm search using Alpha-Beta coordination. Link |
Projects
PyTorch-Model Compare
sGMRFMix
Extremely fast and stable implementation of sGMRFMix model in C++ with python bindings
Mean Spectral Normalization
A plug-and-play alternative for Batch Normalization with fewer parameters for DNNs
Curve Studio
A minimalist app for designing spline curves
FCML
A collection of my notes on Machine Learning as a book
Swarm Robot Project
Autonomous Robot Swarm for Searching using Alpha Beta Coordination
Icthyologist
A Fish (esolang) iterpreter written in C++