Siddha Ganju

I am an AI researcher at NVIDIA and lead the development of neural networks optimizations for medical instruments and life sciences companies. I lead, design, and helps deploy real-time and low power AI applications to enable impact of AI in traditional sciences and domains. Previously, I focused on the Self-Driving initiative - worked towards stable and scalable training of neural networks on very large data centers, and utilized simulation to validate the neural networks. At NVIDIA, I was bitten by the patent bug and have over 20 inventions.

A fun project I worked on the side - flood detection, got converted into an educational course jointly developed by the United Nations Satellite Centre (UNOSAT) and NVIDIA and has had 6k+ audience. Independent Software Vendors (ISV) also deployed this in 5 countries.

In 2017 I led NASA's Long-Period Comets team within their AI accelerator, called Frontier Development Lab, where we use machine learning to develop meteor detectors. Recently this project was able to provide the first-ever instrumental evidence of an outburst of 5 meteors coming from a previously known comet, called C/1907 G1 (Grigg-Mellish). I developed the AI pipeline to make data collection and filtering for meteors seamless, and since then it has discovered 10 new meteor showers! The camera network has expanded 6x, to various new countries and we developed one of the most popular tools https://meteorshowers.seti.org/ to view meteor shower activity. For this, I was awarded the Institute of Engineering and Technology’s Rolls Royce Achievement Award. I also mentored many teams in the SpaceML program. I was also invited as a grant reviewer by NASA for their 'Living with a Star' initiative. As a member of the NASA FDL AI Technical Committee, I'm working towards incorporating AI in many space science projects! NASA published an article about our DAGGER model (formally, Deep Learning Geomagnetic Perturbation) model, which can quickly and accurately predict geomagnetic disturbances worldwide, 30 minutes before they occur.

Previously I was the first engineer at Deep Vision (now called Kinara) where I worked on developing and deploying deep learning models on resource constraint edge devices.

I graduated from Carnegie Mellon University with a Master's in Computational Data Science and a Bachelor’s in Computer Science and Technology from the National Institute of Technology (NIT), Hamirpur, India. I love mentoring and sponsoring capstone projects at CMU, such as the CMU-sponsored Learn-to-Race challenge, which encourages safe, autonomous driving.

I have also authored a book on Practical Deep Learning for Cloud, Mobile & Edge - O'Reilly Publishers

I am a regular keynote speaker, reviewer, and advisor for multiple industry-level conferences and serves as a judge of international competitions such as the CES Innovation Awards. I have given 200+ talks in 50+ countries!

As an advocate for diversity in technology, I mentor students to grow a new generation of technologists from all backgrounds. I have also led Nvidia's Women in Technology team to develop several mentorship programs amassing over 400+ participants from all career tracks and levels including VPs and Directors.

[Resume] [Bio] [Scholar] [GitHub] [Twitter] [LinkedIn]

Email: firstnamelastname[at]emailserviceprovider, yahoo.co.in

IRC nick: sidgan

GPG Fingerprint: FCFC EF8E 95DE 42EC DE83 FA8C 6D18 0E5A DD42 E8B4

I have stopped updating this timeline in 2019. Please see [LinkedIn].

2019