Kartik Chaudhary

I currently work as a Senior AI/ML Engineer at Google, where I design AI/ML based solutions/products leveraging the advancements in the field of Computer Vision, NLP, GenAI and Machine Learning.

I am passionate about learning and inventing new ways of improving ML and DL algorithms to solve real world problems more efficiently. Do checkout my blog on Artificial Intelligence - Drops of AI

If you want to have a 1:1 call, buzz me on Topmate (link below)!

Topmate (meet me 1:1)  /  LinkedIn  /  Google Scholar  /  Twitter  / 
Github  /  Medium  /  Blog

News  |  Books  |  Publications  |  Patents  |  Articles

News

[2024]: Published book on Generative Adversarial Networks titled The GAN Book
[2024]: Published book on The Definitive Guide to Google Vertex AI with Packt
[2023]: Got Promoted to Senior AI/ML Engineer at Google
[2022]: Filed a patent on "Improving Wind Power production forecast using Image Processing techniques"
[2022]: Published Easter2.0 paper preprint on Arxiv and code on Github
[2021]: Joined Google as an AI/ML Engineer, Dec-2021
[2021]: Runner’s Up, Global Data Science Hackathon, Optum
[2021]: Awarded Honory title of Senior Inventor for several contributions to patent program in 2020, Optum
[2020]: Runner’s Up, Global Data Science Hackathon, Optum

Books

If you are a ML practitioner who wants to learn about generative learning approaches and get expertise in Generative Adversarial Networks for generating high-quality and realistic content, this book is for you.

If you are a machine learning practitioner who wants to learn end-to-end ML solution development on Google Cloud Platform using MLOps best practices and tools offered by Google Vertex AI, this is the book for you.

Publications

Most of my research projects are related to computer vision, optical character recognition, image processing and video processing.

Clinical Decision Support System (CDSS) is an important technology for the healthcare industry that analyzes data to help healthcare professionals make decisions related to patient care.

Easter2.0 is a small/fast convolutional model for the task of OCR/HTR that works well even when labelled data is limited.

Easter is a small/fast fully convolutional model for the task of OCR/HTR.

Patents

Automated systems and methods for identifying fields and regions of interest within a document image.

Dynamic detection of cross-document associations.

Dynamic detection of cross-document associations.

Machine learning models for multi-risk-level disease spread forecasting.

Predictive document conversion.

Articles

Understanding Audio data, Fourier Transform, FFT and Spectrogram features for a Speech Recognition System.

Explaining Reinforcement Learning to your next-door-neighbor.

Optimizers explained for training Neural Networks.

1D-CNN based Fully Convolutional Model for Handwriting Recognition.

Boosting your Sequence Generation Performance with ‘Beam Search + Language model’ decoding.

Deep Learning with PyTorch: Introduction.

Deep Learning with PyTorch: First Neural Network.

OpenCV: Introduction and Simple Tricks in Python.

Convolutional Denoising Autoencoders for image noise reduction.

Sound Wave Basics — Every Data Scientist must know before starting analysis on Audio Data.

Variational AutoEncoders and Image Generation with Keras.

this guy's webpage is awesome