About Me

Amir Rajak

I am a Deep Learning engineer working mostly with computer vision systems. I love to travel. Life is a journey where we never fail, but learn in every step. I always try to move out of comfort zone and look for new challenges in life, and that's how we grow, right ??? :-). I believe that satisfaction in life is more important than being successful. And it is the only mantra to a joyful life.

My Career

Artificial Intelligence Technology Center

Artificial Intelligence research lab at Asian Institute of Technology, Bangkok, Thailand. Working on vision based AI systems.

Jan. 2019 - Present
Research Associate

Cotiviti Technologies Pvt. Ltd.

US healthcare informatics company. Worked as a backend developer, worked primarily on implementing core business logic.

Sept. 2015 - July 2017
Senior Software Engineer

Logic Information Systems

Retail data analytics and data warehousing company. Worked in several ETL and BI projects for Express Inc., Siam Makro, and so on.

Jan 2015 - Sept. 2015
Software Engineer

Deerwalk Services Pvt. Ltd.

US healthcare data analytics company. Performed analytics on client data to figure out various insights on the data.

May 2013 - Jan. 2015
Software Engineer

My Skills

My Projects

Video analytics for connection discovery and user behavior monitoring.

This is my master degree thesis where I developed a system to discover connections between individuals at a certain place or environment, using video surveillance systems. Basically, I developed a system and used it for case study at a coffee shop at my university. I used state-of-the-art machine vision algorithms for face recognition, human tracking, built a model for human action recognition, calculated distance between customers, evaluated their gaze direction and finally classified them as belonging to a common group or not.

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eHealth dashboard

A course project for Information Systems Development and Management. Has separate features for different users, patient, nurse or doctor. Individual dashboard for patients. Aggregated reports for nurses and doctors with the ability to drill down to individual patient level. Developed with the view of helping to digitalize data from rural areas of Thailand.

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BPM Detection

A course project for Machine Learning. A beats per minute predictor of a music clip. A model that takes input a music clip and classifies the BPM on the song to five different classes. Used convolutional neural network to train the model. Inspired from https://github.com/GiantSteps/giantsteps-tempo-dataset

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