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I'm Shree.

Machine Learning Engineer

More about me
About

Hi there!

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I'm a full-time Learner and a Seeker.
I aspire to build a system to provide all of us; not an equal opportunity, but the one that enables each one of us to flourish exquisitely.
How is a garden mesmerizing; if all the flowers grown in it, are the same?

Profile

Methodical Machine Learning Engineer with a cumulative experience of 4 years.

Skills

Skilled problem-solver with unique perspective in solutions, focused on answering why do we do what we do while tackling daily problems.

  • Machine Learning
  • Python
  • Problem Solving
  • SQL
  • Google Cloud Platform
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Resume

A bird's-eye view of my professional journey.

Career

Teaching Assistant - Data Science

Jan 2023 - Present
Worcester, MA, USA

Worcester Polytechnic Institute (part-time)

Got selected for being a TA for the Computational Data Intelligence course at WPI along with the tuition scholarship.

Machine Learning Intern (Fall) Biotechnology Research

Aug 2022 - Dec 2022
San Francisco, CA, USA

Openwater.cc (startup)

Trained a self-supervised One-shot learning based Head Segmentation model with 0.75 Dice similarity score. This model will help deliver MRI-based treatments for brain-related illnesses. It removes the current dependency on CT scan and prevents the risk of cancer due to ionization.
Worked on a high-impact project changing more than 1 million lives by helping detect stroke in the first response.
Auto-generating labels by one-shot data augmentation for MRI segmentation dataset, and implementing UNETR, a Vision Transfomer (ViT) based model. Also worked on a time series transformer model for stroke detection.

Summer Intern Applied Research - Deep Learning

May 2022 - August 2022

Quantiphi Inc.

Implemented Graph Machine Learning and GPT, T5, Transformer based algorithms to large Knowledge Graphs for automatic multi-hop Question Generation. This helps to generate 100s of meaningful questions from every single document which further enhances the document understanding for Question Answering.
Researched on applying Graph Machine Learning algorithms to large Knowledge Graphs for automatic multi-hop Question Generation.

Master's Degree (M.S. in Data Science)

August 2021 - May 2023 (expected)
Worcester, MA, USA

Worcester Polytechnic Institute

My area of research is in applying Machine Learning and Deep Learning techniques to various problems in Education, Medicine, Transportation, Autonomous Vehicles, and Robotics.

Senior Machine Learning Engineer

February 2021 - July 2021

Quantiphi Inc.

Created a pipeline of OpenCV data augmentation, model-assisted data cleaning and labelling to qualify dataset to train Efficientnet models which improved classification accuracy by 20% of frequently varying image designs into 500 classes.

Software Engineer Machine Learning

January 2019 - August 2020

Yantriks India Pvt. Ltd. (startup)

Designed and implemented end-to-end ML systems for Global Returns Forecasting, Dynamic Capacity Planning, etc.
Increased inference performance by 70% and decrease running cost by 20% for deployment code by bootstrapping.
Implemented parameterized code to enable Neural Architecture Search (NAS) driven by JSON config.
Mentored an intern for 4 months while implementing EDA and ML data flow pipelines for Anomaly Detection.

Talk

May 2017
Bengaluru, KA, India

Talk on Essence of Linear Algebra

Gave a talk on Essence of Linear Algebra in IISc Summer School 2017 to 80 students from across India.
Inspired by the graphical intuition behind the far-reaching applications of LA concepts. Here's the link. Thanks to the great videos on the 3Blue1Brown YouTube channel.

Master of Technology (M.Tech)

August 2016 - December 2018
Bengaluru, KA, India

Indian Institute of Science

I studied various courses in the Intelligent Systems stream of the Computer Science and Automation department. Relevant courses: Machine Learning, Deep Learning, Natural Language Processing, Reinforcement Learning, Game Theory, Probability and Statistics. Contributed ideas to the Intelligent Traffic Lights System's project.

Bachelor in Engineering (B.E.)

August 2010 - June 2014 Pune, MH, India

Savitribai Phule Pune University

I studied Computer Science in the D. Y. Patil College of Engineering, Akurdi. I gained first-hand exposure in "Engineering" software solutions for real world problems from scratch. I was exposed to inspiring ideas while doing projects in different frameworks starting from C++ console programs to VB scripts to Web-based projects.

Projects

Reinforcement Learning

January 2022 - May 2022
Worcester, MA, USA

DDPG for Turtlebots Path planning

Trained RL agents using DDPG algorithm to handle mapless navigation in simple and obstacle filled environments.
Designed the state space and reward function to help the RL agents learn to take efficient actions and reach goals without any collisions. The solution is scalable, dynamic, and has minimal manual intervention.

Deep Learning

January 2022 - May 2022
Worcester, MA, USA

OffRoadNet - Path detection for Autonomous Vehicles

Our motivation for this project was to improve the offroad path detection performance, and make it light enough to deploy the trained model on edge devices and fast inference. And thus, progress towards autonomy level 5 in difficult terrains.
We trained various Deep Learning architectures like PSPHead, ENCHead, with ResNet pretrained backbone.
We also finetuned the hyperparameters and also met the state-of-the-art performance on the RUGD and Yamaha dataset.

Machine Learning

August 2021 - Dec 2021
Worcester, MA, USA

Brain Tumor Radiogenomic Classification using 3D-CNN

Worked on a very important and challenging dataset of brain MRI scans downloaded from a Kaggle competition.
We tried a one-shot atlas based data augmentation and ensemble methods to improve DNA methylation classification.
Trained 3D CNN and Resnet50 models on 4 different types of brain MRI scan data.
Created an ensemble of these models to increase the methylation classification performance by 4%.

NeurIPS 2019 Deep RL Workshop

August 2018 - Dec 2018
Bengaluru, KA, India

Intelligent Coordination among Multiple Traffic Intersections Using Multi-Agent Reinforcement Learning

This project is done in collaboration Research and development team at Siemens India. We worked on demonstrating the effectiveness of the Deep RL solutions to be better than human intuition based Fixed Signal Time controls.
Setup PTV Vissim and Aimsun for simulating the traffic environments based on Bengaluru's traffic analysis.
Ideated traffic density representation which helped the A3C based RL agents to learn to create green corridors.
Achieved considerable results wherein Average Waiting time for vehicles is reduced by 1 minute saving 1000s of minutes cumulatively.

@alexshree.stories

Camera's attempt towards capturing what our EYES can.

Liberty

San Francisco

Cable car
Shutterbug

Stars

Orion's belt
AlexCake

Cake

By Alex
GoldenGateBridge

Golden Gate Bridge

Iconic San Francisco
Veggies

Veggies

Ready to Roast
Blizzard

Blizzard

Massachusetts
Jalebi

Jalebi

Delicacy
Contact

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Where to find me

Worcester, MA
Oakland, CA
US

Email Me At

nitai.shreedhar@gmail.com

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