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Hello, my name is

Saisha Chhabria.

I'm a computer engineer who specializes in Deep Learning, particularly in Computer Vision and Robotic Process Automation.

I graduated with a Master's in Computing (Arificial Intelligence Specialization) from the National University of Singapore.

Currently, I am a Data Scientist at Monarch Tractor, working towards the future of intelligent and autonomous tractors in farming. Yes, literal tractors.

Whether you have a question or just want to say hi, my inbox is always open!

About

Saisha Chhabria

Hello! I'm Saisha.

I enjoy building things that have a real-world purpose. My interests lie at the intersection of Computer Vision and Robotics, all of which began in 2018 when I worked on my first ever project in the field.

As a curious computer engineer, ever fascinated by the puzzles in the world around me, I strive for challenging opportunities to exercise and build upon my repertoire of computation, development, and collaboration skills, and aspire to combat problems that result in positive impacts on the community.

I recently graduated with a Master's in Computing (Artificial Intelligence Specialization) from the National University of Singapore.

Currently, I am a Data Scientist at Monarch Tractor, working towards the future of intelligent and autonomous tractors in farming.

Some tech I work with daily:

  • PyTorch
  • Tensorflow
  • Neural Networks
  • AWS
  • OpenCV
  • SQL

Where I've Worked

  • Data Scientist @ Monarch Tractor

    December 2023 - Present

    Spearheading development of deep neural networks to drive electric autonomous tractors, facilitating precision agriculture and operational efficiency around the world.

    Developing a UNet model, fine-tuned on a custom built dataset with image augmentation and stable diffusion for camera clarity detection to enhance operation of complimentary AI models.

    Engineered ClearNet, a custom UNet-based model with dual segmentation (87% Mean IoU) and classification (98.6% accuracy) heads for camera clarity detection, crucial for reliable operation of complementary AI models in varying field conditions.

    Deriving an advanced semantic segmentation model based on Mask2Former, improving perception mapping accuracy by 35% and enabling auto-labeling, thereby reducing manual annotation time by 60%.

    Testing and deploying an object detection model based on YOLOv7 to encompass edge case object detection.

  • Software and Applications Developer @ Star Information Systems

    July 2023 - November 2023

    Collaborated with a team of developers to build the proprietary software – a web enabled application with a ReactJS (with Typescript) frontend integrated with a .NET Core backend. Interfacing via a web API, this application manages all the data and functions for a maritime company.

    I specialized in building intelligent software components to enhance the daily workflow in maritime companies.

    Enhanced user experience and accessiblity with a customizable dashboard written in ReactJS and Typescript. The dashboard allows users to build different types of charts with customizable parameters and drill down options. The dashboard recommends useful charts to users based on past activity on the platform.

  • Graduate Research Assistant @ AI Singapore

    January 2023 - May 2023

    Spearheaded research and implementation of state-of-the-art solutions for hateful meme detection, a challenging classification problem.

    Designed and developed a robust pipeline to construct a multilingual dataset of images using Python and OpenCV for efficient classification.

    Led research and planning efforts for misinformation detection and countermeasures in multilingual and multimodal settings, contributing to the advancement of cutting-edge techniques.

    Conducted comprehensive surveys and analyzed state-of-the-art literature and datasets in the domains, collaborating with a team to formulate and refine problem statements for a competition. Successfully prepared and curated high-quality datasets.

  • Machine Learning Intern @ Bank of Singapore

    Emerging and Foundation Technologies

    July 2022 - December 2022

    Build end-to-end systems using ML and statistics along with commercial tools in Python like Tensorflow, PyTorch, Caffé etc.

    Research and development to build a robust knowledge graph extractor from unstructured text in compliance documents to assess client's asset justification. Tested several methods including customization of proven models like BERT, linguistic analysis, etc.

    Built a recommendation system along with two other colleagues in Python, with a collaborative, content-based and hybrid model. Gathered customers feedback to train and further improve the system and add additional features to improve user experience.

    BAU involved labeling and analyzing large sets of visual (images and videos), gathering customer feedback and building new models and improve, training ML models and writing code to prepare, use, enhance and test models, and researching public ML models and datasets.

  • Graduate Research Assistant @ AI Singapore

    May 2022 - June 2022

    Research and planning for the misinformation detection and counter problem in multilingual and multimodal settings.

    Surveyed and reported state-of-the-art literature and datasets in the domain.

    Collaborated with a team to formulate and refine a problem statement for a competition in the domain and prepared a dataset for the same.

  • Machine Learning Intern @ Nested Technologies

    November 2021 - January 2022

    Worked on a project, Quantity AI, which leverages computer vision techniques to extract information from CAD drawings and plans

    Debugged and fixed model errors, as well as deployment issues in the pipeline for the Quantity AI web application

  • Machine Learning Intern @ Vectra Automation Inc.

    January 2021 - June 2021

    Communicated and collaborated with multi-disciplinary teams of engineers and designers daily to build a sustainable pipeline to generate 2D drawings from 3D models.

    Developed a 3D CNN for part recognition from voxelized 3D CAD models (92% accuracy). Implemented a transfer learning approach for part, shape, and bracket recognition using 2D images taken from different orientations of 3D models (99% accuracy).

    Formulated a robust API design to interface with deep learning solutions hosted on AWS, composed microservices using Docker, automated image capture of 3D models and encoding images into JSON, amongst other tasks to establish a smooth process flow, and reduced required pipeline time by 20%.

  • Software Engineering Intern @ Kratos Fit AI

    March 2021 - June 2021

    Expedited development time (20%) by building a robust and load-balanced integration of iOS and Android mobile applications with external ML APIs hosted on Azure cloud.

    Established minimum viable product for Kratos Android Application and its interface with external APIs with Java and Android Studio.

    Built end-to-end APIs with SpringBoot and MongoDB, integrated with the iOS application.

  • Machine Learning Engineer@ Autosys Industrial Solutions

    July 2020 - December 2020

    Architected and developed scalable deep learning architectures including autoencoder neural networks and anomaly detection models amongst others, to detect and predict outliers in machine parameters during functioning with 96% accuracy.

    Built a deep learning solution to predict when tools attached to a machine are wearing (98% accuracy).

  • Software Development Intern @ Diebold Nixdorf Software

    June 2019 - July 2019

    Constructed a microservice tool to aid development by enforcing a constant template for login, authentication, and other common operations in cross-organization applications. The tool works as a Visual Studio Code extension written with Node.js, TypeScript, and Python, and optimizes development time by 20%.

    Investigated and revamped automated testing tools for various products- increased speed and reliability by 40%.

  • Android Development Intern @ TraveLibro

    December 2018 - February 2019

    Assisted in development, testing and deployment the Android application "TraveLibro" – a platform for travel bloggers.

    Conducted trial runs to ensure instruction correctness and production of desired information.

    Storage, retrieval and manipulation of data for analysis of system capabilities and requirements.

Education

2021 - 2023

National University of Singapore

Master's in Computing (Artificial Intelligence specialization)

GPA: 4.35/5

Courses: AI Planning and Decision Making, Neural Networks and Deep Learning (1 & 2), Uncertainty Modeling in AI, Big Data Analytics, Information Visualization, Pervasive Computing Technology and Solutions, Interaction Design with Virtual & Augmented Reality, Human-Centred Intelligent Systems, Knowledge Discovery & Data Mining

2016 - 2020

University of Mumbai - Thadomal Shahani Engineering College

Bachelor of Engineering in Computer Engineering

GPA: 9.39/10

Academic wards: Principal’s Excellence, Academic Excellence, Computer Engineering Branch Ambassador

Extracurriculars: Soccer Captain (2016 - 2019), Entrepreneurship Development and Professional Development Director @ The Rotaract Club of Thadomal Shahani Engineering College (2018 - 2019)

2014 - 2016

The Cathedral and John Connon School

Indian School Certificate in Science (ISC Science)

Grade: 95.56%

Extracurricular Activites: Badminton Captain, Soccer, Cricket

Projects

Here are my personal and coursework projects!
In my free time, I love working on projects to exercise and build upon my skills.

  • All
  • Computer Vision
  • NLP
  • Web/App Dev
  • CS
  • Vizualizations
  • AR/VR

Exploring DeepFakes (Technical Reviewer)

Technically reviewed a book by Packt publishing called Exploring DeepFakes.

LifeAid

A Virtual Reality (VR) simulation aimed at educating users on how to react in emergency situations. Beginning in a forest and then teleporting to different accident sites where users must tackle a person around them having emergency situations like heat exhaustion, etc.

Live Captioned AR Glasses (Research)

A research project on the design and evaluation of live captioning augmented reality (AR) glasses for individuals with hearing impairment.

Location, Location, Location?

A regression model which predicts the resale price of HDBs in Singapore.

Textract

An Open-source knowledge graph extractor from unstructured text based on StanfordOpenIE, spaCy, NLTK and Stanford NLP.

Where should I(m)-migrate?

A data visualization project built to be used when deciding where and whether to migrate to. Built on assimilated and processed data from several sources, the visualizations go from simple to complex and highlight key insights along the way.

‘No turning back’

A research project to determine the best backbone architecture for contrastive learning including ResNet, ConvNeXt and ViT on self-supervised clustering tasks with identical pretext and downstream tasks for fair comparison on the CIFAR10 dataset, further tested on the AID dataset.

Smart Fridge 5451

[Prototype] A smart fridge using IoT component and ML which detects items present inside the fridge. With a Raspberry Pi and accessories, the IoT component collects and relays data to the cloud. An Android application retrieves and presents this data and detected objects to the user.

The SeeFood Diet

An Android application for dietary control (counting calories, planning meals, etc.) using CNNs for food item recognition. Increased accuracy to 97% by hyperparameter tuning.

Prevention > Cure

Created a Django web application which leverages support vector machines to preempt machine breakdown (96% accuracy on simulated machines). The machine data was simulated using an Arduino coupled with sensors..

Zoe

A COVID-19 resource chatbot which converses with users, identifies intents, then searches for resources using a custom Twitter API and delivers resources to the user.

Motus Captis

A facial motion capture and expression recognition application. Utilizing a camera, it replicates human expressions in models on Blender and draws an outline leveraging glumpy with a 95.8% accuracy.

Jerry

A voice-activated virtual mouse built combining CV and natural language processing (NLP). Upon saying the word 'activate', it starts a virtual mouse that you can control with your fingers.

Elmo

A real-time face recognition application with a mask detection module to effect minimal contact and security, identifying individuals with 97% accuracy.

thera.py

A therapist chatbot to combat barriers to therapy, such as cost, availability, and the stigma attached to it. It converses with users to diagnose and treat mental health issues like anxiety and depression.

Synergy

An arcade game written in Python using Pygame consisting of two balls that always move circularly and must avoid obstacles.

Music Player

A music player written in Java using JavaFX and Swing with essential functionalities to control music, create and share playlists, etc.