Aahan is available for hire

Aahan Singh

Verified Expert in Engineering

Machine Learning Engineer and Developer

Location

Singapore, Singapore

Toptal Member Since

October 24, 2022

A certified Kubernetes application developer and full-stack machine learning engineer, Aahan is an expert in computer vision and experienced in creating model training and deployment pipelines on Kubernetes and on-premise hardware. He completed his master's in computer science, where he focused on machine learning and applied Hinton's capsule networks to the domain of time. Aahan's other projects include creating image captioning and question-answering deep learning models.

Machine Learning Artificial Intelligence (AI)Deep Learning Computer Vision Software Engineering Python 3 PyTorch Python Big Data Linux TensorFlow Docker Kubernetes Stable Diffusion Natural Language Processing (NLP)Autonomous Vehicle Software Medical Imaging RNN

Portfolio

Qritive

Python 3, PyTorch, TensorFlow, Docker, Kubernetes, Computer Vision, Research...

Moovita

Artificial Intelligence (AI), Computer Vision, Recurrent Neural Networks (RNNs)...

National University of Singapore

Artificial Intelligence (AI), Computer Vision...

Experience

Python 3 - 6 years Linux - 6 years PyTorch - 6 years Deep Learning - 6 years Computer Vision - 6 years Machine Learning - 6 years Docker - 4 years Kubernetes - 1 year

Availability

Part-time

Preferred Environment

Python 3, Linux, PyTorch, Docker, Kubernetes, Deep Learning, Machine Learning, Computer Vision, Research

The most amazing...

...project I've worked on is creating an AI system that detects cancer in medical images and proving that it works through clinical validation.

Work Experience

AI Engineer

2019 - PRESENT

Qritive

Developed a complete machine learning pipeline, from data acquisition and cleaning to model serving.
Took three products through research and development stages to clinical validation.
Published research papers at the intersection of healthcare and machine learning.

Technologies: Python 3, PyTorch, TensorFlow, Docker, Kubernetes, Computer Vision, Research, Big Data, Medical Imaging, Histopathology, Deep Learning, Convolutional Neural Networks (CNN), Dimensionality Reduction, Software Engineering, Image Classification, Object Detection, Semantic Segmentation, Instance Segmentation, Clinical Validation

Deep Learning Engineer

2018 - 2018

Moovita

Assisted in R&D efforts to develop end-to-end steering control systems for the prototype self-driving system.
Experimented with recurrent neural networks (LSTM and GRU) to enable automated steering control given the stream of roadview images.
Prepared a demo to showcase the working of the RNN-based steering control system for the CTO.

Technologies: Artificial Intelligence (AI), Computer Vision, Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNN), Deep Learning, Self-driving Cars, PyTorch, Python, Linux, Research

Graduate Student Researcher

2018 - 2018

National University of Singapore

Researched the latest methods in the domain of self-modifying neural networks.
Implemented capsule networks for image classification in PyTorch.
Researched the inner workings of capsule networks and what makes their viewpoint invariant.
Experimented with a new type of unit inspired by capsule networks that learn time-invariant properties in sequential data (text and audio).

Technologies: Artificial Intelligence (AI), Computer Vision, Convolutional Neural Networks (CNN), Deep Learning, Machine Learning, Linux, Python 3, Research, Audio, Signal Processing

Research Fellow

2017 - 2017

National Institute of Advanced Studies

Assisted research efforts in the domain of machine consciousness.
Implemented the Long Term Recurrent Neural Network(LRCN) architecture to perform image captioning.
Developed novel methods to determine the level of consciousness of image captioning models.
Presented research results to the fellowship committee.

Technologies: Python, Caffe, Research, Deep Learning, Neural Networks, Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNN), Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Computer Vision, Images

Experience

Capsule Networks in PyTorch

https://github.com/AahanSingh/Capsule-Networks

The project was about PyTorch implementation of capsule networks as described in the Dynamic Routing Between Capsules, a paper written by Sara Sabour, Nicholas Frosst, and Geoffrey E Hinton. I worked on this project as a student researcher during my master's degree.

Neural Image Captioning

https://github.com/AahanSingh/ConsciousAgent

The process of generating descriptions for images is called image captioning and this project aimed to train an AI system to perform image captioning. It was my final year undergraduate project and the first one I did in deep learning and neural networks domains.

Generative Lightning

https://github.com/AahanSingh/Generative-Lightning

PyTorch Lightning implementation of various Generative models with Weights and Biases support. This project was a self-learning project I did to gain a better understanding of generative models, GANS in particular. It contains code written in Python with the deep learning models written in PyTorch sitting on the PyTorch lightning framework.

Out-of-domain Object and Style Generation

This project made use of DreamBooth to train custom objects and styles into the Stable Diffusion base model where I created a custom dataset of the objects and styles along with captions for each image of the dataset which was then used to fine-tune the model to generate images of said objects and specific styles.

Education

2017 - 2018

Master's Degree in Computer Science

National University of Singapore (NUS) - Singapore, Singapore

2013 - 2017

Bachelor's Degree in Computer Science & Engineering

Ramaiah Institute of Technology - Bangalore

Certifications

MAY 2021 - MAY 2024

Certified Kubernetes Application Developer

Linux Foundation

Skills

Libraries/APIs

PyTorch, TensorFlow

Languages

Python 3, Python, Java, C, C++, SQL

Frameworks

Caffe

Platforms

Linux, Docker, Kubernetes, Web

Other

Machine Learning, Artificial Intelligence (AI), Deep Learning, Computer Vision, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNNs), Research, Medical Imaging, Software Engineering, Image Classification, Object Detection, Semantic Segmentation, Instance Segmentation, Fine-tuning, Big Data, Images, Clinical Validation, Image Processing, Stable Diffusion, DreamBooth, Natural Language Processing (NLP), Self-driving Cars, Neural Networks, Operating Systems, Algorithms, Data Structures, Cryptography, IP Networks, Linear Algebra, 3D Graphics, Probability Theory, Graph Theory, Statistics, Statistical Methods, Hypothesis Testing, Generative Adversarial Networks (GANs), Audio, Signal Processing, Histopathology, Dimensionality Reduction, Generative Artificial Intelligence (GenAI), GPT, Generative Pre-trained Transformers (GPT)

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