Sushant Gautam | Machine Learning Engineer

Hi, I'm Sushant Gautam.

As a dedicated Computer Science graduate student with a focus on Machine Learning and Data Science, I am seeking an internship opportunity where I can leverage my expertise in Machine Learning, Deep Learning, Computer Vision, and AWS Cloud technologies. My goal is to apply my theoretical knowledge and innovative ideas to challenging projects, thereby gaining invaluable hands-on experience.

The only way to do great work is to love what you do.

About

Software Engineer with a Passion for AI/ML Applications Development and its Deployment

Welcome to my digital domain, where Artificial Intelligence (AI) is not just a subject of fascination but a canvas for innovation. My journey in AI was kindled by Andrew NG's 2008 CS229 Machine Learning Stanford lecture. Since 2017, I've been deeply engrossed in exploring the enigmatic world of AI, particularly how machines perceive and influence our world.

At the heart of my current exploration is computer vision and machine learning, realms where I am passionately investigating how machines understand visual data. My research is geared towards developing architectures that learn efficiently from minimal data, employing advanced methodologies like few-shot learning. This pursuit aligns with my overarching goal of contributing to the sphere of artificial general intelligence.

A significant aspect of my expertise lies in deploying machine learning models in the cloud. I am fascinated by and skilled in creating scalable, serverless applications, drawing inspiration from industry pioneers like Meta and Google. Their proficiency in developing systems that seamlessly serve millions of users worldwide serves as a benchmark in my professional aspirations.

Technical Expertise and Tools:

Core Areas: Deep Learning, Machine Learning, Computer Vision, Data Science, and ML Model Deployment in the Cloud.
Programming Languages:Proficient in Python, Knowledgeable in Java, C, C++, HTML/CSS, and Bash.
Tools & Technologies: Proficient with TensorFlow, PyTorch, Docker, Kubernetes, Cuda, Distributed Training, PyTorch Lightning, Git, Linux, OpenCV, CSS, React, AJAX, JQuery, Scikit-Learn, Pandas, Flask, SQLAlchemy, Nginx, MLOps, AWS, Sagemaker, Lambda, and other cloud-related technologies.
Databases: MySQL, PostgreSQL, Cassandra
Soft Skills: Strong in Analytical Thinking, Research, Problem-Solving, and Team Collaboration.

I am on a continuous quest for challenging opportunities in the fields of computer vision, machine learning, deep learning, and particularly in the deployment of these technologies in the cloud. My aspiration is to collaborate with a team that shares my enthusiasm for pushing the boundaries of AI and its practical applications.

Embark with me on this exciting journey, as we leverage the transformative power of AI and cloud technology to reshape our understanding and interaction with the digital world.

Experience

CAVS

Research Assistant

Conducting advanced research in computer vision, specifically in image restoration using generative models like diffusion models, pix2pix. .
Skills: Object Detection · Machine Learning Algorithms · Research · Applied Machine Learning · Deep Learning · Amazon Web Services (AWS) · PyTorch

August 2023 - Present | Starkville, USA

Proxmed

Machine Learning Engineer

Spearheaded the research and development of advanced AI models for detecting and classifying brain-related diseases, including Large Vessel Occlusion (LVO), and hypodensity, with deep learning models like YOLOv7, detectron2 enhancing diagnostic accuracy and efficiency.
Engineered and deployed robust APIs for the AI models, facilitating seamless integration into production environments. This deployment significantly improved the operational workflow and led to more reliable and rapid diagnosis of disease

Feb 2023 - August 2023 | Victoria, Australia

HeHealth

Research Scientist(3 months contract)

Pioneering Research in Synthetic Datasets: Spearheaded research initiatives on synthetic datasets derived from a limited number of authentic disease images. This innovative approach focused on enhancing data availability for robust model training, particularly in scenarios with scarce real-world data.
Development of GANs for Disease Image Generation: Played a crucial role in designing and developing Generative Adversarial Networks (GANs). These models were adept at producing high-quality synthetic disease images. The use of these GAN-generated images was instrumental in significantly elevating the accuracy of disease identification models. This breakthrough demonstrated the potential of GANs in overcoming data limitations in medical imaging.
Leadership and Training: As the team leader, led a group of researchers and developers in applying this cutting-edge research to product development. Additionally, undertook the responsibility of trainer, imparting essential skills and knowledge related to GANs and synthetic dataset utilization. This role encompassed mentoring the team to efficiently translate research findings into practical, market-ready healthcare solutions.

Feb - April 2022 | San Francisco, CA

Janabhawana Campus
Tribhuvan University's affiliate

Lecturer

Taught Bachelor In Computer Application.

Spring 2022
- CACS354 - Advance Java Programming (3 cr)
- CACS355 - Network Programming with Java (3 cr)

Summer 2022
- CACS204 - Object Oriented Java Programming (3 cr)
- CACS402 - Cloud Computing (3 cr)
- CACS456 - Machine Learning (3 cr)

Spring 2023
- CACS354 - Advance Java Programming (3 cr)
- CACS355 - Network Programming with Java (3 cr)

Dec 2021 - June 2023 | Lalitpur, Nepal

Wiseyak

Machine Learning/Computer Vision Engineer

Work under the Prof. Dr. Suresh Manandhar
Collaborated as a key member of an international team specializing in the research and design of machine learning and computer vision solutions for healthcare applications.
Led the development of APIs and user interfaces for disease recognition models, enhancing the usability and accessibility of machine learning tools in medical diagnostics.
Engineered a custom Machine Learning Pipeline tailored for medical image diagnosis, enabling dynamic, user-driven model training online for various diseases.
Innovatively researched and developed a Deep Learning Medical Image Diagnosis Model, achieving significant performance improvements in detecting diabetic retinopathy, skin lesions, and lung diseases.

Oct 2020 - Oct 2021 | Bellevue - WA , USA

NAAMII

Machine Learning Research Intern

Work under the Prof. Dr. Suresh Manandhar
Developing language models to improve offline handwritten recognition tasks
Synthesize handwritten images with GAN.

Used of different types of GAN like Cycle GAN, Text2Image GAN, and Variational Encoder

Jan 2020 - June 2020 | Kathmandu, Nepal

Mpercept

Machine Learning Engineer Intern

I Collaborated with a multidisciplinary product development team to identify performance improvement opportunities and integrate trained models
Analyzed the data of customers, and performed customer segmentation, and built the predictive model to recommend products based on purchase history.
I maintained, developed source code, and led a team of more than 3 people.

June - Dec 2019 | Kathmandu, Nepal

PROJECTS

Deep Learning Projects

                
Handwritten Detection
                  Handwritten Line Text Recognition using Deep Learning with Tensorflow
                
AccomplishmentsTools: Flask, HTML, CSS, Bootstrap, Tensorflow, OpenCV
This is my major project which I do with quiet research and found the state-of-the-art
                    architecture for real-time handwritten recognition with CER 4.32%.
Uses CNN, LSTM, CTC loss function and trained on an IAM dataset with a self-created dataset that
                    can detect
                    handwritten text in real-time.
Perform data augmentation to make a robust model and improve accuracy.
Also make some changes on the current architecture which is able to detect handwritten images in
                    Devnagari
                    Script with CER 8.32%.

Nepali Handwritten Detection
                  Nepali Handwritten Line Text Recognition using Deep Learning with Tensorflow
                
AccomplishmentsTools: Flask, HTML, CSS, Bootstrap, Tensorflow, OpenCV 
This is my major project which I do with quiet research and found the state-of-the-art
                    architecture for real-time handwritten recognition with CER 4.32%.
Uses CNN, LSTM, CTC loss function and trained on an IAM dataset with a self-created dataset that
                    can detect
                    handwritten text in real-time.
Perform data augmentation to make a robust model and improve accuracy.
Also make some changes on the current architecture which is able to detect Nepali handwritten
                    images in Devnagari
                    Script with CER 10.32%.

Neural Style Transfer
                  Neural Style Transfer Paper Implementation with PyTorch.
                
AccomplishmentsNeural Style Transfer Paper Implemenation with PyTorch
Try to go through all the techniques mentioned in the [paper](https://arxiv.org/abs/1508.06576) .
                  
Nepali Poem Generation
                  A Nepali POEM Generation using AI
                
AccomplishmentsTools: Numpy, Tensorflow, keras, NLP
This project use the char-rnn model.
 Train on Nepali POEM by Adikabi "Laxmi Prasad Devkota" who is pioneer in Nepali Literature with
                    more than 200k characters.
The char-RNN model is here used to generate the Nepali Poem 
Accuracy will be increase if more amount of data is available.

Reverse Image Search Engine with Python
                  Reverse Search Engine with Transfer Learning and K nearest-neighbors.
                
AccomplishmentsTools: Numpy, Scikit-learn,Tensorflow v2, Flask
Image Search Engine using Deep Learning Model (ResNet50)
                  
Use ResNet=50 model to extract features from Caltech101 datasets, train a K nearest-neighbors
                    model using the brute-force algorithm to find the nearest n neighbors based on Euclidean distance.
                  
Based on less distance, top n images are returned.
 Also some analysis on how to increase speed and accuracy is given.

Celebrity Face Image Generation with GANs
                  Fake Celebrity face image generation with DCGAN trained on Kaggle Celebrities 100k Dataset.
                
AccomplishmentsTools: Python, PyTorch
Architecture: DCGAN
DCGAN Paper Implementation with some improvements
Trained for 60 epochs, output is satisfactory

Music Generation with AI
                  A simple and extensible generating Music with Char ABC notation similar to Irish folk song with LSTM
                  in Keras.
                
AccomplishmentsTools: Python, Keras, cuda
Trained with char ABC notation with char rnn model
Accuracy: 80% and loss: 0.6

Self-Driving Car Projects
                  This project simulates the autopilot's key function of predicting steering angle using the front picture of the car as input. 
                
AccomplishmentsTools: Python, PyTorch, OpenCV
Train an End-to-End Architecture for steering angle prediction.

Other Projects

Encryption And Decryption

A simple and powerful Encryption and Decryption Application with own ASCII shifting algorithm.

Accomplishments

Tools: JAVA, Swing
ALL the main logic is that read the ASCII value of the each character of the string and shift (add) the ASCII value by the key + extra value and in decryption remove the extra value by the given key + extra value to extract the original information

Wave Simulation in C++

Wave Simulation application in C++, that performs various operations between signals and display with graphics library.

Accomplishments

Tools: C++, Graphics.h, Codeblocks

Blog Posts & Paper Reading

                  Blog Posts
                
                      In my free time, I usually create blog posts on fascinating deep learning and computer vision studies that go into extensive detail about ideas, architecture, and mathematical equations.                    
View all posts

                  Annotated papers
                
                  I annotated numerous interesting computer vision papers, particularly GANs and Vision Transformers, by providing an overview of each with details in mathematical calculations.                
                
Read more

                Paper Scratch Implementation
              
                Deep Learning Paper Scratch Implementation with PyTorch & Tensorflow.  
              
Read more

Skills

Languages and Databases

Python

HTML5

CSS3

MySQL

PostgreSQL

Shell Scripting

Libraries

NumPy

Pandas

OpenCV

scikit-learn

matplotlib

Frameworks

Django

Flask

Bootstrap

Keras

TensorFlow

PyTorch

Other

Git

AWS ML

CI/CD

Certificates

Deep Learning Specialization Certificate

Applied Machine Learning In Python Certificate

Extensive MLOps course conducted by the School of AI. Skills I learned are: Docker · Kubeflow · kafka · Data version control · ML Models Deployment · Model Explanation(XAI Methods) · Distributed CUDA Training · PyTorch Lightning · Automated Machine Learning (AutoML) · Continuous Integration and Continuous Delivery (CI/CD) · AWS Lambda · AWS SageMaker · Computer Vision
Course Project Repository

Machine Learning Specialization Certificate

Orchestrating the Cloud with Kubernetes (AWS)

Education

Mississippi State University

2023-2025| Starkville, USA

Degree:Masters In Computer Science(Thesis Track)
Concentration: Artificial Intelligence
Relevant Coursework: Algorithms, Machine Learning, AI Robotics
GPA: 4.0

2023-Present | Starkville, USA

Tribhuvan University

2015-2019 | Kathmandu, Nepal

Degree: Bachelor In Computer Engineering
Grade: A

Accomplishments

For four years during my undergraduate studies, I received a merit-based scholarship for outstanding academic excellence.
Completed Undergraduate In Computer Engineering with Distinction.
Topper of my Batch in my University
First position in instant software competition in my university.

Relevant Courseworks:

Data Structures and Algorithms
Database Management Systems
Operating Systems
Artificial Intelligence
Digital Image Processing And Pattern Recogntion
Big Data Technologies
Advance Mathematics
Probability And Statistics

2015-2019 | Kathmandu, Nepal

Contact

+xxxxxxxxxx

sushantgautm@gmail.com

github.com/sushant097

linkedin.com/in/susan-gautam

https://sushantgautm.medium.com/