Ashwin-Profile

Hi, I'm Ashwin Chafale.

Introducing myself as :

Self-driven, quick starter & passionate programmer with a curious mind who enjoys solving complex and challenging real-world problems.

Actively looking for an opportunity to work as a :

Actively looking for an opportunity to work as a :

About

I am a Computer Science Grad Student at University of Southern California.

Languages: Python, Java, JavaScript, C, C++, HTML/CSS, Bash
Databases: MySQL, PostgreSQL, MongoDB
Libraries: NumPy, Pandas, OpenCV
Frameworks: Flask, Django, Node.js, Keras, TensorFlow, PyTorch, Bootstrap, Apache Beam
Tools & Technologies: Git, Docker, AWS, GCP, Heroku, JIRA

Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.

Experience

Apple

Data Engineering Intern

Developed and maintained aggregated ETL pipelines using Spark SQL and PySpark on Hadoop file systems as part of Apple's Health Software team.
Build an end-to-end data application that would allow QA/QE teams to validate the user data or detect anomalies in the user data streams uploaded by the research health app.
Processed 10 TB of large data in a distributed parallel computing architecture and extracted meaningful features from it to promote data analytics.
Responsible for scheduling, maintaining, and orchestration of data pipeline using Apache Airflow.
Skills: Data Modeling, Data Analytics & Visualization, Workflow orchestration, and ETL processes

May 2022 - Aug 2022 | Sunnyvale, CA, USA

Amazon

DevOps Contractor

Implemented static code analysis recommendation rules in Java for python files to improve code quality, application performance and detect code smells in repositories. The detection percentage of the python rules was 78 % in the amazon GitHub repository.
Incorporated unit test in JUnit cases to validate python rules.
Led junior software engineering interns and collaborated with the Amazon Codeguru Seattle team for proper implementation and testing of python rules.

April 2021 - June 2022 | India - Remote

Mtag Innovations

Software Developer

Programmed a cloud-based web app using Flask and JavaScript aimed at storing, visualizing, and tracking temperature and humidity of each drug container to estimate the degradation of the drug.
Created an alert system to send notifications and emails when the parameters exceed the threshold.
Tools: Python, Flask, JavaScript

July 2018 - Nov 2018 | Ahmedabad, India

CIGNEX Datamatics

Project Trainee

Designed a library management system for a local library, where we undertook activities like requirement elicitation, preparing Data Flow and Entity-Relationship diagrams.
Delivered a solution for a POC involving Automatic Financial Document Classifier using Natural Language Processing and Support Vector Machines with 96% accuracy on the company’s data.
Tools: Python, Scikit-learn, NLTK

June 2017 - July 2017 | Ahmedabad, India

Projects

                
Music Player Web-App
                  A music streaming web app based on Django
                
AccomplishmentsTools: Django, HTML, CSS, Bootstrap, SQLite, AWS S3, Heroku
Register/login to the web app(with OAuth-based Google Sign-In).
Search and filter songs based on language and singer.
Create multiple playlists and add/remove songs to/from playlist.
Scroll through recently played/viewed songs.

Quiz Web-App
                  A quiz playing web app based on Django
                
AccomplishmentsTools: Django, HTML, CSS, Bootstrap, SQLite, Heroku
Register/login to the web app(with OAuth-based Google Sign-In).
Play Quiz and see the leaderboard

Blog Web-App
                  A simple and extensible blog web-app based on Flask.
                
AccomplishmentsTools: HTML, CSS, Bootstrap, Flask, SQLAlchemy, Postgresql, Python
Users can view posts and contact the admin via Contact Page.
Admin can Add, Delete, Update posts.

Visual Question Answering
                  An attention-based classification model that aims at generating an answer for a given input image.
                
AccomplishmentsIncorporated Convolution Neural Networks (CNN) for extracting image features and Long Short Term
                    Memory for extracting question
                    embeddings.
Tested the model on the COCO dataset, abstract scenes images, and got 69% overall accuracy on the
                    VQA evaluation metric.

Video Summarizer
                  A Seq2Seq model that generates a short summary of the given input video.
                
AccomplishmentsIncorporated CNN to detect and classify objects in the video frames and Long Short Term Memory for
                    generating a summary.
Evaluated the model on MSVD (Microsoft Video Description Corpus) dataset; achieved 0.77, 0.71,
                    0.52 scores respectively on ROGUE,
                    BLEU, METEOR evaluation metrics.

Image Generator
                  An image generator based on the concept of adversarial networks (GANs)
                
AccomplishmentsDeveloped system was tested on a human-face database and loss was calculated by comparing the PCAs
                    of generated and original image.
Calculated difference in PCA was less than 10%, depicting the successful generation of an image by
                    the generator.

Head Counting System
                  A system that calculates the attendance of the class from a panoramic image of a live classroom.
                
AccomplishmentsUsed Singular Value Decomposition for image compression; applied various image processing
                    techniques and morphological operations to
                    detect the number of heads.