• Hi!
    I'm Fenil

    A budding Computer Engineer with an interest in Machine Learning, Software Development, Algorithms and Mathematics.

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About Us

Who Am I?

Hi, I'm Fenil Doshi I am a Software Engineer at Slack with over 2 years of experience. I did my Master's in Computer Science at University of Massachussets, Amherst. I have pursued BE in Computer Engineering from Dwarkadas J. Sanghvi College Of Engineering, Mumbai University.

I love Machine Learning, Mathematics, Competitive programming, developing softwares, playing chess and reading. Each passing day I try to improve upon myself. Predominantly, I have an interest and experience in the following domains in Computer Science:

Machine Learning and AI

Software Engineering

Data         Engineering

Web and App Development

Cups of coffee
Research Papers
Internships
Projects
My Specialty

My Skills

I have always had a passion for Mathematics. During my junior years, I was interested in Development, particularly Web and Android. Later on, I became fascinated with Machine Learning. Consequently, I completed a number of courses on Machine Learning (Machine Learning by Andrew Ng, Deep Learning Specialization, Bayesian Learning, Probabilistic Graphical Models by Prof. Daphne Koller, Reinforcement Learning by Prof. David Silver, etc.). Currently, my primary interest lies in Software Development and using Machine Learning in the fields of Computer Vision and Natural Language Processing. I have work experience in both of these domains. I also love Data Structures and Algorithms and love participating in coding competitions. I regularly do competitive programming on Leetcode (https://leetcode.com/fenil25/), Codechef and Hackerrank.

I code in Python, Scala, Java, Go, Javascript, C and C++. I have worked on non-relational (MongoDB, Firebase Cloud Database) as well as Relational (Vitess, SQLite, MySQL, PostgreSQL) databases. I have experience in using softwares like Android Studio, Dialogflow, etc. I have developed websites and webapps using HTML, CSS, React.js, Redux, Node,js, Django, Flask, PHP, etc. I am also familiar with libraries like Tensorflow, Keras, Pytorch, OpenCV, NLTK, PyMC3, Seaborn, etc. During my work, internships and projects, I extensively worked with tools and platforms like Google Cloud Platform, AWS, Kubernetes, Docker, Github, Datadog, Grafana, etc.

Currently, at Slack, I work as part of Data Ingestion team where we bring data fram various sources into the data-warehouse. I regularly work with tools like Airflow, AWS EMR, Jenkins, Kubernetes, S3, EC2 instances, etc. Working in the team, I gained experience with Golang, Scala, Python, Java and distributed programming with Spark, and Flink. Moreover, I worked on the project to modernize our data-warehouse by incorporating streaming using Apache Kafka and using modern data storage formats like Apache Hudi and Iceberg.

Education

Education

I pursued my Master's in Computer Science at University of Massachussets, Amherst. I took courses like - Systems for Data Science, Advanced Algorithms, Intelligent Visual Computing, Advanced Natural Language Processing, Advanced Machine Learning, Reinforcement Learning, etc.

CGPA: 4.0/4.0

I also acted as a grader for Advanced Algorithms and Advanced Machine Learning classes.

I completed my Bachelor's degree in Computer Engineering from Dwarkadas J. Sanghvi College of Engineering, Mumbai University. My score in the semesters are as follows:

CGPA: 9.71/10

I was ranked first in the entire Mumbai University in 3rd, 4th, 6th, 7th and 8th Semesters and second in 5th Semester.

I undertook Science, and studied at Pace Junior Science College. I secured a percentage of 88.90%. Overall, I was in top 5 percentile and was ranked 1st in Mathematics in the college.

I studied at Friend's High School where in 10th Std, I scored 95.40%. Overall, I was ranked 2nd in the entire school and topped in Mathematics and Science.

Experience

Work Experience

Software Engineer at Slack Feb 2023-Present

Slack is a messaging app for business that connects people to the information they need.

I currently work as a Software Engineer in the Data Ingestion team at Slack. The team is responsible for getting data from various sources into Slack’s data warehouse. I worked on the project to modernise the data warehouse by introducing streaming technologies like Apache Kafka and Flink and transitioning from Hive to modern data storage formats like Apache Hudi and Iceberg. This helped reduce the data landing time from 24 hrs to 10 minutes, enabling faster data insights and saving $2M annually. I also worked on ingesting Quip’s data into Slack’s data warehouse and maintained the AWS infrastructure supporting the ingestion of petabytes of data daily.

Software Engineer Intern at Slack May 2022-August 2022

Slack is a messaging app for business that connects people to the information they need.

I worked as a Software Engineering Intern with the Data Engineering Team. I developed a Data Lineage visualization system that tracks the flow of data within Slack. While working on it, I also simultaneously contributed to OpenLineage (an open-source project) to track the data lineage from the Airflow DAGs. The system comprises a backend server made with FastAPI that queries Postgres tables and the frontend uses React.js and Cytoscape to render the visualization graph. The system is deployed using Amazon Web Services (AWS) and helps the teams to notify all the downstream users after detecting errors in some task or table.

Software Engineer Intern at Unity Technologies May 2021-August 2021

Unity Technologies is an American video game software development company based in San Francisco.

I programmed a monthly cron job using Golang, that periodically deletes all the inactive monetary targets for advertisement units that do not generate impressions for the game developers. The service reads all the floors from Bigtable and computes the inactive floors. This data is written to Google Cloud storage and published over via NATS to different services. I also worked on the subscriber part which receives the inactive floors and deletes them from the MongoDB database using Javascript. Using optimized data retrieval and parallel processing, brought down the runtime of service from 9 days to 6 hours. Deleting all the inactive floors saves around $300K in storage and processing costs for the company, every year.

Machine Learning Engineer at Clutterbot June 2020-December 2020

Clutterbot deals with creating a robot that helps people in tidying rooms and organizing things at home.

At Clutterbot, I worked on Monocular and Stereo Depth Estimation using Deep Learning on Embedded systems. This aids the robot in the preception pipeline to know the map of environment. I performed various optimizations on the inference model so that it can work in real-time under constrained environments. I also worked on calibrating camera for a custom dataset in order to obtain disparity maps from depth maps.

Machine Learning Enginnering Intern at Fusion Engineering June 2019-August 2019

Fusion Engineering is a service-based company that develops mobile application on iOS platform.

I worked on Optical Music Recognition focussing on reading printed sheet music from images and converting it to human-readable format. I modified the existing dataset by adding camera-noise to reflect real-world data and recognized notes and their positions corresponding to clefs and staff lines using object detection and image processing techniques.

Software Developer Intern at Speridian Technologies June 2018-July 2018

Speridian Technologies is a global company that provides technical consultancy and provides IT-services to clients to modernize their business.

Worked as a full time intern and co-ordinated with an international team for 2 months on frontend development. My work primarily included developing webpages using React.js and Redux for multiple live projects. I created webpages for tracking products using barcodes and developed a production management system.

Software Developer Intern at Symphony October 2017- June 2018

Symphony is a music social network startup that connects people with similar music tastes and provides song recommendations to users. It won the People's Choice award at Rice Business Plan Competition at Rice University, Texas and the Chatbot was voted one of the most useful features by the users.

I developed a Chatbot that recommends music to the user based on user's interest, mood, weather, activity, genre, latest trends, etc. It also does small talk, tells joke, conducts music quizzes and provides news related to music industry. The chatbot was developed with Dialogflow using Node.js and Firebase for storage.

My Projects

Recent Projects

PoxelNet

3D Deep Learning Project

Created a Deep learning model for classifying 3D shapes using Point based and Volumetric approaches. The model - PoxelNet achieves an accuracy of 89% on ModelNet40 dataset.

Map Reduce System

Distributed Processing Project

Developed a fault-tolerant system similar to Hadoop, that can run arbitrary user-defined Map-Reduce programs efficiently. The program partitions user-provided data and spawns multiple processes to run Map and Reduce function on each partition. Implemented parallel processing and enabled inter-process communication using sockets.

Virtual Dressing Room

Research Project

Modified the image with text using conditional Generative Adversarial Networks (GANs). Trained the network with a text-adaptive Discriminator and a novel Bilinear residual layer to effectively merge image and text represenations. Also, created a Django-Application that allows user to modify the color, style and size of user outfits using the trained model.

Normalizing Text with Language Modelling using Phonetics and String Similarity

Research Project

Worked on converting SMS text to normlaized English language using Masked language modelling. Created a custom score based on string and phonetics similarity and our unique word-by-word masking approach achieved an accuracy of 86.7% on human-based evaluation.

Stock Manager

Web Application

A web application that gives trends and predicts prices of stocks (using a trained RNN network) based on the previous history and allows you to buy and sell stocks and other currencies with virtual money at real-time prices.

Book Recommender System

Website

A system that recommends books based on user’s preferences. It also provides search and ability to read the books on-site using Google Books API.

Automated Event Application Screening

Web Application

Using NLP Techniques, the application sorts out people on the basis of skills required by the organizer by going through the resume, GitHub and Quora accounts of the applicant by assigning individual scores on a scale of 100.

News Classification using Stance Detection

Research Project

A Deep Learning Algorithm using Word Embeddings and LSTM network that classifies a headline and article based on their stances. Furthered the research in this area by using novel architectures such as Temporal Convolutional Networks and Embeddings such as Bert, XLNet.

Refugee Database System

Web Application

Django based database system for storing information on refugees around the world. Web App also allows raising petitions and register NGOs for helping refugees.

Word Search Game

Android Application

Word Search game using Tries where the user forms a connected English word from a random matrix of letters in a fixed time limit and is scored accordingly.

Book Exchange Portal

Web Application

A Book Exchange portal that facilitates exchange of books among students of our college. It also includes student forums for discussing doubts and other student queries.

2-Player Checkers

Game

A 2-player Checkers game made from scratch using React.js. The game also suggests possible moves to the player.

  Play Game

Extras

Extra Curriculars

Unicode
Sept 2017 - Sept 2020 | Website Development

Developer and Mentor at Unicode

Unicode is a student chapter aimed at nurturing the culture of open-source development among the students.

At Unicode, during the second year, I was a frontend developer where I developed the Book Exchange portal. I also mentored a team of 20+ juniors over the course of 2 years and headed the development of a Canteen Application to ease the ordering system at the college canteen.

CVIT
August 2019 | Computer Vision

Attended Computer Vision Summer School (CVIT) at IIIT-Hyderabad

I was selected to attend the 8-day summer school at IIIT-Hyderabad (CVIT). I learnt a lot in the field of Computer Vision and also got to interact with Prof. Narendra Ahuja, Prof. Pulkit Agrawal, Prof. C.V Javahar, etc. and got to know about the latest research in the field of Pattern Recognition, einforcement Learning, Computer Vision, etc..

Codestars
Nov 2018 - Sept 2020 | Competitive Programming

Technical Head at Codestars

CodeStars is a committee that focusses on developing the programming skills in students and promotes the spirit of competitive programming.

My work primarily included- conducting lectures on Data Structures, Number Theory, Algorithms, etc. and creating coding problems for monthly contest on Hackerrank. Many of our students represented the college in coding competitions like ICPC accross the nation.

Get in Touch

Contact

fenilmdoshi98@gmail.com

San Francisco, CA 94107, United States

+1 (413)-379-4990