I'm a Software Engineer based in NYC who loves exploring new places. I was born in Boston and have lived in Singapore, Lucknow, Chicago, and Cupertino after which I went to high school in Noida. Scroll down to learn more about the projects I've worked on.
Utkarsh Jain
(608)504-1332
utkarshj1303@gmail.com
BS in Computer Science
GPA: 4.0/4.0
2017- 2019
Relevant Coursework :
CS 540 Introduction to Artificial Intelligence
CS 506 Software Engineering
ECON 101 Principles of Microeconomics
CS 354 Machine Organization and Programming
CS 368 Learning a Programming Language (MATLAB)
CS 766 Computer Vision (Graduate)
CS 567 Medical Image Analysis
CS 532 Matrix Methods in Machine Learning
CS 640 Introduction to Computer Networks
CS 576 Introduction to Bioinformatics
CS 639 Data Management For Data Science
CS 537 Intro to Operating Systems
CS 435 Introduction to Cryptography
B.Tech Computer Science • 2015 - 2017
Delhi Technological University is consistently ranked amongst the top 10 engineering colleges in India ( Rank 7 (India Today) , Rank 8 (Shiksha.com) , Rank 9 (Getmyuni.com) ). Only students with a rank of under 5000 out of 1,500,000 in the JEE Main exam get admitted to the Computer Science major at Delhi Technological University.
Relevant Coursework :
CO 101 Programming Fundamentals
CO 201 Data Structures
CO 203 Object Oriented Programming
CO 205 Discrete Mathematics
CO 208 Design and Analysis of Algorithms
CO 202 Database Management Systems
CO 204 Operating System Design
EC 261 Analog Electronics
EC 262 Digital Electronics
CO 206 Computer Organization and Architecture
Massive Open Online Courses
Deep Learning Specialization - Convolutional Neural Networks (Coursera) - Certificate
Become an Android Developer from Scratch (Udemy) - Certificate
Machine Learning (Coursera)
Algorithms: Design and Analysis, Part 1 (Coursera)
Software Engineer • October 2022 - Present
• Part of the OMS team which is responsible for a system used to create advertising campaigns for clients.
• Designed and implemented a custom Google Drive-like system from scratch along with another team member, closely working with and receiving constant feedback from the product team. This was part of a wider project which helped users manage advertising campaigns exceeding $750k directly from OMS.
• Collaborated closely with Amazon’s DSP team to build a widget in OMS which allowed users to push goals and optimization information for managed advertising campaigns to the DSP.
• Extended OMS’s campaign approval workflow to the EU region by adding additional stages and rules required for the region.
• Onboarded and mentored a new team member by giving her code walk throughs, planning initial tasks designed to help familiarize her with the code base, and setting up a recurring 1:1 to answer questions.
Software Engineer • September 2021 - June 2022
• Worked on the Messaging team which manages the Apache Kafka infrastructure at Twitter and provides API's to internal clients to help them effectively use Kafka for their needs.
• Created dashboards to help customers get a better insight into the performance of their Kafka Connect instances.
• Helped automate a tedious workflow which helped customers quickly deploy Kafka Connect instances by themselves.
• Rapidly on-boarded and participated in on-call shifts where I independently closed most of the pages assigned to me.
Software Engineer • August 2019 - September 2021
• Worked on the AIM OTE team which built the frontend and backend for the entry points to Bloomberg’s buy-side portfolio management solutions.
• Identified bottlenecks by analyzing performance of our main service for different service configurations (number of threads, instances etc) under various loads
• Helped increase the throughput of our main I/O bound C++17 service 3x by reducing slow service calls.
• Contributed to a dashboard for monitoring service throughput.
• Gained a lot of experience in debugging legacy C++ services through quarterly sprint long rotations where I was responsible for all incoming client bugs.
• Contributed to the migration effort from our old to new stack by adding various features/fixing bugs.
• Took various internal technical courses including a course in modern C++ and an initial 1.5 month long boot camp which included various topics including Python, Javascript, C++.
Software Engineering Intern • June 2018 - August 2018
• Learnt about options pricing theory during an intensive one week course during the first week of my internship.
• Solely responsible for building a vital application for traders in Java. The application displayed information to the traders which was crucial for making decisions about CTC's markets. Traders were very excited to use the application and it was put into production by the end of my internship.
• The project consisted of a backend where information was gathered and certain values were calculated and a UI which displayed the infomation to the traders using heatmaps.
• The project helped me learn about the best practices for writing event driven applications in Java. I used Google Proto Buffers, Java Immutables Library, Java Swing, Netty, Git, Gerrit and Jenkins as well as CTC's internal tools and frameworks.
Spring 2018
I held weekly office hours to help students with the concepts and homework assignments of CS 540 Introduction to Artificial Intelligence.
Project Chaap Member • Aug 2015 - Oct 2016
The objective of Project Chaap is to empower women socially and economically by training them in screen printing on tee shirts and thereby help them set up an independent business. It was inspiring to see how this work enabled the women to bring similar benefits to the lives of other women by employing them in their business. As a part of Project Chaap, I worked in a team and we helped the women set up their business by finding suitable suppliers for tshirts, paint etc; setting up training workshops and getting orders for them from various colleges.
During my undergrad, I actively participated in the long challenges hosted on Codechef every month. I primarily use C++ while participating in contests. Some of my competitive programming profiles and achievements are listed below.
•Rating: 1688, Codechef
•Rank 74/2811, OpenBracket Delaware - Invited to Onsite Round
•Rank 615/11390, Codechef SNCKPB17
•Google Kickstart Practice Round 2018 - Rank 260
I developed a web app that helps groups find new restaurants catering to everyone's preferences, using Anthropic's Claude Haiku and Perplexity's online LLM API. As shown in the demo above, a user can log in and set up a profile with their location and preferences/dietary restrictions. They can then create a chat with their friends in which they specify the location, price range and preferences/restrictions (which are initially populated with each member’s preferences) for the group. After this, each member of the group can individually chat with the AI which takes the group preferences into account while responding with personalized suggestions to each individual member. To suggest something to the wider group, the user can click on the suggestions within the response and a pin with their profile picture pops up on the adjacent map which can be seen by everyone else. User’s can click on the pins to learn more about the restaurant and assign ranks to their top choices. The idea is to make the whole process as simple as possible while still enabling individual creativity.
I use Claude Haiku to craft a search query to Perplexity’s online LLM API given the group’s preferences, a summary of the conversation so far and the latest prompt from the user. Another instance of Claude Haiku then parses Perplexity’s response into JSON and provides an updated summary of the conversation. The app was built using NextJS, Vercel, Typescript, and Tailwind CSS.
Meshiagare
Github Repository
Chirayu Garg and I implemented a variation of the algorithm described in the paper Howard, Andrew. “Real-time stereo visual odometry for autonomous ground vehicles.” (2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (2008)) using Python and OpenCV 3.0. The aim of the project was to plot the trajectory of a moving vehicle using a sequence of images captured by a camera on top of the vehicle. The demo video above shows the trajectory plotted by our algorithm for the vehicle shown on the right.
Github Repository
My proposal for an Android application that helps the students of UW-Madison choose courses that align with their interests and fulfill the degree requirements of their major was chosen as one of the top 20 projects out of 130 and was developed by me and team of students in CS 506. Academic Advisor is an Android application that aggregates data from the UW Course Guide, Rate My Professors and UW Madison Course Grade Distribution. The app generates a list of courses based on the users selected range of professor rating, range of average gpa and L&S requirement which they wish to satisfy. This was submitted as the final project for UW - Madison's CS 506 Software Engineering course. The project consists of an Android application and a server which starts the scrapers and then stores the scraped data in a database which the Android application then queries. A major part of my work on the project was developing the scrapers for Rate My Professors and the UW Madison Course Guide. I wrote the Course Guide Scraper in Python and the Rate My Professors scraper in Java. The video above shows my Course Guide scraper in action. It automatically opens the Course Guide page, goes through the list of subjects and scrapes the information from the page and stores it in JSON format. The pictures to the left of the video are screenshots of the final Android application.
Github Repository
One of the many cool things I learned in the Convolutional Neural Networks course on Coursera was how to use use neural networks to transfer the style of one image onto another.
Github Repository
For my final project in CS 567 Medical Image Analysis, I implemented a classifier in MATLAB that differentiates between healthy and retinopathy retinas. I used various image analysis techniques to extract features unique to the retinopathy retinas and then used KNN and Logistic Regression for cross validation.
Github Repository
Panorama stitching, object tracking, and boundary detection are just some of the cool things I learned how to do in CS 766 Computer Vision. Above are pictures and a video of the output of some of my homework assignments from CS 766.