rohit-swami / portfolio Resume

portfolio README.md

Systems that hold up at 3am.

I'm the engineer you hand the thing that's on fire. The pipeline that takes 22 minutes, the graph too big to render, the service that dies under real traffic. Five and a half years of turning those into things that are fast, boring and still running. Fifty-odd of them now in production.

Selected impact

  • 22 min → <1 min KEGG pathway rendering, with UI latency from 15 minutes to under a second
  • 10× faster Graph engine rebuilt from R to Python/Polars, on 80% less memory, scaled to 100K+ entities
  • 28% cheaper AWS Batch pipelines running 10,000+ jobs a month on a spot/on-demand mix
  • <100 ms Redis + WebSocket notification microservice, at production scale
  • 70% less Manual effort on OMOP table mapping, via a React + Next.js + FastAPI platform

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About

Engineer, mentor, and hands-on architect

I build the unglamorous machinery real products run on. Across 5.5+ years and 50+ production projects the pattern is usually the same: something slow, fragile or expensive comes in, and something fast, boring and cheap goes out.

What I build

  • Low-latency microservices and APIs that hold under real traffic
  • Data pipelines that survive production volume, not just the demo
  • Real-time infrastructure on Redis and WebSocket
  • GenAI systems with LLMs and RAG, shipped rather than prototyped

How I work

  • Profile first, then optimise. Guessing is expensive
  • Own it end to end: infrastructure, CI/CD, and the 3am page
  • Test automation and code review as defaults, not afterthoughts
  • The security work nobody volunteers for, including HIPAA and GDPR

Where I'm headed

  • A hands-on tech lead role, owning architecture without leaving the code
  • Teams that ship, measure, and fix what the numbers show
  • More mentoring. It is the part I would keep above everything else

Technical skills

Languages & scripting
PythonTypeScriptJavaScript (ES6+)SQLRBashGoHTML/CSSData Structures & Algorithms
Cloud (AWS)
EC2AWS BatchLambdaEKSS3RDS / AuroraDynamoDBAPI GatewayStep FunctionsSQS / SNSCloudWatchVPC
DevOps & infrastructure
DockerKubernetesTerraformAWS CDKCloudFormationGitHub ActionsCI/CD
Data engineering
PolarsPandasParquetdbtSQLAlchemyPostgreSQLMongoDBMySQLRedis
Frameworks & frontend
FastAPIFlaskDjangoReactNext.jsNode.jsExpress.jsReduxR ShinyStreamlitWebSocketGraphQL
AI & GenAI
LLMsRAGPrompt engineeringFAISSQdrantVector databases
Testing & ways of working
PyTestJestCypressTeam leadershipArchitecture designMentoringAgileCode reviewHIPAA / GDPR

If that is the kind of engineer you are hiring, let's talk.

Experience

Where I've worked

From analysing public sentiment for the Government of India to architecting real-time microservices that process 100K+ biomedical entities per run.

  1. Senior Software Engineer

    Current

    Elucidata-New Delhi (Remote)

    Feb 2022 → Present4 yrs 7 mos

    • Rebuilt the graph engine from R to Python/Polars for 10× faster runtime, 80% less memory, scaled to 100K+ entities across 1,000+ pathways.
    • Optimised KEGG pathway rendering: runtime 22 minutes → under 1 minute, UI latency 15 minutes → under 1 second.
    • Built a production Streamlit + Python app with bi-directional S3↔EC2 sync and Elastic IP deployment, giving instant h5ad visualisation, runtime from hours to seconds.
    • Developed a React + Next.js + FastAPI platform for OMOP table mapping with PostgreSQL validation, cutting manual mapping effort by 70%.
    • Designed AWS Batch pipelines running 10,000+ jobs/month on a spot/on-demand mix, cutting infrastructure costs by 28%.
    • Architected a Redis + WebSocket microservice (EC2, VPC, CI/CD) delivering sub-100ms notifications at scale.
    • Built production Shiny apps and React/Node.js/Python POCs that powered client demos and secured new contracts.
    • Shipped production GenAI apps using LLMs, RAG and vector databases (FAISS / Qdrant) for real-time semantic search and summarisation on domain-specific data.
    • Developed 10+ interactive dashboards in R Shiny and React, including a Yale University data explorer later published in a peer-reviewed journal.
    • Diagnosed and fixed a major memory leak in tooltip rendering for 90% less memory and no more Shiny disconnects.
    • Mentored three engineers, introduced CI/CD automation (85% test coverage) and code review, cutting 40% fewer production issues.
    • Hardened infrastructure security: HIPAA/GDPR-compliant handling across S3, RDS and VPC, passing a third-party audit with zero critical findings.
    • Python
    • Polars
    • FastAPI
    • React
    • Next.js
    • AWS Batch
    • Redis
    • WebSocket
    • R Shiny
    • LLMs / RAG

  2. Software Engineer

    Ignite Solutions-Pune (Remote)

    Jan 2021 → Feb 20221 yr 2 mos

    • Built demand-forecasting pipelines (Python, Airflow) reducing MAPE by 15% for 500K retail energy meters.
    • Modelled 100M credit-card transactions, boosting upsell precision to 90% in the pilot region.
    • Created a Flask-based recruitment portal integrated with Google Workspace, cutting hiring cycle time by 30%.
    • Python
    • Airflow
    • Flask
    • Forecasting

  3. Software Engineer, Intern

    InterviewBit-Bengaluru, India

    Aug 2019 → May 202010 mos

    • Implemented an end-to-end auto-suggestion tool measuring semantic similarity between student queries and existing solutions, deployed as a REST API on AWS EC2 with a Flask backend, reducing query resolution time for 72% of students from 2 days to 13.3 minutes on average. Built a KPI dashboard on top using SQL.
    • Built an NLP tool to calculate the percentage of code vs. text in TA responses, increasing overall student–TA interaction.
    • Wrote scripts to email and migrate 1,500+ students from Flock to the open-source platform Mattermost.
    • Revamped InterviewBit's web pages and created content for Data Science, Machine Learning and Deep Learning tracks.
    • Python
    • NLP
    • Flask
    • AWS EC2
    • SQL

  4. Data Science, Intern

    upGrad-Remote

    Jun 2019 → Jul 20192 mos

    • Mentored 200+ students, providing clear, positive, line-by-line actionable feedback on their submitted projects using upGrad's code review tool for data science courses.
    • Python
    • Code review
    • Mentoring

  5. Data Analyst, Intern

    MyGov (MoEIT, India)-New Delhi (Remote)

    Jun 2018 → Jul 20182 mos

    • Analysed public sentiment on government policies and campaigns across social media.
    • Exported over 4,000 tweets with the Twitter API and built a hybrid solution classifying each tweet as positive or negative with a KNN algorithm.
    • Performed data mining operations on websites for various internal purposes.
    • Python
    • Twitter API
    • Sentiment analysis

  6. Lead Organizer

    Microsoft Student Technical Community, LPU-LPU, India

    Aug 2017 → Sep 20181 yr 2 mos

    • MSTC hosts community events guiding professionals across different technologies. It is a platform where like-minded people come together to share and learn about technology.
    • As a lead speaker, shared knowledge on front-end technologies.
    • Community
    • Public speaking
    • Front-end

Projects

Things I've built

A selection of the public ones: personal, freelance and open source. Most of the 50+ I've shipped live behind company walls. Earlier university-era work is in the archive below.

Indian Paper Currency Prediction Machine Learning

Indian Paper Currency Prediction

A CNN trained to classify the 7 types of Indian paper currency, served through a Flask app with CSRF protection and deployed on Heroku.

Jun 2020 Details
Date
June 2020
Algorithms
Convolutional Neural Network (CNN)
Technology
Python, Jupyter Notebook, Flask

Problem statement: build an app to predict Indian paper currency.

  • Collected images from search engines and trained a CNN to predict the 7 types of Indian paper currency: 10, 20, 50, 100, 200, 500 and 2000.
  • Deployed the model on Heroku with a Flask back-end and secured the app with CSRF protection.
GitHub repo Live demo
Customer Churn Prediction with PySpark Machine Learning

Customer Churn Prediction (PySpark)

Used PySpark to find the factors driving churn in a fictional music app, training on IBM Cloud to 83.87% accuracy.

Jun 2019 Details
Date
09 June 2019
Algorithms
PySpark, TF-IDF, SGDClassifier
Technology
Python, Jupyter Notebook

Problem statement: customer churn prediction from a music app using Spark.

  • Used PySpark to analyse data from a fictional music app, Sparkify, identifying the factors affecting customers most likely to churn.
  • Trained the machine learning model on IBM Cloud with an accuracy of 83.87%.
GitHub repo Read the write-up
Disaster Response Pipeline Machine Learning

Disaster Response Pipeline

An ML pipeline that classifies disaster messages from Figure Eight data and routes them to the right relief agency, deployed as a web app.

Apr 2019 Details
Date
13 April 2019
Technology
Python, Jupyter Notebook

Problem statement: building a machine learning pipeline.

  • Analysed disaster data from Figure Eight to build a model for an API that classifies disaster messages.
  • Created a machine learning pipeline to categorize events so messages can be sent to an appropriate disaster relief agency, and deployed it as a web app.
GitHub repo
ContinentInfo Python package Open Source

ContinentInfo (Python package)

A published PyPI package that returns the continent a given country belongs to. Built to learn how Python packaging works end to end.

Mar 2019 Details
Date
3 March 2019
Technology
Python
Installation
pip install ContinentInfo

Problem statement: get the name of the continent a country is located in.

  • Built a pretty simple Python package to understand how packages work on PyPI.
PyPI index
Hacktoberfest Status Checker Web

Hacktoberfest Status Checker

An open-source tool built on the GitHub REST API v3 that tells contributors where they stand on their four Hacktoberfest pull requests.

Oct 2017 Details
Date
October 2017
Technology
HTML, CSS, JavaScript, Bootstrap, Git REST API v3
Contributors
See complete list
  • Hacktoberfest is a month-long celebration of open source software in partnership with GitHub, in which participants need to make 4 pull requests across GitHub.
  • Hacktoberfest Status Checker is an open-source tool to know the status of your Hacktoberfest activities during October.
openstalk.tech
Shortto URL shortener Web

Shortto.com URL shortener

A URL shortening service hosted on AWS with a Flask back-end, built under the Microsoft Technical Community at LPU.

LPU / MSTC Details
Technology
HTML, CSS, JavaScript, Flask, Bootstrap
Contributors
Soumyajit Dutta, Biswarup Benerjee
Made under
Microsoft Technical Community, LPU
  • The project centres around developing a URL shortening service. You have long URLs that are hard to remember, so use shortTo.com to shorten them into something easy to recall.
  • Hosted on AWS with Flask in the back-end. The Bootstrap framework and JavaScript with media queries make the UX/UI responsive and interactive.
www.shortto.com
Earlier & archived projects 10

Publications

Peer-reviewed research

Four peer-reviewed papers across IEEE, ACM and international journals covering deep learning, NLP and computer vision, plus a 2025 ASMS poster co-authored with Yale University.

  1. 01
    MAD-Lib: Library Optimisation for Enhanced Metabolite Annotation

    Poster TP 476, ASMS 2025, co-authored with Yale University

    ASMS 2025 Poster TP 476 Cut manual LC-MS annotation from weeks to days
  2. 02
  3. 03
    Driver Fatigue Detection System with Mobile Notification Alarm

    International Journal of Emerging Technologies and Innovative Research (jetir.org), 5(12), 598–605

    ISSN: 2349-5162 Read paper
  4. 04
    Sentiment Analysis with Fully Supervised Speaker Diarization

    Think India Journal, 22(3), 8382–8391

    ISSN: 0971-1260 Read paper
  5. 05
    Automated Web Development: Theme Detection and Code Generation Using Mix-NLP

    ACM International Conference Proceedings Series (June 2019)

    DOI: 10.1145/3339311.3339356 Read paper

Writing

Blog posts

All posts on Medium, @rowhitswami Customer churn prediction of a music app using PySpark 4 crunching facts of the Stack Overflow Developer Survey '17

Education

Where I studied

  1. Data Scientist Nanodegree

    Udacity Aug 2018 – Jun 2019

    Verify credential

  2. B.Tech, Computer Science & Engineering

    Lovely Professional University Aug 2016 – Aug 2020

  3. 5th – 12th standard

    BSJD Convent School Mar 2008 – Mar 2016

Achievements

Certifications & hackathons

  1. Top 0.05%

    Kaggle Expert Tier

    Datasets (top 0.05%) & Notebooks (top 0.07%)

    View profile

  2. HaXplore Hackathon, IIT-BHU

    Ranked top 10 of 45+ teams

  3. 250+ DSA problems solved

    LeetCode, Codeforces & CodeChef

  4. Winner

    Hackathon 2.0

    Chandigarh DC

    View certificate

  5. IT Hackathon 2.0

    Government of Rajasthan

    View certificate

  6. IT Hackathon 4.0

    Government of Rajasthan

    View certificate

Contact

Let's build something together

Open to conversations about tech lead roles, architecture and interesting engineering problems. The fastest way to reach me is email.

[email protected] +91 80594 59498 linkedin.com/in/rowhitswami github.com/rowhitswami Hisar, Haryana, India
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