Hello, I'm
Kushagra Tandon
Software Engineer + Machine Learning
I build ML-backed products, data-driven systems, and polished full-stack apps with a focus on measurable impact.
Get To Know More
About Me
Experience
4+ years
Software Development & Research
Education
B.S. in Computer Science
Arizona State University
Class of 2026
I’m a Computer Science student at Arizona State University (Class of 2026) interested in software engineering, machine learning, and quantitative systems. I enjoy building practical solutions—everything from ML-powered web apps to tools that automate real workflows.
Recently, I’ve worked on virtual field experiences for the NSF-funded WORM Portal, ML models for credit risk and sentiment-based trading, and full-stack applications using React, Flask, and cloud deployment.
Outside of class and research, I like exploring new technologies, experimenting with data-driven trading and risk models, and collaborating on projects at the intersection of AI, finance, and user-focused design. I’m especially excited about opportunities where I can ship production code, work with real data, and learn from experienced engineers and researchers.
Right now, I’m looking for software engineering or quantitative / ML internships where I can work with real data, design systems end-to-end, and contribute to production code.
Explore My
Skills
A balanced toolkit across ML, full-stack engineering, and cloud-backed delivery.
Languages
Machine Learning & Data
Web & App Development
Databases & Cloud
Tools & Systems
Focused on production-ready Python & ML systems, full-stack web development (React/Flask), and cloud-backed deployment with real-world data and backtesting experience.
My Professional
Experience
Research Aide
ASU School of Earth & Space Exploration · Tempe, AZ
October 2023 – May 2025
- Developed virtual field experience modules for the NSF-funded WORM Portal project, enhancing user engagement.
- Collaborated with Dr. Reano and an interdisciplinary team to ensure scientific accuracy and cultural relevance.
- Integrated Indigenous knowledge frameworks into immersive educational content to create inclusive materials.
Software Development Intern
Hindustan Aeronautics Limited · India
June 2023 – August 2023
- Developed and optimized internal aerospace monitoring dashboards using HTML, CSS, JavaScript, and Java Servlets.
- Designed modular web components to simplify maintenance and enable reuse across internal tools.
- Collaborated with cross-functional engineering teams to ensure accurate real-time telemetry data.
Secretary
TEDx Club, Arizona State University · Tempe, AZ
September 2023 – Present
- Managed 30+ TEDx event meetings, coordinating logistics and documentation.
- Strengthened collaboration across 15+ team members through structured planning.
- Improved event execution efficiency and stakeholder communication with better documentation processes.
Browse My Recent
Projects
Impact-focused case studies with measurable outcomes and production-ready stacks.
Peer-to-Peer Rental App
SwiftUI marketplace with realtime booking, chat, and listings.
Tap for detailsPeer-to-Peer Rental App | SwiftUI, Firebase, MVVM
- Built a mobile app enabling users to list, book, and manage rental equipment using Firebase (Auth, Firestore, Storage).
- Designed scalable MVVM architecture with reactive UI via
@StateObject,@ObservedObject, and@Published. - Integrated real-time booking, chat, and listing features with Firestore-backed data synchronization.
Stack:
SwiftUI, Firebase, MVVM
Sentiment Analysis Bot
News-driven strategy with 19% annualized backtest performance.
Tap for detailsSentiment Analysis Bot | Python, TensorFlow, NLP, Scikit-learn
- Achieved ~19% annualized return in backtests by building a news-driven trading strategy processing 120+ headlines/run.
- Reduced latency ~35% with a multi-source RSS pipeline fetching 1K+ headlines/day.
- Improved signal accuracy ~25% using TextBlob sentiment scoring and rolling-window smoothing.
- Produced full performance metrics in < 2 s/test via a vectorized Pandas/NumPy backtesting engine.
Stack:
Python, TensorFlow, Scikit-learn, NLP, Pandas/NumPy
Credit Risk Prediction
Live ML inference with React + Flask and CI/CD delivery.
Tap for detailsCredit Risk Prediction | Python, Scikit-learn, React, Flask
- Developed a web app that predicts credit risk using a Random Forest classifier.
- Designed a clean Flask + React stack for live model inference and result visualization.
- Set up CI/CD pipelines for smooth deployment and high availability on GitHub Pages and Render.
Stack:
Python, Scikit-learn, React, Flask
Intent-Level Market Model MVP
Tracks semantic drift + hiring signals to surface early org intent.
Tap for detailsIntent-Level Market Model MVP | FastAPI, Postgres, pgvector, Docker
- Built a multi-tenant intent inference platform that ingests job posts and filings.
- Computed semantic drift and generated evidence-backed intent hypotheses with timelines.
- Added outcomes tracking, backtesting, and lead-time metrics for validation.
Stack:
FastAPI, Postgres, pgvector, Docker
PDF to Lecture
Turns long PDFs into audio lectures with feedback loops.
Tap for detailsPDF to Lecture | Python, NLP, Flask, React.js
- Built a tool to convert PDFs into audio lectures using NLP for text extraction and synthesis.
- Automated a 6-step manual process to reduce content creation time and effort.
- Integrated real-time feedback via a React frontend for a better user experience.
- Handled large files (up to 500MB) efficiently for broader usability.
Stack:
Python, NLP, Flask, React.js
Momentum/Trend-Following Strategy
Golden cross strategy with visualized entry and exit signals.
Tap for detailsMomentum/Trend-Following Strategy | Python, Backtrader, yfinance
- Implemented a momentum trading strategy using Golden Cross / Death Cross signals (50-day vs 200-day SMA) in Backtrader.
- Backtested on historical stock, ETF, and crypto data using Yahoo Finance (yfinance).
- Rendered visual buy/sell markers on price charts to evaluate entry and exit quality.
- Designed an extensible framework that can be adapted for live trading with broker APIs.
Stack:
Python, Backtrader, yfinance
Facial Recognition Attendance
Real-time recognition with attendance dashboards.
Tap for detailsFacial Recognition Attendance System | Python, TensorFlow, OpenCV
- Developed a real-time facial recognition system for classroom and corporate attendance.
- Applied deep learning techniques to boost identification accuracy and tracking efficiency.
- Designed a simple dashboard to visualize attendance results.
Stack:
Python, TensorFlow, OpenCV
EPL Betting Model — Model vs Market Analysis
Model-vs-market edge analysis with interactive dashboards.
Tap for detailsEPL Betting Model — Model vs Market Analysis | Python, XGBoost, Scikit-learn, Pandas, Streamlit
- Built a calibrated XGBoost model for EPL outcomes, achieving ROC-AUC ≈ 0.79 on 570 out-of-sample matches.
- Compared model vs bookmaker-implied probabilities using odds-derived features and ELO ratings to identify market edges.
- Backtested fixed-stake and Kelly strategies across 100+ candidate bets, analyzing ROI and drawdowns.
- Deployed an interactive Streamlit dashboard to explore predictions, edges, and bankroll simulations.
Stack:
Python, XGBoost, Scikit-learn, Pandas, Streamlit
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