Summary
Overview
Work History
Education
Skills
Websites
Awards
Machine Learning Algorithms
Timeline
Generic

Madhuri Tata Madhusudan

Summary

Senior Software Engineer with 9+ years of experience, focused on backend development and production-grade Machine Learning. Built predictive models for taxi time and runway classification using Random Forests and XGBoost. Designed and deployed scalable ML pipelines with FastAPI, Docker, and AWS (EC2/RDS).

Overview

10
10
years of professional experience

Work History

Independent Study & Parental Leave

08.2024 - Current
  • Focused on developing end-to-end, production-ready ML applications while caring for my toddler.
  • Developing a healthcare chatbot using a RAG pipeline with medical content, deployed on AWS EC2
  • Integrated FAISS for vector search and experimented with embedding models (e.g., Sentence-Transformers, OpenAI embeddings)
  • Used quantized LLaMA models and ChatGPT APIs to generate responses from RAG-derived context
  • Working with Hugging Face, PyTorch, AWS SageMaker, and vector databases for LLM-based application development
  • Completed applied coursework: Generative AI with Large Language Models (Coursera) and Prompt Engineering for Developers (DeepLearning.AI)

Senior Software Engineer

Passur Aerospace, Inc
11.2017 - 08.2024
  • Developed software solutions in C/C++ and Python for the aviation industry, leveraging machine learning to improve flight predictions, scheduling, and operational efficiency.
  • Improved taxi time prediction accuracy by 10–30% across the 25 busiest U.S. airports using a regression tree model, contributing to reduced downstream scheduling delays. Involved in end-to-end ML development: data collection, preprocessing, model tuning, and deployment.
  • Built Random Forest and XGBoost models to predict arrival/departure runways, boosting accuracy from ~65–70% to 85%
  • Re-engineered a flight on-time prediction system in multi-threaded C++ and integrated ActiveMQ for high-throughput data; achieved ~95% coverage and ±5-minute accuracy for 80% of flights across 300+ U.S. and 80 international airports.
  • Spearheaded production deployments, monitoring, and continuous improvements of the flight on-time prediction system, ensuring high availability and responsiveness.
  • Designed data preprocessing pipelines in PostgreSQL and AWS RDS; developed and deployed REST APIs with FastAPI
  • Deployed ML services on AWS EC2 with Docker and Kubernetes for scalability and reliability

Software Engineer

Passur Aerospace, Inc
02.2015 - 11.2017
  • Led development of C/C++ and OpenGL-based web GUIs for flight tracking and deicing, used by ground staff and air traffic controllers
  • Built FastCGI programs on Apache for real-time flight monitoring interfaces
  • Contributed to the design and feature set of a web-based flight analytics platform
  • Created internal tools to visualize flight paths, track prediction accuracy, and monitor system health

Education

MS - Electrical Engineering

University of Southern California
05.2015

BS - Electronics and Communication Engineering

Visvesvaraya Technological University
07.2013

Skills

  • C
  • C
  • Python
  • Shell Scripting
  • OpenGL
  • HTML
  • MATLAB/Octave
  • Windows
  • Linux
  • PostgreSQL
  • AWS RDS
  • Visual Studio
  • Codelite
  • Emacs
  • Vim
  • Perforce
  • Gitlab
  • SonarQube
  • ActiveMQ
  • CI-CD Pipelines
  • Apache Jenkins
  • AWS EC2
  • Docker
  • Kubernetes
  • REST APIs
  • Pandas Machine Learning Suite
  • Jupyter Platform
  • Numpy
  • Scikit-learn
  • Pytorch
  • AWS Sagemaker
  • Linear Regression
  • Polynomial Regression
  • Logistic Regression
  • Random Forests
  • Decision Trees
  • Support Vector Machines
  • Neural Networks
  • K-Nearest Neighbors
  • XGBoost
  • Bagging
  • Boosting
  • K-Means Clustering
  • DBSCAN
  • Principal Component Analysis
  • Collaborative Filtering
  • Content-Based Filtering
  • Convolutional Neural Networks
  • Large Language Models

Awards

  • Partner of the Year, Awarded at Passur Aerospace, Inc for the year 2017.
  • Best Project, Awarded by KCST (Karnataka State Council for Science and Technology, Indian Institute of Science, India) out of the entire state of Karnataka, 2013.

Machine Learning Algorithms

Linear Regression, Polynomial Regression, Logistic Regression, Random Forests, Decision Trees, Support Vector Machines (SVM), Neural Networks, K-Nearest Neighbors (KNN), XGBoost, Bagging, Boosting, K-Means Clustering, DBSCAN, Principal Component Analysis (PCA), Collaborative Filtering, Content-Based Filtering, Convolutional Neural Networks (CNNs), Large Language Models (LLMs)

Timeline

Independent Study & Parental Leave

08.2024 - Current

Senior Software Engineer

Passur Aerospace, Inc
11.2017 - 08.2024

Software Engineer

Passur Aerospace, Inc
02.2015 - 11.2017

MS - Electrical Engineering

University of Southern California

BS - Electronics and Communication Engineering

Visvesvaraya Technological University

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Madhuri Tata Madhusudan