Ananya Mantravadi

Work

NC State University

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Graduate Teaching Assistant

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Highlights

Graded assignments, evaluated projects, mentored, and conducted tutorial sessions for 7 graduate and undergraduate courses like Object-Oriented Design and Development, Operating Systems, and Data Structures. Guided over 400 students across 3 institutions.

NetApp

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Artificial Intelligence & Software Engineering Intern

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Highlights

Developed and deployed an MLOps pipeline for revenue forecasting using time-series modeling with Python, Pandas, and DataRobot, integrating product capacity and usage data, CI/CD workflows, and quarterly backtesting (90/60/30-day rolling updates), reducing forecasting error to 1% (MAPE) for a $30M business unit; presented insights and visualizations (Tableau) to business stakeholders.

Built and evaluated customer churn prediction models for a SaaS product using XGBoost, Dynamic Time Warping, Tableau, and survival analysis; estimated potential loss and retention ROI, uncovered data limitations that informed strategic pivots.

CANDLE Research Lab, IIT Roorkee

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Machine Learning Research Intern

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Highlights

Implemented and enhanced image dehazing, PCB components inspection, dental X-ray segmentation, and arrhythmia classification using novel neural networks and deep learning techniques, leading to scholarly publications.

Mahindra & Mahindra Financial Services

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Data Science Intern

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Highlights

Designed, built, and deployed a voting ensemble classification model using Python, SQL, and Azure ML for predicting cases likely to default while extending loan offers for Scorpio Z101, a newly launched SUV improving recall by 30% to achieve 72%. This model was developed using features extracted from large-scale credit bureau data and the internal bank database.

Developed and executed ETL pipelines, utilizing Python and SQL, to process retro scrub data from diverse credit bureau sources such as CRIF, CIBIL, and Experian, reducing data processing time by 20 hours.

Capgemini

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Data Science Intern

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Highlights

Developed an interactive stock analysis dashboard using Python, Dash/Plotly, CSS, & Yahoo Finance API, integrating real-time data, user interaction logic, and dynamic Ul elements for technical indicators, risk modeling, and future projections (GBM, GARCH). (Link)

Education

North Carolina State University

Master of Computer Science Computer Science Grade: 4/4

Indian Institute of Information Technology, Raichur

Bachelor of Technology Computer Science & Engineering Grade: 8.8/10

Courses

Data Structures & Algorithms

Software Engineering

Database Management Systems

Object Oriented Design & Analysis

Operating Systems

Parallel Systems

High Performance Computing

Natural Language Processing

Neural Networks

Publications

CLINet: A Novel Deep Learning Network for ECG Signal Classification

Journal of Electrocardiology

Spatial Field Fusion Network (SFFNet) for Panoramic Dental X-ray Segmentation

IEEE APSCON

ClarifyNet: A high-pass and low-pass filtering based CNN for single image dehazing

Journal of Systems Architecture, 132, 102736

Dilated Involutional Pyramid Network (DInPNet): A Novel Model for PCB Components Classification

IEEE

In 2023 24th International Symposium on Quality Electronic Design (ISQED) (pp. 1-7).

Skills

Python

C++

SQL

NoSQL

MySQL

MariaDB

MongoDB

Windows

Linux (Ubuntu)

HTML/CSS

Flask

FastAPI

REST APIs

Dash/Plotly

PyTorch

Tensorflow

MLOps

LangChain

Microsoft Excel

Pandas

Tableau

Git

GitHub Actions

Docker

Azure

AWS

Spark

CUDA

Projects

Wikipedia-Based Language Model

Summary

Fine-tuned DistilGPT-2, a lightweight generative language model, on a curated subset of Wikipedia articles for text generation, leveraging tokenization and causal language modeling to generate coherent responses while optimizing for minimal computational resources.

Multimodal Knowledge Base

Summary

Engineered a dockerized RAG system using FastAPI and React for document ingestion and querying leveraging LangChain for semantic and agentic chunking (Gemini), ChromaDB for vector-based retrieval, and prompt engineering. Integrated PDF parsing (Llama Parse, pymupdf4llm) and table/image extraction to handle diverse formats.

Wolf Parking Database System

Summary

Built using Java, JDBC, and MariaDB, enabling multi-role support for permits, vehicles, zones, and citations through dedicated modules for permit issuance, citation processing, payments, appeals, and automated reporting. Designed relational schemas and implemented transactional operations to ensure ACID compliance and real-time system updates.

Parallel PageRank for large-scale webgraphs

Summary

Implemented and profiled parallel variants using CUDA, OpenMP, and Hybrid CUDA-MPI in C++. Benchmarked performance across increasing graph sizes up to 16K nodes, achieving 350x speedup over sequential baseline.