Vaishnavi Kasturipally
Software Engineer • Hyderabad, India • v********************@gmail.com • +91*******625 • github.com/••••• • drivetube.ai/•••••
Professional Summary
Software Engineer with 0-1 years of experience applying Python-based AI and security concepts through academic projects and an AI internship; strong foundation in data preprocessing, ML model prototyping, and IoT security design.
Technical Skills
Programming Languages: Python,C,Java
Frameworks and Libraries: NumPy,Pandas,scikit-learn,TensorFlow,Keras,Matplotlib
Databases: SQL,SQL relational queries
Cloud and DevOps: Linux
Data and Analytics: Data preprocessing,Feature engineering,Model evaluation and validation,Supervised learning,Deep learning
Tools and Methodologies: Git,Jupyter Notebooks,VS Code
Security and IoT: IoT security concepts,Multifactor authentication,Lightweight cryptography,Intrusion detection concepts
Productivity and Communication: MS Excel,Documentation,Technical communication,Team collaboration
Work Experience
Edunet Foundation
Artificial Intelligence Intern
June 2025 – July 2025
EdTech organization focused on educational content and learning technologies; supported AI research and prototype development to analyze and enhance educational resources.
Tech Stack: Python, NumPy, Pandas, scikit-learn, TensorFlow, Jupyter Notebooks, Git
- Assisted in design and implementation of Python-based ML workflows to analyze educational content, using NumPy and Pandas to prepare datasets for model experiments.
- Built reproducible data preprocessing pipelines and exploratory analyses in Jupyter Notebooks to accelerate experimentation and ensure clean training inputs.
- Implemented baseline supervised models with scikit-learn and prototyped neural network approaches using TensorFlow/Keras to evaluate classification performance on small education datasets.
- Documented experiments, model configurations, and evaluation metrics; prepared concise demonstration notebooks and slide summaries to communicate results to mentors.
- Applied version control with Git to track code and experiment iterations, and organized modular Python scripts to improve reproducibility and handoff.
- Researched lightweight model techniques and privacy-aware approaches relevant to resource-constrained devices and sensitive educational data to inform project direction.
Projects
Scalable and secure big data IoT System based on Multifactor Authentication and Lightweight Cryptography
Tools Used: IoT security concepts, Multifactor authentication, Lightweight cryptography, System design
- Designed an architecture for secure IoT data collection that incorporates multifactor authentication and lightweight cryptographic primitives suitable for constrained devices.
- Outlined data flow and scalability considerations for large-volume IoT telemetry, focusing on secure ingestion, authentication, and privacy-preserving storage.
- Prepared threat model and mitigation strategies highlighting lightweight crypto trade-offs for device-side encryption and server-side verification.
Intrusion Detection in Cybersecurity Using Deep Learning
Tools Used: Deep learning, Data preprocessing, Model evaluation, Python
- Studied intrusion detection concepts and applied deep learning approaches to identify anomalous network or system behavior from labeled datasets.
- Performed feature engineering and preprocessing to transform raw logs into model-ready inputs, then trained and evaluated neural network models to measure detection performance.
- Documented experimental setup, evaluation metrics, and limitations to guide future improvements in dataset quality and model robustness.
Online Voting System for Elections
Tools Used: Secure system design, Authentication, Documentation, Web application design
- Designed a secure web-based voting system concept that emphasizes voter authentication, ballot integrity, and auditability in election workflows.
- Defined role-based access, encryption of ballots, and end-to-end process flows that reduce opportunities for tampering while simplifying voter experience.
- Created system diagrams and documentation to explain security controls and deployment considerations to non-technical stakeholders.
Education
Malla Reddy College of Engineering for Women (JNTUH)
B.Tech in Computer Science and Engineering • Hyderabad, India • 2022 – 2026
TSR Junior College (MPC)
Intermediate • 2020 – 2022
Zilla Parishad High School
SSC • 2019 – 2020
Certifications
Python — HackerRank
Generative AI — GUVI
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