I am a Computer Science student with hands-on experience in full-stack development, machine learning, mobile applications, and low-level systems programming.
I have delivered AI-driven software projects and contributed to Android application development.
My technical background also includes engineering foundational IT systems on cloud platforms, building a Y86-64 Processor Emulator in C, and gaining exposure to advanced computational concepts through programs at Cornell Tech and Duke University.
Currently, I am seeking challenging Software Engineering and Machine Learning roles where I can apply my diverse skillset and passion for continuous learning to build impactful solutions.
I am also a Quantum Intern at Quantumpedia x QWorld, selected as one of five interns out of 130+ applicants for a 2025 research project on privacy-preserving quantum machine learning models for financial systems. We are developing an automated quantum-AI framework involving distributed QML, algorithmic trading, and quantum-enhanced protocols, with an upcoming peer-reviewed publication.
| Project | Skills & Tech | Repo Link |
|---|---|---|
| ML Sentiment Analysis | Python, NLP, Sentiment Analysis, Jupyter Notebook | [Repo Link] |
| ML Neural Network Implementation | Python, Neural Networks, Deep Learning | [Repo Link] |
| ML Model Selection for KNN | Python, K-Nearest Neighbors, Model Tuning | [Repo Link] |
| ML Regularized Logistic Regression | Python, Logistic Regression, Regularization | [Repo Link] |
| ML Handwritten Digit Classification | Python, CNNs, Image Processing | [Repo Link] |
| ML Regression Ensemble Modeling | Python, Ensemble Learning, Regression | [Repo Link] |
| Anamorphic Encryption Implementation | Python, Qiskit, PennyLane, Quantum ML | [Repo Link] |
| Y86-64 Processor Emulator | C, Low-level Systems Programming | [Private Link] |
| Quantum Internship (Quantumpedia x QWorld) | Qiskit, PennyLane, Python, Quantum ML, Algorithm Design | [Private Link] |
More projects are pinned on my profile.
- Languages: Java, Python, C, Kotlin, TypeScript, SQL
- Frameworks & Tools: Qiskit, PennyLane, TensorFlow, PyTorch, DeepXDE, JAX, AWS, Firebase, Vercel, Pinecone, Groq API
- Technologies: Machine Learning, Neural Networks, Quantum Computing, Distributed Systems, Backend & Frontend Development
- Development Tools: VS Code, Google Colab, Eclipse, Android Studio, Unity
- Quantum QuEra Atoms Certificate
- SQL Tips and Tricks for Data Science
- Womanium + WISER Quantum 2025
- Womanium Global Quantum+AI Badge 2024
- Womanium Global Quantum 2023
Each project repo includes:
- A comprehensive README with project overview, objectives, methodology, results, visualizations, and next steps
- Sample datasets to help you test functionality
- Jupyter/Colab notebooks demonstrating example scripts where applicable
- Step-by-step installation instructions and model training guidelines
- Complete documentation including API references and user guides
Feel free to connect via LinkedIn, email me at fanizza.t.tahir@gmail.com, or check out my Portfolio.
Thanks for stopping by my GitHub! 😊