I'm a software engineering student and technical builder who likes going underneath the abstraction — implementing transformers, physics engines, and quantum-classical ML pipelines from first principles rather than just calling a library. My work spans low-level systems in C++, AI/ML research, and full-stack tools built for real users. I'm particularly interested in roles where I can learn quickly, take ownership, and ship real software.

Languages

• C++, C#, Java, Python, x86 Assembly, Javascript, Typescript, HTML, CSS

Frameworks & Libraries

• PyTorch, LangGraph, PennyLane, React, React Native, Node.js, Vite, Framer Motion, Selenium, BeautifulSoup, Pygame, Discord, yt-dlp, SFML

Tools

• Git / GitHub, VS Code, Visual Studio, Unity

Core Concepts

• Data Structures & Algorithms
• Object-Oriented Programming
• System Architecture
• Physics Simulation
• Machine Learning Fundamentals (built from scratch: autograd, transformers)
• Quantum Computing (VQE, QFT, hybrid quantum-classical ML)
• Web Scraping & Automation
• Debugging & Testing

A from-scratch, dependency-free decoder-only transformer language model, implemented entirely in portable C++17 with no PyTorch, TensorFlow, Eigen, or BLAS.

• Hand-built an N-dimensional Matrix<T> class with stride-based reshaping, slicing, and transposition
• Implemented a custom DynamicComputationalGraph driving backpropagation through manually-derived gradients for multi-head self-attention, layer normalization, feed-forward layers, and cross-entropy loss
• Built a full training pipeline (AdamW optimizer, checkpointing) and autoregressive character-level text generation, demonstrated on Shakespeare

🔗 https://github.com/AnkoninaShahar/CGPT

A hybrid quantum-classical research framework comparing physics-informed neural networks (PINNs) against quantum-augmented PINNs (QAPINNs) for modeling silicon photonic phase shifters.

• Modeled heat diffusion and thermo-optic phase shift dynamics using PDE-constrained neural networks
• Built a hybrid quantum-classical pipeline combining PyTorch with PennyLane quantum circuits
• Compared classical vs. quantum-augmented approaches for physics simulation accuracy

🔗 https://github.com/AnkoninaShahar/qapinn-thermo-optic

A fully functional chess application with complete rule enforcement and a graphical interface.

• Implemented full chess ruleset including legal move validation and turn management
• Designed an object-oriented architecture to model board state, pieces, and game flow
• Built a responsive GUI using SFML for rendering and user input

🔗 https://github.com/AnkoninaShahar/Chess

• Sales Tracker — Sleek — Animated React/Vite sales-tracking web app built for a real client (GIFT theater bake sales)
• Sales Tracker — Retro — C++/SFML desktop precursor to the Sleek web version, also built for GIFT
• Physics Sandbox — Real-time 2D physics simulation (C++/SFML) with collision detection and response
• Tension Simulation — Python/Pygame simulation of nodes connected by breakable, physics-driven tethers
• LangGraph Weather Agent — LLM agent using LangGraph + Tavily web search for real-time weather retrieval
• Pennylane101 — Quantum computing exercises (VQE, QFT) using PennyLane
• Portfolio — Personal portfolio site with a blueprint/architectural design theme
• ChooseFunction — C++ algorithmic project reducing Pascal's Triangle lookups to O(1)
• Link-Scraper — Python scraper (Selenium/BeautifulSoup) for pulling basketball stats from the web
• Discord Music Bot — Python Discord bot with full music playback controls

Coursework

• Java Assignments — CIS 35A: OOP, inheritance, serialization, adapter pattern
• Assembly Assignments — CIS 21JA: x86/MASM assembly

• Software Engineering Internships
• Early-stage startup roles where I can wear multiple hats
• Systems-level, AI/ML, or simulation-focused engineering — especially work that goes deeper than calling a framework (custom engines, ML internals, performance-critical code)
• Opportunities to apply quantum computing or research-adjacent ML in a practical setting

I'm especially interested in environments where I can take ownership, learn fast, and contribute meaningfully.

De Anza College — Associate of Science in Computer Engineering Expected Graduation: 2027 GPA: 4.0 / 4.0

• 📧 Email: Shahar.Ankonina05@gmail.com
• 💼 LinkedIn: www.linkedin.com/in/shahar-ankonina
• 📋 Portfolio: https://ankoninashahar.github.io/Portfolio/