Achievements
Contribute a major feature to an Open Source Project
Land at least one merged PR in projects like Aseprite, MuseScore, cuDF, or Torchao
Publish an Open Source Library
Release a C++ or CUDA library (e.g., image processing, caching, or ANN search) with documentation and community adoption.
Create a Multiplayer Video Game
Develop a Multiplayer PvE Indie Game from scratch using any Graphics API
Build a Database System from Scratch
Achieved: 04/30/25Design and implement a database system from scratch with networking, and data-structures.
Achieved: 04/30/25
Build a Fully-Distributed System from Scratch
Design and implement a distributed system from scratch with networking, consensus, and fault tolerance.
Read Tour of C++
Achieved: 05/01/25Study Tour of C++ thoroughly and implement core data structures and RAII-friendly containers from scratch.
Achieved: 05/01/25
Read Learning Go
Achieved: 04/01/24Study Learning Go by Jon Bodner thoroughly and implement exercises from Go Further.
Achieved: 04/01/24
Read Designing Data Intensive Applications
Study DDIA thoroughly and implement relevant DSA and create flash-cards for each chapter.
Read Operating Systems: Three Easy Steps
Study OSTEP thoroughly and mess around with xv6 + create flash-cards for each chapter.
Read Programming Massively Parallel Processors
Study PMPP thoroughly and implement a np-like CUDA Library for MatMul.
Read Beej's Guide to Network Programming
Study Beej's Guide and implement smaller toy projects to understand sufficient amount of TCP/UDP.
Complete a Masters at Georgia Tech
Graduate from Georgia Institute of Technology with a Masters in Computer Science and a minimum of 3.5 GPA.
Publish a Blog Series on CUDA & Neural Networks
Achieved: 09/12/25Author a blog series covering the math, implementation, and optimization of a CUDA-based neural network from scratch.
Achieved: 09/12/25
Complete a Masters at New York University
Achieved: 01/23/25Graduate from New York University with a Masters in Computer Engineering and a minimum of 3.0 GPA
Achieved: 01/23/25
Design a custom ML Model
Achieved: 04/01/24Design and implement a train an ML model with data ingestion, feature pipelines, model training/validation, and testing.
Achieved: 04/01/24
Build a Fullstack Application
Achieved: 04/01/24Design and implement a complete fullstack application with API handling, database queries, and efficient retrieval.
Achieved: 04/01/24
Build a Real-Time Rendering Engine
Achieved: 01/02/2023Implement a graphics engine supporting PBR, deferred shading, and compute-based particle systems.
Achieved: 01/02/2023
Build an Embedded System
Achieved: 01/02/2023Implement an STM32 embedded system using GPIO, I2C Protocols, Sensors, Soldering
Achieved: 01/02/2023
Secure a Internship or Full-Time Role in HPC/MLE/Graphics
Land a full-time position in high-performance computing, ML inference optimization, or graphics engineering.
