Latest Post:Hello World Dec 3, 2022 - 1 min read
About Me
I am a software engineer with over 10 years of professional experience. My career’s main theme has been developing prototypes/proof-of-concepts of machine learning systems, as well as the tools to help build them, for a wide range of applications. In the course of my career, I’ve developed a passion for building quality software to help people bring to bear the power of data in a secure and ethical manner.
I currently work at Verizon, formerly at SRI International.
Those I have worked with have told me that I project energy and passion when talking about topics I believe in, I’m eager to jump in and help others, I’m able to quickly learn and apply new things, and I’m able to explain complex concepts clearly in simple terms.
When I’m not doing hobby software projects, I also enjoy playing video games, watching anime, performing music (singing, percussion, and a little bit of guitar), and doing some home cooking.
I live with my wife and daughter in the New Jersey part of the Tri-State area.
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My Stuff
💼 I keep my Linkedin up-to-date with my professional record.
🖥️ I have some open source work mostly on Gitlab but also on Github.
🎓 You can view my purely academic work on my ORCID page.
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Curated Keywords
🧑💻 Programming & Markup Languages:
Python (10 years), C/C++ (6 years), C# (7 years), XAML (6 years), Javascript (2 years), Java, Rust, Matlab, Powershell, Bash, CMake, HTML/CSS, XML, JSON, YAML, TOML, SQL
📕 Major Libraries:
NumPy, Pandas, Flask, OpenCV, TensorFlow, Eigen, Boost, TensorRT, Sci-kit Learn, XGBoost, React
🛠️ Software Development Tools and Platforms:
Google Search, Linux (Ubuntu & Redhat), Windows, Visual Studio Code, SSH, VIM, Git, Github, Gitlab, Unity3D, Docker/Podman, Kubernetes, Cloud (AWS, GCP, Digital Ocean), Godot, Postgres, Slack
⚙️ Technologies:
MVC/MVVM, TCP/IP, REST API, Single-page Application, WebSockets, GraphQL, WebAssembly, Machine Learning
💭 Methodologies:
Critical Thinking, Design Thinking, Unit Testing, Agile, Clean Architecture, API-First, Bayesian thinking
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