Rutvij Shah

Hi there 👋

I am Rutvij, a CS grad student at UT Dallas.

My specialization is in Intelligent Systems. Eventually, I would like to pursue a PhD in CS & work as a researcher.

_Drop down each section to learn more about me!_

Interests ...

My interests are far too wide ranging for me to ever catch up with them. Some of them are:

• Machine Learning, especially Reinforcement Learning
• Logic Programming & AI - automated reasoning!
• Data Science, particulary the statisitcal & mathematical side of it.
• Programming Language Design & Compiler Theory
• Functional Programming - Haskell & Lisp in particular
• Theory of Computation & Algorithm Design
• Numerical Optimizaiton & Computational Geometry
• System Programming - OSes, Databases etc.
• GUI Programming (native apps) - MVC, UI/UX design

And thus I call myself a deluded dilettante!

🔭🌱 I’m currently working on and learning ...

• Implementing the first interpreter in Crafting Interpreters using Python. The implement repo for PyLox.
• Learning Lisp (Scheme) & a new way of looking at fundamentals of our craft from SICP. My notes.
• Learning Go & making practical projects following prompts at Gophercises.
• Grokking C language through the lens of its creators K&R2.

🤔 I'm looking forward to learning these in the near future ...

• Learning Quantum Algorithms and Neural Net Mathematics this Fall!
• _Haskell_ - through a category theoric lens & revisiting http://learnyouahaskell.com/chapters" rel="noopener nofollow" target="_blank">LYAH before learning from new resources.
• _Reinforcement Learning_ & _Neural Networks_ in greater depth.

Projects

Artificial Intelligence & Machine Learning

1. Capstone project involving analysis of Transistor Load Pull Data for Qorvo. [Data Analysis]

2. Custom implementation of Decisiton Trees as a part of a graduate ML course. [ML]

3. Contact tracing data analysis [ML]
- Custom implementations of Bagging & Boosting (adaBoost) ensembles on ID3 trees.
- Custom implementation of a simple NN
- Use of various sampling methods and a comparison of their effectiveness at addressing class imbalance.
- Check out the Project Report for details!

4. Statistical analysis projects using R Language as a part of a grad course. [Statistics]

5. Lane Line Detection: Detecting lane lines on roads & stop signs using Open CV. [Computer Vision]

6. Medial Axist Transform: Medial axis transform using Delaunay triangulations. MAT was used to demonstrate too of its applications, one, to compress shapes by reducing a dimension. Another, a computer vision cross-application to perform pattern matching and find similar shapes using path matching. [Computational Geometry & Computer Vision]

7. Implementation of A* search using Python to solve 8-Puzzle game and comparison with other search methods.

8. A Q&A system using Prolog, which can answer basic questions given an encoded description of a simplified real world environment. [Logic Programming]

9. Flower Images Classification - Transfer learning on trained CNN models to classify flowers.

10. Cheque Perspective Transform - A cheque scanning workflow with amount extraction using HTR.

iOS & GUI App Development

1. Flix: An app that allows users to browse movies from the The Movie Database API. [iOS]
2. TwitterClone: A basic twitter app to read your tweets, compose new tweets, and like + retweet timeline tweets. [iOS]
3. Parstagram: An Instagram clone with a custom Parse backend that allows a user to post photos, view a global photos feed, and add comments. [iOS]
4. Used PyQT as a part of my internship & for my DB course to build a contacts list app using OBDC (CRUD, triggers, text search etc.). [PyQT]

Database Engine

1. An SQLite like DB, named RioDB, implemented as a part of a Database Design course.

C/C++ Programming

1. Few examples created as a part of the coursework for an OS course
2. Few more as a part of an Unix Programming Course.

Cybersecurity: Docker Wordpress vs Kali

• As a part of a Cybersecurity course I took with Codepath, we created an airgapped system to learn and perform pentesting.
• The course initially suggested the use of Vagrant to setup and maintain the VMs for testing (a Kali Linux instance and a WordPress server).
• I replicated the process using Docker, making it easier & faster for first time learners to deploy the test enviroments with minimum fuss.
• Also leveraging the light weight nature of containers to make the process less resource intensive.

HDL Programming

• Built an 16-bit ALU using the Verilog HDL and an interactive simulation Logism.

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