Ramanan Abeyakaran

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CS & Stats • UC Berkeley

About Me



My name is Ramanan Abeyakaran, and I'm a second-year undergraduate from Atlanta, GA pursuing a degree in Computer Science and Statistics at the University of California, Berkeley. I'm an avid problem solver, and am passionate about exploring how the fields of mathematics and computer science intersect. Currently, I'm interested in software engineering and machine learning.

I love picking up new skills and learning about anything and everything (this website is my first project in HTML/CSS/JavaScript)! Apart from academics, I enjoy playing tennis, exploring, painting and reading, but I'm always open to try something new. If you're ineterested in any of the above, I would love to connect!

Feel free to take a look at my resume.

Education



University of California, Berkeley (Expected Graduation: May 2023)
Bachelor of Arts, Computer Science and Statistics

Relevant Coursework: (CS 61B) Data Structures • (Stat 133) Concepts in Computing with Data • (CS 61A) Structure and Interpretation of Computer Programs • (Math 54) Linear Algebra and Differential Equations • (Math 53) Multivariable Calculus • (Data 8) Foundations of Data Science

Skills: Python (NumPy, Flask) • Java • JavaScript • Git • HTML • CSS • R • SQL • Excel • Scheme • LaTeX

Projects



Gitlet • Java

A local version control system that mimics some of the features of Git. Employed serialization, file compression and SHA-1 encryption in order to safely and efficiently ensure proper file distribution.

AI Player • Java

An AI Player for the Lines of Action Board Game. Utilized Alpha-Beta pruning and the Mini-Max algorithm to search 3 moves ahead from the current configuration and decide on the optimal move.

Max Flow Solver • Python

A python program to solve the max flow problem for given Flow Networks. Applied the greedy Ford-Fulkerson Algorithm on an inputted network represented as a matrix.

Absorbing Markov Chain Simulator • Python

A python program that calculates the infinite sum probabilities of Absorbing Markov Chains that enable an initial state to transform into a terminal state.

Scheme Interpreter • Python

An interpreter for Scheme, the minimalist dialect of Lisp, using Python. Based on the REPL environment and a pre-existing framework. Parsed tokenized Scheme commands to run in Python

Genre Classifier • Python

A movie genre classifier built in Python that applies the K-Nearest Neighbors algorithm to an inputted movie script. Identifies proximity to keywords conveying strong emotion found in the script.

Honors



4 Time AIME Qualifier
Mathematical Association of America • American Invitational Mathematics Exam
  • Qualified for the AIME 4 Times
  • Distinguished Honor Roll (Top 1% Nationally)
  • (Top 3 in State) AMC 10 - 133.5 / AIME - 8
  • (Top 5 in State) AMC 12 - 121.5 / AIME - 8

Honorable Mention MathWorks Math Modeling Challenge
Society for Industrial and Applied Mathematics March 2019
  • Tied for 13th nationally out of 750+ teams

Mu Alpha Theta National Convention
Mu Alpha Theta July 2017
  • 6th Place nationally on the Speed Math test across all divisions
  • 14th Place nationally in the Alpha Individual division

Contact



Feel free to connect with me or checkout my other profiles!


Email: Ram.Abey2001@berkeley.edu


Resume




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