CV
Projects
- Revisited all of the labs of all my AI courses at uni, and worked through many Deep Learning textbooks. Organised my CS, Math notes and trampolined off all this knowledge to solve my own novel problems with the power of ML.
- Implemented 2D, 3D state of the art semantic segmentation architectures, along with conducting a thorough literature review and experimentation with transfer learning models across the term-long project. Ultimately, obtained full-marks with a class-leading Mean Sorensen Dice score of 78.
#nnUNet #vnet #unet #samnet #gpu #python #jupyter #HPC #group-project
- Scored a High-Distinction in this term-long project
#full-stack #group-project #python #typescript #front-end #testing #CI/CD #docker
Education
65.0
- MT1131 - Mathematics 1A
- MT1141 - Mathematics 1B
- MT1081 - Discrete Mathematics
- MT2501 - Linear Algebra
- MT2011 - Several Variable Calculus
- MT2521 - Complex Analysis
- MT2121 - Differential Equations
- MT3161 - Optimisation
- MT2901 - Higher Theory of Statistics
- MT3611 - Higher Algebra
- CS1151 - Programming Fundamentals
- CS1531 - Software Fundamentals
- CS2521 - Data Structures and Algorithms
- CS1521 - Computer Systems Fundamentals
- CS2511 - O-O Design & Programming
- CS3121 - Algorithm Design
- CS3231 - Operating Systems
- CS3311 - Database Systems
- CS3331 - Computer Networks & Applications
- CS3411 - Artificial Intelligence
- CS9417 - Machine Learning & Data Mining
- CS9444 - Deep Learning & Neural Networks
- CS3900 - Computer Science Project
- CS4920 - Professional Issues and Ethics
- CS9517 - Computer Vision
- AR1630 - Japanese 1A
- AR1631 - Japanese 1B
- AR2630 - Japanese 2A
85.0
- AR2631 - Japanese 2B
- CS2041 - Shell Construction: Techniques and Tools
- CS9418 - Advanced Statistical Methods for Machine Learning
- MT5960 - Bayesian Inference and Computation
- MT5905 - Statistical Inference
- MT5835 - Advanced Stochastic Processes
- MT5825 - Measure, Integration and Probability
- FI5513 - Investments & Portfolio Selection
- MT5171 - Linear and Discrete Optimisation Modelling
- MT5806 - Applied Regression Analysis
- MT5845 - Time Series
Experience
Skills
-
Deep Learning (Novice)
Python, Numpy, Pytorch, Matplotlib
-
Linux (Pro)
shell, git, regex, emacs, vim
-
Typing (Amateur)
dvorak, 110wpm
Languages
- English — Fluent
- Hindi — Proficient
- Japanese — Learning
Interests
- Operating Systems — design, memory, gpu
- Rap — eminem, ye, kendrick, jcole
- Other — Ultimate Frisbee, motorcycles
References
Volunteering
An op-shop that assists people experiencing poverty and inequality to shape a more just and compassionate society
- stacking / drowning in lots non-academic books!
Awards
Certificates
Publications