Teaching and learning

Teaching

Visiting Instructor- ENTC, University of Moratuwa

I assist the lecturers in assignment preparation, evaluations, laboratory work, and invigilation of examinations. Additionally I conduct reviews on problem sets, and conduct extra sessions when students request additional help or tutoring.

• EN4553 Machine Vision, Fall 2023
• EN3551 Digital Signal Processing, Fall 2023
• EN3160 Fundamentals of Image Processing and Machine Vision, Fall 2023
• EN2412 Electronic Control Systems, Fall 2022
• EN2091 Laboratory practise and projects, Fall 2022

Tutor- Skill Surf

• STAT/CSE4340 Statistical Methods for Engineers, Fall 2022
• MATH3304 Introduction to Linear Algebra, Spring 2023

Learning

A Selection of Undergraduate Modules

While following these modules and gaining theoretical knowledge, I have experience projects and publications in related research. Gradually I discovered my passion for underlying stochastic processes and in the theory of machine learning.

Advanced Courses

• EN4573 Pattern Recognition and Machine Intelligence:
  • Covered Random Matrices, Multivariate Gaussian Density, Concentration of Measure in high dimensions, Goals of Learning, Randomness of the Generalization error, Inductive bias, Density estimation, Concentration inequalities, Introduction to PAC inequalities. Mostly from Statistical Learning Theory by Bruce Hajek and Justin Raginsky.
• EN4583 Advances in Machine Vision

Mathematical fundamentals

• MA4033 Time Series and Stochastic Processes
• MA4013 Linear Models and Multivariate Statistics
• MA3023 Numerical Methods
• MA3013 Applied Statistics
• MA2053 Graph Theory
• MA2033 Linear Algebra
• MA2023 Calculus
• MA2013 Differential Equations

Signal/Image Processing and Telecommunications

• EN4553 Machine Vision
• EN4053 Digital Communications II
• EN3053 Digital Communications I
• EN2570 Digital Signal Processing
• EN2550 Fundamentals of Image Processing and Machine Vision
• EN2083 Electromagnetics
• EN2040 Random Signals and Processes
• EN1060 Signals and Systems

Computer Engineering

• EN3240 Embedded Systems Engineering
• EN3143 Electronic Control Systems
• EN3030 Circuits and System Design
• EN2030 Fundamentals of Computer Organization and Design

MOOCs

• Mathematics for Machine Learning- Imperial College London- (Coursera) August 2020
• Neural Networks and Deep Learning- Deeplearning.AI (Coursera) July 2020
• Computational Thinking and Datascience- MIT 6.00.2 (EdX) June 2020
• Machine Learning- Stanford University (Coursera) May 2020