I believe education should be accessible to everyone and thus I have created a medium page where I write articles on machine learning. I try to cover many topics starting from linear models to statistics with the simplest possible explanation. You can find all of my articles here. I also have some new article ideas upcoming!
I recently gave a talk at the Machines, Inference, & Algorithms (MIA) at the Broad Institute (MIT) on Decoding Word Meaning from Brain Imaging Data along with Dr. Alona Fyshe. Full talk here
.Talk on Linear Models at Calgary Data Science Academy (CADASA) during the Machine Learning Bootcamp, November 2020. Full talk here.
Another talk where I talk about new features in Android 11 at the Android 11 meetup by Google Developers Group Edmonton. Full talk here
.The project uses machine learning to understand how early do the semantics of the words are acquired by the human brain. We read EEG data from children brains and train a machine learning algorithm on it. This is a decoding problem where we find the relationship between the EEG and the stimuli. We also use word embeddings from Word2Vec for the stimuli. We also use various optimization techniques along with statistical tests for significance testing.
I love programming. Here are some programming languages that I know.
Here are some frameworks I know.
I am currently pursuing my master's degree with a GPA of 3.5/4.0. Here, I am working on improving my research abilities. My primary research area is in the intersection of machine learning, neuroscience, and natural language processing. Supervisor: Dr. Alona Fyshe.
I completed my undergraduate degree with a GPA of 9.48/10.0. Here, I studied the foundations of computer science.
Currently working as a research assistant at the University of Alberta, Computing Science department.
I taught CMPUT-301 (Software Engineering) for terms Fall 2019 and Winter 2020 at the Computing Science department, University of Alberta.
Six months internship working on a mixed reality project with Microsoft HoloLens. We developed a proof-of-concept application to visualize ambient radiation in the environment.
Two month internship where I worked on a payment collections interface. I used Ruby on Rails to upgrade the software to the latest framework version.
Vice President at the CSGSA. Roles include assisting the president and other executives in making executive decisions along with organizing department wide events.
Volunteering as the Academic Director at the CSGSA. My roles and responsibilities include promoting academic opportunities for students, overseeing the buddy list program, and assigning office spaces to students.
Technical speaker on various topics such as machine learning, python, firebase, and introductory android developement. I was also a session lead for a recent machine learning bootcamp where I covered linear models.
I was a technical speaker and I taught deep learning, machine learning, and python to peers and undergraduate students. I also gave talks on machine learning at other institues.
This was a course project for CMPUT 659 - XAI in Games, University of Alberta. We implemented a evolutionary program synthesis approach with a domain specific language to generate the best set of rules for winning the game.
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In this project, I compare various classification models on Kepler Data to find out whether a celestial body is a planet given various features and characteristics. This was a course project for CMPUT-566, Introduction to Machine Learning at University of Alberta.
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In this project, various unsupervised algorithms were assessed on their ability to cluster contextual embeddings from the BERT language model. Various linear and non-linear dimensionality reduction techniques were also used for visualizing the data.
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