Reload: Data-Free Machine Unlearning and Model Editing through Selective Data Forgetting and Selective Data Replacement (Ongoing)
A self-driven research project undertaken as a research intern at the Vector Institute under Dr. Rahul Krishnan
Research Initiatives
Automatic labelling of data clusters: Alignment checking and unsupervised clustering
Using word embeddings to learn a descriptive feature space to automatically annotate unlabelled clusters
Understanding the dynamics of adversarial training through generative adversarial kolmogorov-arnold networks
Using the Kolmogorov-Arnold network capacity for symbolic equation decomposition to understand the phenomena of adversarial training
Are video-games effective tools for early-years mathematical education
A project completed under Prof. Steve Engels, designing a hyper casual mathematics game for reinforcing arithmetic skills in children
Exploring Syntactic Dependency Trees as a Method for Assessing Semantic Equivalence
Discovering whether there are more efficient implementations by first researching whether similarity measures on dependency trees are a good measure of semantic equivalence between sentences.
An Investigation and Simulation of the Impact of COVID-19 on the Political Satisfaction of the General Public
A sentiment analysis based project aimed at understanding political satisfaction during COVID-19 through scraping and studying reddit data
To what extent is Proximal Policy Optimisation a more efficient and accurate reinforcement learning algorithm in procedurally generated environments?
An evaluation of Proximal Policy Optimisation on procedurally generated video game environments
You should think about that some more: Recurrent Threshold Neural Networks
Exploring using a probability threshold and a feedback loop to create a dynamically deep neural network with the ability to say ‘I don’t know’
Downstream Feature Masking for Contrastive Pretrained Models (Ongoing)
A research project in collaboration with Patrik Reizinger on unlearning in contrastive self-supervised models
Are Sequential Models Fantastic Simulators? (Ongoing)
Exploring the use of autoregressive models in simulations
Can Self-Supervised Models unlearn themselves? (Ongoing)
A study into whether the data-augmentation and completion mechanisms of self-supervised models allow them to unlearn data themselves
Discovering hidden correlations from Sequence Read Archive Bioproject metadata
Conducted during my time at the RNALab under Dr. Artem Babaian. Studying the metadata in the sequence read archive using text embeddings and unsupervised learning.
Continuous and Real-Time Audio Diffusion through freeze maps (Ongoing)
Exploring the use of freeze maps to use stable diffusion to generate audio in real time
Fine-Tuning LLMs on small datasets for real-time script generation in the performing arts
Studied ways to use QLoRa fine-tuning for LLMs with small theatrical datasets
Manipulating the historical latents of large diffusion models for targeted generation (VoiceScroll Project)
Discovering how to manipulate old stored latents for generation of images consistent with the current latents
Interesting State Learning as a paradigm for Reinforcement Learning in Mario
Using a learned probability distribution to select interesting states for reinforcement learning trajectories to start from