I am a PhD candidate in the Department of Biomedical Engineering at Johns Hopkins University with expertise in machine learning, deep learning, and signal processing. Current areas of interest: continual learning, reinforcement learning, generative modeling, computer vision, and out-of-distribution (OOD) generalization.
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                  Johns Hopkins University
 - Baltimore, MD
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  11:31
  
(UTC -12:00)  - https://laknath1996.github.io/
 - @AshwindeSilva1
 - in/ashwin-de-silva-6852b14b
 
Highlights
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  neurodata/prolearn
neurodata/prolearn PublicProspective Learning: Learning for a Dynamic Future (NeurIPS 2024)
Python 9
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  neurodata/value-of-ood-data
neurodata/value-of-ood-data PublicThe value of out-of-distribution data (ICML 2023)
Python 10
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  gen-models
gen-models PublicCourse project for EN.553.741 Machine Learning II at JHU. Implements Wasserstein GAN, variational autoencoder and denoising diffusion probabilistic models.
Python
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  semi-supervised-learning
semi-supervised-learning PublicRepository for the EN.553.738 High-Dimensional Approximation, Probability and Statistical Learning group project on graph-based semi-supervised learning
MATLAB 1
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  DeepPhaseUnwrap
DeepPhaseUnwrap PublicThis repository Introduces a joint convolutional and spatial quad-directional LSTM (SQD-LSTM) network for phase unwrapping in 2D images (ICASSP 2021)
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  sEMG-Hand-Gesture-Recognition
sEMG-Hand-Gesture-Recognition PublicThe source code for the real-time hand gesture recognition algorithm based on Temporal Muscle Activation maps of multi-channel surface electromyography (sEMG) signals (ICASSP 2021)
 
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