Vaidheeswaran Archana

Data Product Manager, Women Who Code | Machine Learning Consultant

Vaidheeswaran Archana | Data Product Manager, Women Who Code Machine Learning Consultant

Master Thesis:TinyML for Solar Panels: Bringing Edge Computing Applications to Solar Energy Systems

August 2020

In this work, we work on novel applications of edge computing for Solar Power Systems for 1)Identification and Estimation of Power Loss of Solar Panels 2)Classification of Soiling on Solar Panels and 3)Solar Irradiance Forecasting through Sky Images:

ACL 2019: Pre-trained BioBERT with Attention Visualisation for Medical Natural Language Inference

August 2019

This paper explores the use of Bidirectional Encoder Representation from Transformer (BERT) for solving MedNLI. The proposed model, BERT pre-trained on PMC, PubMed and fine-tuned on MIMICIII v1. 4, achieves state of the art results on MedNLI (83.45%) and an accuracy of 78.5% in MEDIQA challenge.

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Convolutional Neural Networks In Classifying Cancer Through DNA Methylation

July 2018

A CNN based Deep Learning model that can classify the cancer of a new DNA methylation profile based on the learning from publicly available DNA methylation datasets

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Compositional Attention Networks for Interpretability in Natural Language Question Answering

October 2018

We propose a modified MAC net architecture for Natural Language Question Answering. Question Answering typically requires Language Understanding and multi-step Reasoning. MAC net's unique architecture-the separation between memory and control, facilitates data-driven iterative reasoning.

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Gallium Nitride Power Device Modeling using Deep Feed Forward Neural Networks


this work proposes deep feed forward GaN ML device models which are highly accurate and can predict the switching behaviour of the device without having to delve into the physics and geometry of the device.

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