Hi everyone. My name is Sanjiv Parthasarathy. I am currently a high school senior in Allentown, PA. I was originally introduced to AI and ML when collaborating with a professor at Lehigh University on a research project. I am very interested in this project and hope to become much more well versed in the topics that it addresses.
Would love to know how’s it going mate?
Appreciate your idea of diving into STEM and I wish you good luck
I’m a senior high school student from New Delhi, India and I want to pursue deep learning in my higher education. I spent the last 2 years studying Machine Learning having completed multiple specialisations from deeplearning.ai Google, IBM, Imperial College London and many other courses (ALL CERTIFICATES ON MY WEBSITE). Before that, I’ve worked as a Front End Developer in a leading educational startup. I’ve also worked a lot with IoT and Robotics having won multiple hackathon’s and representing my projects in the National Science Fair consecutively for 2 years. Two of my projects on Fake News Classification and Regressional Analysis of Primary Biliary Cirrhosis are currently being mentored by Intel under the AI4Youth program. I’ve been through the deeplearning.ai AI For Medicine specialisation and also been through some other courses/projects on Genomics/Prognosis/Diagnosis. I’ve worked a lot with JAX based ecosystems having multiple contributions to google/Trax and Flax. I saw the jaxchem repo on Github and was curious. The codebase looks great but it has been quite dormant lately, would love to contribute to the repository if the project is still active.
I hope to pursue my Bachelors ( Hopefully with integrated masters ) from the United Kingdom. I’ve applied and already gotten an offer from the University of Birmingham, hoping to get into University of Edinburgh as well (Fingers Crossed )
I’m currently working on Attention and Self-Supervised Representation Learning. Currently working on BioBERT and the ML Reproducibility Challenge.
I initially came to know about Deepchem after I saw the Gradient Descent podcast by Weights and Biases.