I'm a Machine Learning Engineer who's been building AI for 3+ years. I love creating things that actually help people.
I'm really into NLP and Computer Vision, and I'm always looking for a good challenge to tackle next.
Used BERT model to learn optimal splits within the paragraph/document ensuring maximal contextual information is preserved in the resulting chunks. Achieved an improvement of 77%, 19.61%, and 10.49% F0.5 score on CoNLL-2014, BEA-Dev, and FCE-Test datasets respectively from current SOTA models. Paper accepted at BDA 2023.
View Project →Introduced an optimized weighted ensemble model that predicts the risk of Type 2 Diabetes. Worked on improving the performance by developing custom cost function for weights. Technologies: Scikit-learn, Seaborn, Ensemble Learning, SciPy.
View Project →Developed an Encoder-Decoder model using CNN and LSTM to generate captions from an image. Encoded Images using InceptionV3 model and words using GloVe. Technologies: Keras, CNN, LSTM, GloVe, Transfer learning.
View Project →Won Smart India Hackathon 2022 against the problem statement KK1182 (Shared usage of workshops/labs across india) held at IIT Guwahati.
View Project →Built and launched a startup from idea to MVP in under 10 hours. Won $1,000 cash and an opportunity for $1M funding via SwarmSpace by Together Fund.
Took home 1st place among 120 teams with SynthScene — a project reimagining brand advertising through virtual product placement.
Won the Metadome.ai Emerging Tech Hackathon, pushing the boundaries of what's possible in immersive spatial computing.
Won Smart India Hackathon 2022 against the problem statement KK1182 (Shared usage of workshops/labs across india) held at IIT Guwahati.
Among the top 3 students from ADGITM who made it to Amazon ML Summer School 2022.
Placed 1st among 300+ participants in MLH's Neighborhood Hacks with AasPaas.
Secured 1st among 600+ participants in Coders vs COVID Hackathon with ArchSearch.
Winners of HackISOLATION by IOSD and 2nd runner-up in Innerve Hackathon, by IGDTUW.
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