Gaurav Bhatt
Student Researcher at Vector Institute
Vancouver, British Columbia, Canada
Summary
🤩
Rockstar🎓
Top SchoolGaurav Bhatt is a Ph.D. researcher in computer vision and machine learning at UBC with nine years of experience bridging academic research and industry practice. He co-founded a health-tech startup, served as CTO at Mediledge, and has supported enterprise ML teams as a technical facilitator at the Vector Institute, demonstrating an ability to translate research into product-focused solutions. His GitHub showcases hands-on implementations of deep learning, NLP, and CV papers using Keras and TensorFlow, reflecting practical expertise in transfer learning and multimodal models beyond theoretical work. A former research assistant at IIT Roorkee and IIT Hyderabad and a short-term research fellow at Amazon, he blends rigorous academic training with startup and corporate collaboration. Based in Vancouver, he combines mentorship and technical leadership to shepherd ML projects from prototype to deployment.
9 years of coding experience
5 years of employment as a software developer
Indian Institute of Technology RoorkeeDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of British Columbia
English, Hindi, garhwali
Github Skills (10)
mask-rcnn10
keras10
faster-rcnn10
deep-learning10
python10
nlp9
computer-vision8
scikit8
scikit-learn8
audio-processing6
Programming languages (1)
Github contributions (5)
GauravBh1010tt/DeepLearn
May 2017 - Dec 2022
Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.
Role in this project:
Data Scientist
Data ScientistContributions:2 releases, 219 commits, 5 PRs in 5 years 7 months
Contributions summary:Gaurav appears to be implementing and refining a deep learning model for a multi-modal learning task, as evidenced by changes to `DeepLearn_cornet.py` which includes the build and training of a model with various layers and loss functions. The code involves loading data, splitting it into training and testing sets, and utilizing Keras for model definition and training. The user demonstrates an understanding of deep learning concepts like CNNs and loss functions, as well as transfer learning.
nlpaudio-processingpythondeep-learningcomputer-vision
GauravBh1010tt/Solving-NP-Hard-problems
Nov 2016 - Dec 2016
Contributions:51 commits, 50 pushes, 1 branch in 18 days
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