Vijay Kapse

Intermediate / Mid Level

AI Research Engineer

Role interests:

No role interests added yet.

Skills:

pytorch
python
cnn
rl
ml
ai
aws
gcp

Regional interests:

Remote/Anywhere

Country interests:

united kingdom
united states
germany

Bio

At Manipal Academy, my research in AI-driven coronary artery segmentation is advancing the early diagnosis of heart disease. Leveraging OpenCV-UNet++ pipelines, I have increased diagnostic accuracy to 95% while optimizing deep learning workflows on PyTorch, enhancing A100 GPU performance by 200%. My work also includes creating preprocessing pipelines for handling large datasets (2TB), improving data processing speed by 40%, and contributing to published research on CNN architectures for medical image classification.

With a Bachelor's degree in Data Science and Applications from IIT Madras, my academic foundation is rooted in machine learning and data analytics. During my tenure at IIT Madras, I analyzed NASA microbial data, identifying key bacterial species critical for hospital sanitation. Using network analysis, I developed actionable insights that influenced policy improvements and presented these findings at prestigious conferences such as IIT Kharagpur and IMSC.

Previously, at the Indian School of Business, I developed an AI-driven storytelling application that transformed over 100 textbooks into dynamic stories for schoolchildren. By integrating advanced generative AI models, the tool personalized content delivery, boosting student engagement metrics by 35%. Additionally, I optimized content generation using A/B testing and enhanced user experience through robust UI/UX designs and multi-platform integration.

My commitment lies in harnessing AI to solve complex problems in healthcare and education. With expertise in deep learning frameworks like PyTorch and TensorFlow, model optimization techniques, and deployment platforms such as AWS and GCP, I aim to create impactful solutions that drive innovation across industries.

Job Types:

Full Time