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Hi there πŸ‘‹

I am a pre-doctoral fellow at IIM Bangalore in the field of decision science, under the mentorship of Dr. Saudeep Deb. Here, I have worked on developing novel methodologies for predicting disease outbreaks and evaluating them using experimental and simulation approaches. Currently, I am focused on quantile autoregression and its efficiency in predicting higher values in time series data.

I am a dedicated researcher with a post-graduate degree in Statistics and a Master’s in Population Studies. With a profound interest in public health research. With a master's in population studies from the International Institute for Population Sciences in Mumbai, my academic journey has been enriched with a comprehensive MSc in Statistics from Sardar Patel University, Anand, Gujarat, and a BSc in Statistics from Savitribai Phule Pune University, Maharashtra.

Professional Journey

In my recent role as a Statistician and Jr Data Manager at Johns Hopkins India Private Limited, Pune, I played a pivotal role in supervising data management staff, developing clinical risk prediction methods, and contributing to the statistical analysis plans for complex public health and clinical research projects.

I have worked on many freelance projects, showcasing my proficiency in designing surveys, analyzing clinical data, and leveraging statistical methodologies.

Shreyash Deshmukh's Projects

brain-vgg icon brain-vgg

Low-grade gliomas (LGGs) are a diverse group of primary brain tumors that often arise in young, otherwise healthy patients and generally have an indolent course with longer-term survival in comparison with high-grade gliomas.In this study , we trained model for automatic lgg brain tumor detection by fully connected convolutional neural networks. The paper presents a network and training strategy that relies on deeper U-Net architecture design . Convolutional Networks for Biomedical Image Segmentation paper was published in 2015. Our method was evaluated on datasets of 20 patients were obtained from TCIA, which contain 20 low-grade brain tumor cases. Cross validation has shown that our method can obtain promising segmentation efficiently.

notebooks icon notebooks

Jupyter Notebooks with Deep Learning Tutorials

resume icon resume

my resume built in R with pagedown::html_resume

shr.github.io icon shr.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

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