Sahil Nalawade

WORK HISTORY

SKILLS

ABOUT SAHIL NALAWADE

Skills:• Primary skills: Machine learning and Deep Learning Analysis, Image processing, Medical data analysis.• Software Tools: Python, R programming, MATLAB, Linux, Shell Script• Python Package (Machine Learning): Keras, Pytorch, Tensorflow, Theano, Fast AI• Python libraries for Machine Learning: Keras, Tensorflow, PyTorch, Theano, Scikit-Learn• Python libraries for Image Processing: OpenCV, Scikit-Image, Scipy, Nipy, Npiype, Nilearn, Nibabel, SimpleITK• Data visualization tools: Matplotlib, seaborn, ggplot.• Cluster and Cloud computing: SLURM, BioHPC• Matlab Libraries: SPM, FSL, ANTS, Homer, Easytopo, Brainstorm, EEG LAB• Troubleshooting: GeeksforGeeks, Github, Stackoverflow, Kaggle, Leet code• Statistical Tool and Analysis: R programming, Microsoft excel, regression, correlation, ROC analysis, t-test, ANOVA.• Deep Learning Architectures: CNN, DNN, GAN, VAE, Autoencoders, Inception, Res-Net, Dense-Net, SE-Net, Efficient-Net, Capsule-Net Deep Learning Projects: 1. Semantic Segmentation for brain tumor images, segmenting tumor into subtypes of edema, non-enhancing tumor and enhancing tumor using deep learning algorithm: 2D and 3D CNN Networks.2. Classification of clinical tumor images with molecular subtypes using Dense-Net, Res-Net and Inception Network3. Machine learning analysis on brain tumor dataset: Predicting Survival analysis for the brain tumor subjects using classical machine learning networks.4. Improving Resolution (Super-Resolution): Enhancing the image quality of the under-sample medical image using 2D Deep learning algorithm.Google Scholar Link: & hl=enWebsite - https://sahilnalawade.github.io/portfolio/Please feel free to reach out for any queries, opportunities or feedbackThanks & RegardsEmail ID: s••••••••@gmail.comPhone:+16•••••••95