What i do
CNN (DenseNet, ResNet, Inception), FCN, RNN (GRU, LSTM, bi-LSTM, stacked-LSTM, VAEs, Object Detection, Transformers, Transfer Learning, customizing, debugging and tuning Neural Networks.
Linear Regression, logistic Regression, KNN, Naive Bayes, SVM, RL, Bagging & Boosting (ensemble), PCA, SVD,regularization, accuracy measures, statistical analysis and modeling, and knowledge of end-to-end machine learning pipeline (feature engineering, data cleaning, data visualization, model deployment and serving)
Data structures and Algorithm, C++, Python, Java, GO Rust, Swift, Pytorch, Tensorflow, FastAI, Scikit-Learn, OpenCV, CUDA, HTML, CSS, JS.
Scrum, Agile process, UML, Build Pipeline, Junit-test, unit test, Java Docs, Doxygen, Build tools (Cmake, gcc, Make, gmake).
Full stack development: RestAPI, GRPC, Flask, NodeJS.
Mobile Development: Android (Java, Kotline), Flutter (Dart), Xcode (Swift), Figma, Adobe XD, Human Computer Intreaction Certified.
AWS Certified, Kubernetes cretified, Google Cloud platform, Azure.
Experience & skills
From developing deep learning based various components of visual scene
understanding deep learning pipeline to building C++ and CUDA based systems,
I had a phenomenal experience of wearing a lots of hats and taking ownership.
Implemented and trained CNN based models for next-generation QPCR and PCR analysis software using Python and Tensorflow. Improved existing system accuracy from 78% to 98%. Solved multi dye cross-talk problems. Developed various methodologies to evaluate the performance of the model according to the domain. Built front-end system to use the Genotyper
During the 3 months internship, got the pleasure of building a
computer vision application to detect defects in the railway
tracks and developing various data analysis algorithms.
In order to help the community with its need for reliable storage,
we built a MVP and launched it to aid people in finding
a place to store their belongings safely and conveniently