My specialization

What i do

Deep Learning

CNN (DenseNet, ResNet, Inception), FCN, RNN (GRU, LSTM, bi-LSTM, stacked-LSTM, VAEs, Object Detection, Transformers, Transfer Learning, customizing, debugging and tuning Neural Networks.

Machine Learning

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)

Software Development

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.

Cloud Computing/Deployment

AWS Certified, Kubernetes cretified, Google Cloud platform, Azure.

Experience & skills


Aug 2013 – Present
Machine Learning

Third Insight

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.

Sep 2013 – Oct 2016
ai specialist

ThermoFisher Scientific

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

Sep 2013 – Oct 2016
Data Science Intern


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.

Sep 2013 – Oct 2016


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

AI (Deep Learning: CNN, LSTM, Transformers, ML: Regression, SVM, SVD, Kmeans Navie Bayes, PCA. End-to-end pipeline)
Web development
Machine Learning
C++, Python, Java
Deployment(Cloud: GCP, AWS Certified, Kubernetes Certified, Build pipelines, docker, AB testing)
Design Patterns

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lines of code


Research Paper


projects done