I am a Graduate student in Computer Software Engineering at Arizona State University have worked with Dell close to 3 years. I have been a part of dell digital excellence team and have created solutions for both native and hybrid mobile platforms. I have a strong background in problem solving and algorithms.
I love to build mobile apps and have developed various mobile applications to solve intricate use cases of some of renowned organizations like AVIS Car Rental, Prudential, Volaris, Dell Digital Studio and NASA- for Psyche Asteroid Mission.
I am very keen to work in the field of Machine Learning and AI and am working in VISA Research Lab of Arizona State University to explore the ways to perform machine learning on Mobile devices.
I am pursuing my Grduate education having a focus on Machine Learnig technologies. I have completed the courseera Deep learning Specialization. In five courses, I have learnt the foundations of Deep Learning, understood how to build neural networks, and learned how to lead organize machine learning projects. I have implemented Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and went through various papers leading the ML research today. I have worked on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. Python, TensorFlow and Keras are frameworks which I have used for all of the above implementations. Currently I am working at VISA LAB. My focus is to explore machine learning on Mobile Devices. How large models can be trained quickly on memroy constrained devices like Cell phones. Focus is to try to find a way to accelerate the hardware for deeplearning operations like inference, backward-prop, forward-prop.
I have worked with Dell international Services which is now NTT-Data Services for close to 3 years as Mobile application Developer. I have strong programming experience in front end development and have developed solutions for mobile devoices using Android, Swift, AngularJS, Phonegap, Javasript, Ionic, Bootstrap technology stack. I have developed both native and hybrid mobile applications. I have worked with some of the renouned clients in teh industry like Avis, Prudential, Volaris. I have successfully played the role of tech lead in Prudential application and ensured the code quality and standards to be able to deliver the oprimal solution. I have also been awarded Bronze award in Dell for exceptional performance by a new comer for successfully delivering three projetcs simultaneously. Currently I am NASA-Psyche Programming Intern and developing Android and iOS Applcations for NASA's Psyche Astroid Mission. Also, I am the president of the undergoig NASA Capstone Projects- helping undergraduate students to succesfully develop and optimal mobile application.
Student Data Analysis and Prediction
"Student Data Analytics and Prediction" : Applying Machine learning to predict students GPA based on their performance in the assignments of courses. Also, to predict the hardness of a subject based on the dropout rate and performance in that subject. System is a web application having a dash board which has graphical representation of the predictions.
Supervised ML model: predicting cholestrol level
Co-Hosted by: Arizona State University, Icahn School of Medicine at Mount Sinai, and
Columbia University
Used data to make predictions and test hypotheses,
Worked with high dimensional and heterogeneous data,
Built generalizable models that are robust to errors and missing data,
Figure out how well your model performs and how well it generalizes to new datasets,
Built and deployed a model in the real world, using modern data science tools.
Deep NN Image Classifier
"Image classifier Neural Net modal" : Developed a image classifier having 50 layered Neural Net to predict the image of a cat with a accuracy of 82 %, later improved it using Adams algorithm to 97%. Technical stack: Python, Numpy, matplotlib.
VISA LAB: ML on mobile Devices
Exploring the ways to accelerate the training on memory constrained devices like cell phones
AVIS
Avis is the largest Car Hire Company based in US. It has Offices in more than 12 countries.
This application provides the user the accessibility to various types of cars.It has so many features like book the car pay later, extras etc.Our aim was to increase the scalability of the application to efficiently manage the increase the customer base.It was a phone gap application targeted for the iOS, android and windows devices.
Android App
iOS App
Prudential
Prudential is one of the biggest insurance organisation in United Kingdom and they assist the teachers to plan their retirement properly by taking the AVCs (Additional Voluntary Contributions).So for this they go into universities and give a presentation to the teachers. Prudential wanted to make their presentation more lucrative and indulging for the teachers.the solution which we came is following: We developed two apps one for presenter and other for Teachers. The application has a feature that allows the presenter to trigger a question during presentation and ask questions regarding to the slide and in turn the teachers will get a notification and they can answer and in turn presenter can see the responses of the audience in the form a chart and accordingly modify the pitch of the presentation.
NASA
Work in progress for mobile applicaitons targetting ios and android platforms which showcases all the important updates about teh NASA-Psyche Astroid Mission.
Oracle
The application was developed using the Oracle Mobile Application Framework and targeted iPad and android tablet. The application was for Insurance broker agents and the idea was to give a consolidated place to receive the information on Monthly commissions and estimate yearly bonus. Target device iPad retina 8.3 or more.This application was presented in the "Oracle Open World" held in San Francisco and was considered as a great solution in that space.
