Shivam Gupta Email & Phone Number

Seattle, Wa, Us

Seattle, Wa, Us

Software Development Engineer at Internal Audit Process Automation (IA2) Team at Amazon.Developing highly scalable web applications for facilitating the process of Internal Audit at Amazon.Technologies: Python, SQL, AWS S3, EC2, React, TypeScript, JavaScript, jQuery, Git.AWS Services: CDK, EC2, CFN, SQS, Lambda, S3, ECS, CodePipelines.

Seattle, Wa, Us

Software Development Engineer in the Elastic File System(EFS) Team at AWS. I am the part of Neo-Quux (File-System Protocol) Team. Developing Highly scalable features for EFS. Responsible for the backend of EFS Data-plane, Server-side Development , Data Caching, development of efs-utils, Integration with EC2, Lambda, Fargate, ECS containers, EKS Contributing to EFS to Serve Millions of Customers for the faster Performance of the File Systems.•Responsible for the backend of the EFS (Elastic File System) Data-plane, Server-side Development, Data Caching, development of efs-utils. Integrated EFS with EC2, Lambda, Fargate, ECS containers, EKS(Kubernetes).•Designed and implemented the architecture for faster performance of the File systems, which served millions of customers. Especially the NFS data and metadata operations. Made the NFS data operations faster by 200%.•Implemented performance & load testing scripts to test the design of caching the file system’s NFS operations and improved latency from 0.6 ms to 0.1 ms which boosted the customer’s file system’s performance drastically.•Single handedly led the metadata caching project with multi-threading and made it available to customers and mentored the newly hired SDEs in the team and was the component owner of the efs-utils in GitHub.•Designed and developed an Access Point Increase limit to 1000 for mounting Elastic file system for the customers.•Designed many alarm monitors which helped in getting the latency impact on the customers w.r.t to the data and meta-data operations to detect the Customer contentious Workload on an application hosted on EFS.• Led EC2 RunInstances project from the Dataplane side of EFS.•Designed and implemented a lot of internal Applications (Canaries) that emulated the Customer workload internally for Load and Performance testing of the EFS.•Technologies: Java, Python, Ruby, Golang, SQL, AWS S3, EC2, Flask, NodeJS, JavaScript, jQuery, Git.AWS: Athena, EC2, CFN, SQS, Lambda, S3, ECS

Richardson, Texas, Us

• CS Grader for the Course CS 1336.014 Programming Fundamentals C++• Grading their Assignments and Providing Feedback to improve.• Helping Undergraduate Students in the C++ Programming.• CS Grader for the course: CS 3345 Data Structures & Algorithms Analysis• Helping students in Data Structures & Algorithms Projects and grading, providing the proper feedback as well.

Dallas, Tx, Us

Software Development Engineer(SDE) Intern (Data Science)• Worked with Digital Global Strategy Team(DSCE-Data Science Center of Excellence) on Lease Abstraction and Valuation & Advisory Services (VAS) at CBRE(Natural Language Processing-NLP)• Developed an End-to-End Web Application for the Lease Abstraction using Flask, where User Uploads a Lease Document and Extracts the Useful Business, Financial and Legal information automatically(Entities Like Operator, Client, etc) and can download or send for further requirements.•Developed many Deep Learning Based NLP Models like BERT, RoBERTa, XLMRoBERTa, Distill RoBERTA, BiLSTM, AutoML for this End-to-End Application which I managed to run these models at the Backend in parallel Processing which reduced the time by 50%.• Developed CI/CD Pipelines for Machine Learning Algorithms Backend of the application.• Implemented Parallel Processing and Multi-threading to make the Web application faster by Running the Models in Parallel at the Backend.• Handled the Backend with Multiple concurrent requests(1000s of requests) in that Web application by using Nginx, Gunicorn.• Developed the Algorithms that take the document (Income statement, Leases, Valuation forms) and converts them in a tabular format in order to do the calculation automatically for verification in Valuation & Advisory Services (VAS) of CBRE.• Technologies: Python, Java, Jupyter Notebook, NLP, GCP, Vision-API, Document-AI, Auto-ML, Tensorflow, Keras, Pytorch, Transformers, NLTK, AWS S3, EC2, MySQL, Git, JIRA, Heroku, Azure DevOps, Docker, Flask, NodeJS, MLFlow, KubeFlow, HTML, CSS, Bootstrap, FIGMA, JavaScript, jQuery, Ajax, MVC (Model-View-Controller) architecture, Nginx, Gunicorn.

Richardson, Texas, Us

• Worked on developing Deep Learning models for the evaluation of the coordinates of the swipe screen from the UI Images of the apps.• Developed the ConvLSTM model for prediction of the coordinates of the swipe screen/single tap from the UI Images hierarchy and image traces from around 100,000 apps.• Worked on Reinforcement Learning for automatic GUI bug detection in android Apps!• Wrote Python Scripts for M-ary Trees for the extraction of the relevant features in the JSONs.• Worked on Android studio to calculate the results of the Reinforcement Learning model using java for Code coverage Calculation.• Did the testing of the Real-time GUIs on multiple applications on Android studio by running the pre-trained Reinforcement Droidmate models.• Calculated the code coverage in GUIs of different Apps using XML and JSONs for the recognition of bugs in Android Studio.• Worked on Droidmate by running/testing on pre-trained reinforcement models to check the code coverage in the android apps.

Richardson, Texas, Us

• Computer Science(CS) Mentor At Computer Science Mentor Center (CSMC), UTD•Helped Undergraduate Students in their Course Works like Discrete Structures, Data Structures and Algorithms, Operating Systems, Programming Fundamentals and Solving their Doubts.•Managed CSMC by helping students and grading their Quizes.

Hadapsar, Pune, Maharashtra, In

Artificial Intelligence, Deep Learning(ML), Computer Vision, Image Processing, NLP, Python, Java, C#, MicroServices, MySQL, AngularJS •Developed End to End Applications and models that predict buildings and tanks in satellite images using deep learning algorithms using Python to calculate the Total Insurance value, latitude and longitude of the buildings using Python and Java. •Implemented many models like ResNet with refine net , VGG, AlexNet, etc using python libraries like tensorflow, keras, scikit, numpy ,pandas, etc. to calculate the Total Insurance value, latitude and longitude of the buildings. •Developed Machine Learning Pipelines For this application (CI/CD Pipelines). Reduced the Execution time the pipeline by 50% using Parallel Processing.• Increased the revenue of the company by 20% through this application.• Integrated this application with another Application "TrueCAT" which was written in C#, MySQL, AngularJS, NodeJS.•Worked on Improving the ResNet with refine net model for increasing the accuracy by Bagging & Boosting, also worked on NLP to extract the natural disaster’s information. •Worked on Web Scraping for particular websites for the extraction of the interior information (Financial Content Value) like ACs, Number of Rooms, number of floors for the rough estimate of the Content Financial Property Value.•Developed many Principal Component Anaysis(PCA) Models to Analyze my predictions for Buildings and the features in satellites images for increasing the Accuracy.•Developed Clustering and Classification Algorithms for the interpretation of the structures of the roof tops of the buildings like flat,gable, complex,etc. •Worked on assets Detection over the building Rooftops as well using the Satellite Images in Java and Python.•Technologies: Spring, Java, Python, C#, MySQL, MongoDB, Flask, Tensorflow, Keras, JSON, JavaScript, NodeJS, React.

Kanpur, Up, In

Machine Learning Intern under PROF. GAURAV PANDEY, IIT Kanpur( Machine Learning, Computer Vision, Image Processing, Python) •Worked on the Support Vector Machine (SVM) and Convolutional Neural Network (CNN) based Facial emotion recognition in static images, videos and in Real Time as well in Python with an accuracy of around 93.7%.•Worked on OpenCV and Dlib libraries for the detection of Face and the Facial Landmarks in real time and static images and trained the model using various Machine Learning algorithms from Cohn-Kanade Datasets(CK & CK+).• Developed a GUI using Tkinter Python where the User can upload images/Videos or start the live streaming for facial Emotion Recognition.•Technologies used: Python, Flask, Node.js, AngularJS, Express, MySQL, JavaScript, EJS. •Completed the research paper titled "Facial Emotion Recognition in Real-time and static images" got accepted and presented in International Conference on Inventive systems and Control ICISC conference 2018 and got published in IEEE digital Xplore library!

New Delhi, In

Machine Learning Intern under PROFESSOR TAPAN K. GANDHI, NeuroComputing Lab, IIT Delhi( Machine Learning, Signal Processing, Wavelets, MATLAB) • Worked on the Detection of Obstructive Sleep Apnea using Heart Rate Variability in ECG Signals using the Time Domain and Frequency Domain methods and Classification is done using SVM(Support Vector Machines) and K-Means Clustering.• Developed a GUI using Matlab for this application where the Doctors can upload the ECG signals for Apnea detection.•Developed an end-to-end application using AngularJS, NodeJS, Django where doctors can upload the ECG signals and detect. • Also worked to calculate the LF/HF Ratio in the ECG signals using Wavelets Packet Decomposition and FFT Methods for the detection of Obstructive Sleep Apnea and Compared these two methods for the LF/HF Ratios values during Sleep Apnea.• Completed the Research Paper titled "DETECTION OF OBSTRUCTIVE SLEEP APNEA USING HEART RATE VARIABILITY IN ECG SIGNALS" which is under review.•Technologies used: Python, Django, Node.js, AngularJS, Express, MySQL, JavaScript, EJS.

Prayagraj , Uttar Pradesh, In

Machine Learning Intern under PROF Mr. DUSHYANT KUMAR SINGH, CSE Department MNNIT, ALLAHABAD (Machine Learning, Computer vision, Image Processing, Robotics, MATLAB) •Worked on the Optical Flow-Based moving Object Detection and Tracking using MATLAB which is based on the Lucas Kanade method and also modified in the manner to reduce the effect of noise and increase the precision.• Developed a GUI using Matlab for this application where the user can upload the video or start the live streaming for Moving Object detection.•Applications of this technique are to use it for interaction between machines and humans, security and surveillance, supplemented authenticity, monitoring traffic in roads, medicinal image processing and other video processing. Also Published a Research paper in IEEE on this research project.•Technologies used: Python,MATLAB Flask, Node.js, AngularJS,React, Express, MySQL, JavaScript, EJS. •This system was successfully working on many live videos through webcam and videos captured through camera. •Also implemented Face detection on images using Viola Jones Algorithm.

Master'S Degree In Computer Science & Engineering, Computer Science (Intelligent Systems- Artificial Intelligence)

Bachelor’S Degree, Electronics And Communication Engineering

Science(Pcm)

High School