Dinesh Dev Pandey

Booking Engine

• Design and development of Booking Engine web application along with management of team of 3 people.
• Handled different software development stages like requirement gathering, feature design, data modeling and backend development
• Mock API development in Postman to parallelize frontend and backend development
• REST API development using AWS stack like lambda, GoLang, API gateway, DynamoDB, S3 and Cognito
• Unit testing and integration testing of API
• Interface/API development for integration of site controllers
• Interface/API development for integration of Google Hotel Ads API

ValueChain

• Incharge of ValueChain, which is smart hotel review analysis system
• Designed software architecture and handled backend
• Developed REST API using Laravel framework and AWS Aurora database.
• Worked with VueJs for frontend development

Price manager

• Designed an efficient database schema in NoSQL database mongodb
• Restructuring and migration of structured data into mongodb data format
• Development of REST API to access mongodb data in faster way
• Tools and Technology used : Nodejs, Expressjs, Python, AWS documentDB (mongodb)

Sentiment Analyzer

• Developed and deployed multiclass sentiment analyzer for Valuechain
• Used standard NLP techniques like Noise Removal, Lexicon Normalization, Object Standardization, Feature engineering, Statistical Features designing.
• Developed a flask API to use sentiment analyzer model
• Tools and Technology used : PyTorch, NLTK, sklearn, python, MeCab, Deep learning

Mobile GPU (Adreno) library development

• To port the image processing modules of Camera using OpenCL for mobile GPU and Optimize the Kernels for better performance.
• Implementation of modules to Adreno GPU, conformance Testing for output correctness and performance Measurement analysis.

Development of OpenGLES based equivalent standalone of mobile GPU libraries

• Development of the standalone version of different openGLES based GPU libraries and optimize the usage of texture memory.
• Understand the client software framework, Development of a openGLES based equivalent code for GPU library. Optimize the number of texture used.

Online Integrated development environment

• Developed an online Integrated development environment for shared memory, Distributed memory and hybrid memory architecture applications.
• User can develop application in different parallel programing languages like OpenMP, MPI, CUDA and OpenCL. Provide facility to select resources available in cluster, build, execute and profile applications.
• Technology used in the project are JAVA, Servlet, Html, JavaScript and JQuery

Parallelization of Cyber Forensic Application

• Parallelize cyber forensics application to search of keywords from large amount of data present in a file using Boyer Moore search algorithm.
• Technology used in project Distributed System Cluster with MPI, CUDA and C. parallelization of Selective Cationic Antibacterial Peptides application.
• This application calculates some of the cationic properties like Mean Hydrophobicity, Isoelectric point, Mean helical hydrophobicity and mean net charge of peptide sequences and to optimize the same code on GPU.
• Technology used in project Distributed System Cluster with MPI, CUDA and C.