• “Analysing and Predicting Algorithm for social network analysis using graph based mining techniques in disease outbreak” - Intelligent approach for predicting Diseases whether building a model to help the Doctor or even preventing its spread in an area Worldwide, is accumulative day by day. Here we present a noble approach to predict the disease prone area using the power of text analysis tweet download obtained for a specific time span based on twitter search criteria “malaria” ,“dengue” , “chikunguniya” and “measeles” and alike epidemic outbreak in India.

           Team size           : 2

           Technology         : Machine Learning approach using Python  (ubuntu).

                        Input                 : Twitter Data contains 2,588,570 Records  .

URL: http://journalstd.com/gallery/83-oct2019.pdf

• “Workload Prediction Model for Autonomic Scaling of Cloud Resources with Machine Learning” –Cloud computing enables clients with on-demand access to software, platform, and infrastructure, in the form of services through the Internet. Client applications are executed over the cloud which is backed by Virtual Machines (VMs) and these VMs are hosted on top of physical servers. The amount of workload traffic received by the cloud changes over time. To fulfil these fluctuating workload needs, VMs must be automatically scaled up and down to guarantee that the quality of service (QoS) to the client is maintained, which, in turn, must be achieved by ensuring that the Service-Level Agreement (SLA) criteria are not breached. To achieve this goal of automatic scaling (also known as auto-scaling), the important task is to predict the future workload demands for cloud resources so that appropriate numbers of VMs must be made ready in advance so that the requirements of clients are met. The prediction is done on the basis of the past resource usage trends. In this paper, we propose an autonomic          

            Team size          : 3

           Technology         : Cloud Computing, Cloud Storage, Machine Learning using python                   

URL:https://books.google.co.in/books?hl=en&lr=&id=BAGiEAAAQBAJ&oi=fnd&pg=PA343&ots=k58VEsMN4D&sig=Q2TOYYrBSY6KfpLw1bXlszOEW58#v=onepage&q&f=false

• Database Schema Matching Approach in a Homogenous Distributed Database – Schema matching is one of the critical step and a basic problem in many database domains such as database integrity and semantic query processing. In the current and normal scenario the matching procedure is generally done manually which is quite time consuming and has numerous issues. In this paper we suggest an automated approach which can distinguish differences between two databases on schema-level, structure level and on constraint level in a homogenous distributed database based on SQL Server.

            Team size           : 3

            Technology         : SQL server, Database

URL                   : https://www.researchgate.net/profile/Wilson-Jeberson/publication/303842579_Database_Schema_Matching_Approach_in_a_Homogenous_Distributed_Database/links/5757d39408aef6cbe35f5c1d/Database-Schema-Matching-Approach-in-a-Homogenous-Distributed-Database.pdf

• Machine Learning based Workload Prediction for Auto-scaling Cloud Applications– Cloud computing is a ubiquitous computing paradigm that offers its users access to software, platforms, and infrastructure as services, on-demand, over the Internet. User requests for these services (also known as workload) are placed over Virtual Machines (VMs) for execution. These VMs are hosted over Physical Machines (PMs) to abstract processing capabilities of these PMs. Over a period, Cloud services experience fluctuations in the workload pattern. To match the resources required for serving the varying workload, VMs must be added or removed autonomically as performing the same task manually is inefficient. Moreover, VMs take some fraction of time to be setup before they can be used. The goal behind automatic scale-up and scale-down operations is to ensure that the Service Level Agreement (SLA) between the cloud service provider and cloud client is upheld and cloud users experience acceptable …

           Team size           : 3

            Technology         :  Cloud Computing, Cloud Storage, Machine Learning using python

URL:  https://ieeexplore.ieee.org/abstract/document/10114033

• Image Processing for Bird Watching using tensorflow – AMS This tool is developed for people who are interested in bird watching. The tool takes a image of a bird and the using the image processing the species and bird is predicted.

            Team size           : 3

            Role                   : To design algorithm, code functions and modules.

            Technology         : Python, Tenserflow, Kearas.

15+ Years 

Role and Responsibilities
Teaching Assignments:

• Conducting theoretical and practical sessions in UG, PG and Ph.D.
• Educate students according to the guidelines provided by the University.
• Ensuring high standards of professional practice, quality of teaching and learning of the subject(s) through effective learning materials, class tests, assignments etc.
• Subjects taught: Data Structure , Python Programming, Machine Learning, Data base ,Distributed Systems, etc.

Software Development:

• Written code, designed to abide by the standards of object-oriented programming.
• Developed software using C#, implementing pure OOP concepts.
• Implemented machine learning techniques using python
• Evaluated and inspected code written by other trainee/students for quality assurance and for advising on how to improve code efficiency.
• Bug fixing and supporting existing software.
• Tracked project financial metrics such as related purchasing, invoice distribution and accounts receivable

Additional Responsibilities Executed:

• Team Lead for in-house software development team.
• Exam Committee Member, VIAET
• Experiential Learning Program Head, Network Committee Member SHUATS.
• Lab-Incharge  Department of CS&IT.
• Software Development Team, SHUATS.

Member of Syllabus Revision Committee of UTTAR PRADESH Education Board Class 6-8 Subject Science