nitin-sharma-profile-mriirs

MANAV RACHNA INTERNATIONAL INSTITUTE OF RESEARCH AND STUDIES (DEEMED TO BE UNIVERSITY) FARIDABAD Sector 43,Aravalli Hills, Manav Rachna Campus Rd, Faridabad, Haryana 121004

Mr. Nitin Sharma Designation: Assistant Professor Qualifications: M.Tech(Data Science),B.Tech Email: nitinsharma.fca@mriu.edu.in Experience: 6 Years Research Interest: Machine Learning, Data Science, Artificial Intelligence, Data Mining, Statistics, Data Visualization,Blockchain.

Journal Publication Details:

A. International/National Journals

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Bitcoin Price Prediction using Neural Networks, 15 May 2020 Information and communication technology for intelligent systems (ICTIS)- 2020 SPRINGER Lecture Notes in Networks and Systems 141, https://doi.org/10.1007/978-981-15-7106-0_59.

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Real Estate Price’s forecasting through Predictive Modelling, 15 May 2020 Information and communication technology for intelligent systems (ICTIS)- 2020 SPRINGER. Lecture Notes in Networks and Systems 141, https://doi.org/10.1007/978-981-15-7106-0_58.

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Sharma Nitin & Singh Gurpiyar. 2015. WIRELESS POWER SHARING –A NEXT GENERATION POWER SHARING SYSTEM. International Journal of Research in Science and Engineering. 86-89.

Volume: 1 Issue: 3 e-ISSN: 2394-8299 p-ISSN: 2394-8280.

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Sharma Nitin, Siddharth Manohar & Shubham Singh. SMART AGRICULTURE- AN AMALGAMATION OF MACHINE TOMACHINE TECHNOLOGY INTO AGRICULTURE SECTOR. International Journal of Advances in Electronics and Computer Science. 123-126.Volume: 2 Issue: 12 ISSN: 2293-2835.

Novel Approach for an efficient and secure image identity-based signature computing system, International Conference on Smart Innovations for Society (ICSIS-22) held on 06-07 May, 22 at Poonima Institute of Engineering and Technology, Jaipur.

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C. Patent

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Australian Innovation Patent is filled with application -2021105177, the title of the invention is Intelligent System & Method for Health Care Information Exchange in Distributed Frameworks Based on Blockchain Technology.

Indian Patent is published with application number-202211004112, the title of the invention is wirelessly controlled intelligent system for digital door lock applications using IOT. Data Science and its correlation to big data and data driven decision making with application number202211032892.

Administrative Responsibilities: 1. SPOC for Code Tantra 2. NAAC Criteria 3. International Conference Professional Affiliation:  IBM Certifications in Quantum Computing, Machine learning with python, Data science methodologies, Enterprise Design and Thinking.  Computer Science Teacher Association  Machine Learning and AI Association Projects Filled

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Proposed and submitted the project for grant on Earth Management System by SERB. Different form of datasets to be used like raster, geographical. Techniques to implement are Convolution neural networks and LSTM.

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Price Prediction of the Bitcoin using machine learning techniques: Time series analysis performed on the different time stamp data set. Modelling techniques have been used using Linear regression, Polynomial regression and decision tree also used correlation matrix to do the evaluation.

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Real Estate price forecasting using machine learning techniques: Analysis and pre-processing performed on the dataset, correlation performed on the columns of the data set. Linear Regression and Random Forest technique implemented and concluded with the accuracy of 81%.

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Data Analysis performed on the data COVID-19 data set. Concluded the state wise visualization on the parameters (Confirmed, cured and death).

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Smart handheld health monitoring device for rural India, DMIMS(DU) NewGen IEDC, Datta Meghe Institute of Medical Sciences. DST Project.

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Soft Computing based Irrigation Control System in Precision Agriculture, DMIMS(DU) NewGen IEDC, Datta Meghe Institute of Medical Sciences. DST Project.

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Designed the churn model for customer retained and exited. Taken the parameters geography and gender for the processing and implemented using random forest where n_estimator=50. Modelling technique used is random forest provided with 80% of data in training which provides 87.2% of accuracy.