Computer Science & Engineering and Information Technology (CSE&IT)

Dr. Himanshu Jindal

Dr. Himanshu Jindal
Assistant Professor (SG)
91-8054689490(M), ( 91) 01792 239237
For More Information Click here

Biography :

Dr. Himanshu Jindal is presently working as an Assistant Professor (Senior Grade) in the department of Computer Science and Engineering & Information Technology Department, at the Jaypee University of Information Technology, Waknaghat, H.P, India, since December 1, 2019. He has also worked as an Assistant Professor (Gr-II) in the same department from July 16, 2018 to November 30, 2018. Prior to that, he has also worked as Teaching Associate in Computer Science & Engineering Department at Thapar Institute of Engineering and Technology, Patiala (July 2015 - June 2018), Lecturer in Computer Science & Engineering Department at Rayat Bahra Group of Institutions, Patiala (September 2012 - July 2014) and Lecturer (Guest Faculty) in Computer Science & Engineering Department, Thapar Polytechnic College, Patiala (August 2011 - September 2012), respectively. He has received his Doctor of Philosophy (Ph.D.) degree titled “Procreation of Energy Efficient Topologies for Data Transmission in Underwater Wireless Sensor Network” in Computer Science & Engineering Department from Thapar Institute of Engineering and Technology, Patiala (March 2019). He has obtained his Master of Technology (M.Tech) with dissertation title “Image Zooming using Wavelet Coefficients” in the Computer Science and Applications Department from Thapar Institute of Engineering and Technology, Patiala (July 2014). He has completed his Bachelor of Technology (B.Tech) in Computer Science & Engineering from Shaheed Udham Singh College of Engineering and Technology, Tangori, Mohali, Punjab (July 2011).
He has more than 10 years of teaching and academic experience; and 9 years of research experience. He has strong coding capabilities that includes Procedural/Programming Languages: C/C++, Java, Asp.Net with C#, VB.Net, Arduino IDE, Scripting Language: HTML, XML, Javascript, Python, Database Language: SQL, PL/SQL, Scientific Tools: MATLAB, Scientific Writing: LATEX and Other Tools: VMware, Visual Studio, MS-Office, Edraw, AutoCAD. He has also integrated Arduino based Multi-parametric for sensing physical parameters data for monitoring pollution underwater. Also, he has designed image sensor to capture still images for detection of algae blooms and corrosion on underwater pipelines. He has more than 29 publications in his account including 4 patents, 1 copyright with h-index as 11 and i10-index as 12 having 260+ citations. He is currently guiding 02 Ph.D. students and has guided more than 20 B Tech undergrads. He has organized two summer schools on “Library Database Maintenance and Web Development” and “Advanced Java". He has organized 06 Scopus indexed conferences of IEEE as Technical Program Committee Chair, Hospitality Committee Member and Local Organizing Committee Chair Member, respectively. He has chaired 4 technical session in IEEE Scopus indexed conferences. He is also a reviewer of many journals and a member of TPC of different conferences such as PDGC, ICIIP, FTNCT, ICRCWIP, Computers & Electrical Engineering, Wireless Networks, Wireless Personal Communications, Journal of Supercomputing, and IJIGSP.

Research Interests:

Wireless Sensor Network

Information Retrieval

Data Transmission

Digital Image Processing

Computational Intelligence

Underwater Communication

Internet of Things

Arduino Programming

Machine Learning

Artificial Intelligence

Healthcare Data Analytics

Doctoral Research Supervision:

Kumari Monika (196210): Procreation of Automated and Ensembled Methodology for Fever Detection and Classification
Anuj Gupta (206201): Designing of Efficient Classifier for Analyzing brain Tumor Images

Undergraduate Projects Supervised/Supervising:

Year       Project Titles

2023       Case Study of Self Driving Car

2023       An Optimized Ensembled Framework to Secure IOT Network

2023       Handwritten Mathematical Expression Recognition using AI

2023       Reconstruction and Refinement of Images

2022       Conversion of Handwritten Text to Digitized Text

2022       Client Managed One to One and Group Chats by Hybrid Encryption

2022       Smart Assist

2022       Energy Efficiency in Mobile Device using Cloud Services

2022       Autonomous Image Caption Generator using Neural Network

2022       Pathfinding Visualizer

2021       Implementation of Encryption Algorithm

2021       Malware Detection with Machine Learning

2021       Image Reconstruction of Underwater Images

2021       Image Processing with Deep Learning and Neural Networks

2020       Transformation and Restoration of Satellite Images using GIS Technique

2020       Attendance System with Face Recognition using OpenCV

2020       Mood Detection using Facial Recognition

2020       Image Captioning

2020       Twitter Sentiment Analysis using Webapp

Open Project Titles:

1. Image Processing by using Python - Python is an open-source library used for image preprocessing. It makes use of machine learning with built-in functions and can perform complex operations on images with just a few functions. It works with numpy arrays and is a fairly simple library even for those who are new to python.

2. Detection of Credit Card Fraud System - Credit card fraud detection is the process of identifying purchase attempts that are fraudulent and rejecting them rather than processing the order. There are a variety of tools and techniques available for detecting fraud, with most merchants employing a combination of several of them.

3. Smart Health Consulting Application - This system aims at maintaining patient health records and even getting appointments from various doctors for related treatments. The system user must register as a member of this system and keep updating his medical history. Patients can then select from a list of specialized doctors for respective treatments such as (skin specialist, ENT specialist cardiologist etc) at particular locations. Patients may also select suitable appointment timings for their meeting.

4. Heart Disease Prediction - In this study, an effective heart disease prediction system (EHDPS) is developed using neural network for predicting the risk level of heart disease. The system uses 15 medical parameters such as age, sex, blood pressure, cholesterol, and obesity for prediction. The EHDPS predicts the likelihood of patients getting heart disease. It enables significant knowledge, eg, relationships between medical factors related to heart disease and patterns, to be established.

Author Publication Profile:
Book Chapter(s) :
Journal(s) :
Conference(s) :