In the first phase, 6 faculty innovation projects have been approved and seed funds provided. In the 2nd phase, it is expected to approve about 60-70 projects.
The objective of the faculty innovation project scheme is similar to Student Pre-Start up projects but these projects are expected to have direct and leading involvement of the faculty.
Dr. Smriti Gaur
Department of Biotechnology
Prebiotic cookies using edible seeds
This project focuses on the development of functional prebiotic cookies formulated with nutrient-rich edible seeds and red rice.
The innovative combination offers not only unique ...
Dr. Suma Dawn
Department of Computer Science and Engineering & IT
Context-Aware Image Enhancement of Digitized X-Ray Film for Better Radiography Imaging
Radiography X-ray imaging is widely used to identify fractures, diagnose pulmonary conditions like pneumonia and neoplasms, conduct mammographic exams, and evaluate dental patholog...
Dr. Megha Agarwal
Department of Electronics & Communication
Reliable classification of cyclic alternating pattern (CAP) for sleep disorders
Cyclic Alternating Patterns (CAP) in EEG signals are a key biomarker observed during non-rapid eye movement (NREM) sleep and are crucial for diagnosing various sleep disorders. Thi...
Dr. Abhay Kumar
Department of Electronics & Communication
Substrate Integrated Waveguide sensor for detecting adulteration in edible oil and honey
The objective of the proposal is to develop a low cost sensor based on substrate integrated waveguide techniques to detect the adulteration of edible oil and honey. The adulteratio...
Dr. Bhartendu Chaturvedi
Department of Electronics & Communication
Design and Realization of Integer/Fractional Order Memristive Element Emulators
This project presents a novel and compact memristor emulator architecture based on a single active element and a grounded capacitor, utilizing a Current Backward Transconductance A...
Dr. Ashish Gupta
Department of Electronics & Communication
Mr. Raghvenda Kumar Singh
Department of Electronics & Communication
Metasurface-based broadband lineartocircular polarization converters for modern wireless communication
This project aims to design and develop a broadband linear-to-circular polarization converter using metasurface-based technology for advanced wireless communication systems. Metasu...
Dr. Hemant Kumar
Department of Electronics & Communication
Dr. Parul Arora
Department of Electronics & Communication
Automated Photoluminescence Detention using image processing
The proposed project aims to develop a low-cost and portable alternative for sophisticated photoluminescence measurements, making it suitable for applications where mobility and sp...
Dr. Megha Agarwal
Department of Electronics & Communication
Reliable classification of cyclic alternating pattern (CAP) for sleep disorders
Cyclic Alternating Patterns (CAP) in EEG signals are a key biomarker observed during non-rapid eye movement (NREM) sleep and are crucial for diagnosing various sleep disorders. This project presents a simple yet highly accurate system for classifying the two primary phases of CAP, namely Phase A and Phase B. The EEG signals are divided into small segments and processed using Gaussian filters to isolate sub-band components. From these, a set of statistical features is extracted, and significant features are selected using the Minimum Redundancy Maximum Relevance (mRMR) technique.
To evaluate classification performance, three machine learning models are tested, with the k-nearest neighbor (kNN) classifier achieving the best results: 79.14% accuracy and an F1 score of 79.24% on a balanced dataset. The method also performs effectively on unbalanced data. The system is not only computationally efficient and easy to implement, but also demonstrates superior performance compared to existing approaches, making it a strong candidate for real-time clinical deployment in sleep disorder diagnostics.
