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Undergraduate Projects​

Learning by doing

At NIIT University (NU), “Learning by doing” is not just a catchphrase. The spirit of enquiry informs everything that we do. Every student, including undergraduate students, are given the opportunity to connect classroom learning with independent research that suits their special interests under faculty mentorship. NU research spans multiple disciplines, labs and innovation centres. Students get the opportunity to present co-authored research papers and present research at conferences. This teaches students how to write grant proposals, develop research budgets, manage projects, and affords them valuable networking experience. The ‘hands-on’ learning experience helps students refine their specific interests beyond the classroom.

357

R&D projects executed successfully by BTech students since 2013-14

R&D Projects

NU’s Research and Development (R&D) Projects is a core course for all undergraduate students in their sixth semester. The aim of this well-thought-out programme is to train students to perform research as co-investigators in faculty research and to familiarise themselves with the activities and methodologies generally followed during the research process.

NU faculty share research areas, from which students can choose a subject of interest. Over the course of a semester, students survey literature related to the subject, identify research gaps and challenges, and narrow down the specific gap/challenge they want to pursue. Subsequently, the students design and implement a complete solution in consultation with their faculty mentor. They present and demonstrate their solutions during the final evaluation.

Advanced R&D Project is offered as an open elective in the seventh semester to the students with aptitude and carries the same credits as other open electives. Students who show promise in their sixth semester R&D project are given the opportunity to extend their research in the Advanced R&D Project under the same faculty mentor.

Advance research may involve the application of the same technique to different problems; fine tuning/improving the technique to get a higher precision/accuracy; survey more recent literature on the subject; devise instruments to collect data; data gathering and analysis, etc., in close collaboration with the faculty mentor. Lastly, students will create a comprehensive report/research article under faculty guidance. Their final evaluation will be based on mid-semester evaluation, end-semester evaluation, mentor’s evaluation and students’ final report/research article.

Why engage?

Research is crucial to overall student development for many reasons. The learnings and takeaways are different for each student. But there are some common benefits to engaging in research projects from the undergraduate years.

It develops students’ critical thinking and problem-solving skills as well as their soft skills such as communication, teamwork, etc. Research allows students to hone their quantitative analysis, gives them access to labs and innovation centres beyond their classrooms, and surrounds them with the best intellectual minds in their subject of interest.

Research project outcomes are exhibited and transmitted through publications, conference papers, prototypes, patents, etc., giving students authorship and ownership of their work. Participation in research projects also inculcates a research bent of mind in all NUtons, irrespective of whether they intend to pursue research as a career or not. NU’s signature Research Assistantship Programme (NURap) and Travel Assistance Programme (NUTap) are valuable student aids during and post their R&D project.

Excited by the possibility of real-world research? Check out what NUtons are already doing

Students:
Aditya Joshi, Jitender Reddy Kalli, Shravya Gupta

Faculty Name:
Dr Gaurav Gupta

Objective:
To find evidence of correlation between probiotics and gut health.

Methodology:
Isolating novel LAB bacteria and applying it as a probiotic with anti-cancer properties. Testing the probiotic’s anti-toxic and anti-cancer properties to investigate whether it can act as a mediator for treating cancers.
Students:
Deergha Borker

Faculty Name:
Dr Sudeep Goswami

Objective:
To broaden the spectrum of antimicrobial activity of a powerful bacterial membrane targeting antimicrobial peptide ‘Nisin’ at varying pH range simply by conjugating it with organic acids followed by developing Nisin-Nanoparticle composite

Methodology:
Many food-borne drug resistant pathogens have evolved to evade antibiotics meant to kill them by changing physical parameters such as pH. Nisin being an FDA-approved food preservative inactivated at higher pH. The nanocomposites can be characterised and synergistic antimicrobial interaction of nanomaterial with Nisin is further tested on targeted microbial strains.
Students:
Aditya Joshi, Jitender Reddy Kalli, Shravya Gupta

Faculty Name:
Dr Narayan Kumar

Objective:
To specifically identify APC-represented peptides unique to lung cancer to be used for therapeutic purposes. Methodology: Identify and eliminate all peptides that show similarity above the degree of similarity (DoS) threshold values so as to prevent any off-target cyto-toxicity. Use multiple computational techniques and novel strategies to mitigate current challenges associated with existing strategies to develop an improved version of the same.
Students:
Amit Ladha, Soumya Shah

Faculty Name:
Dr Gaurav Gupta

Objective:
To find evidence of correlation between pro-biotics and gut health.

Methodology:
Isolating novel LAB bacteria and applying it as a pro-biotic with anti-cancer properties. Testing the probiotic’s anti-toxic and anti-cancer properties to investigate whether it can act as a mediator for treating cancers.
Students:
Tekuru Vishnu Koushik and Anushka Chakraborty

Faculty Name:
Dr Utkarsh Raj

Objective:
To identify potential plasma microRNAs (miRNAs) for the early detection of oral cancer using RNA-Seq data analysis.

Methodology:
Oral cancer is among the three main kinds of tumours found in the Indian subcontinent. Oral squamous cell carcinoma (OSCC) is often diagnosed at a late stage and may be malignantly transformed from oral leukoplakia (OL).
Students:
Akash Hirgond

Faculty Name:
Dr Utkarsh Raj

Objective:
To examine the inhibition proficiency of well-known kinase inhibitors as well as natural compounds from flavonoids library for the control of HPV16/18-E7 function, through molecular modelling, virtual screening and MD simulation studies.

Theory:
HPV16/18-E7 participates in the process of cell proliferation and metastasis of cancer, indicating its functional similarity with human cellular kinases.
Students:
Mousumi Saha, Navelli Gupta, Sushmita Nandy

Faculty Name:
Prof Ratna Sanyal

Objective:
To examine the inhibition proficiency of well-known kinase inhibitors as well as natural compounds from flavonoids library for the control of HPV16/18-E7 function, through molecular modelling, virtual screening and MD simulation studies.

Objective:
To select only important parts in a document to reduce the number of lines to summarise any document.
Students:
Pratyaksh Mathur Prerak Anand Om Ahire Suman Dey

Faculty Name:
Dr Chandan Medatwal and Prof Ratna Sanyal (Accepted and presented in ISDSI-Global 2021)

Objective:
To investigate the effectiveness of appraisal systems and its effect on employee morale.
Various modifications are presented on an extractive graph-based summarisation technique called TextRank to show how these modifications improve upon the original algorithm in different aspects. State-of-the-art text vectorisation and anaphora resolution techniques are used. The performance of modifications with the original algorithm are shown using ROUGE scores as a metric. Two sentence vectorisation approaches, using GloVe embedding and SBERT are explored in this research work. The quality of sentence vectors generated using these two models are evaluated. This has been done by assessing the quality of summaries produced using them against reference summaries from CNN’s news article dataset.
Students:
Akshat Jain, Dishank Kalra, Varun Bisht

Faculty Name:
Dr Ratna Sanyal (1st prize in Project Innovation Contest (PIC 2022))

Objective:
To monitor and study the class participation of students in online lectures.

Methodology:
Without face-to-face interaction, it has become harder to keep track of the overall progress of a class. Analysis of chats during online classes is vital and essential to the online method of learning, to gauge the level of effective participation of the students.
Students:
Ritav Das and Sristi Agrawal

Faculty Name:
Dr Ratna Sanyal

Objective:
To deploy an ensemble learning model to solve the fine-grained sentiment classification task.


Sentiment classification is an important process to analyse social conversations online and determine deeper context as they apply to a topic, brand or theme. Four classification algorithms were implemented for the purpose of this study. Implementing k-fold cross validation on each improved their accuracies by 40 per cent. The final ensemble model was created by calculating the correlation between each of the models and combining them carefully using results generated. Out of the four classification algorithms, Multinomial Naives Bayes and Support Vector Machine were found to produce the best results.
Students:
Kouthagouni Nikhil Reddy

Faculty Name:
Dr Sanjay K Biswas

Objective:
To deploy an ensemble learning model to solve the fine-grained sentiment classification task.
  • To establish pre-requisite understanding of the 5G network, its architectural builds, and components to get a proper know-how of the 5th generation of cellular network.
  • To set up basic groundwork leading to device-to-device communication-related research work that is a prominent feature of 5G.
  • To address the issue of suitable handover criteria under QoS aware D2D handover schemes which is a challenge with respect to mobility management in D2D communications.
Students:
Anushree Krishania, Rajat Kaushik, Pranay Kumar Shrivastava, Mohd. Hamza Ahsan

Faculty Name:
Surender Singh

Objective:
To examine the security vulnerabilities in Bluetooth technology used in IoT devices. This paper lines up the following objectives:
  • Describing the overview of Bluetooth Low Energy with a focus on its security in IoT devices.
  • Discussing major threat to Just Work Pairing Method
  • Proposing authentication method in Just Works and OOB as alternatives.
Students:
Tanuj Pandey, Anup Mishra, Tripti Lamba, Kanishya Mohan

Faculty Name:
Surender Singh

Objective:
To create a feasible detection system with low false positives to identify phishing attacks.
Students:
Vishnu Sharma, Siddhant Sharma, Sahil Singh Rawat, Ali Khan, Priyanshu Joshi, Richard Tony, Siddhi Lad, Yashas Grover

Faculty Name:
Prof Debashis Sengupta and Prof Nagendra Nyamgondalu

Objective:
To find an effective solution for mass vaccination using blockchain technology combined with IoT.
Students:
Mayuri Mane, Harsh Parmar, Hritik Dalal

Faculty Name:
Dr Thota Sivasankar

Objective:
To find an effective solution for mass vaccination using blockchain technology combined with IoT.

Methodology:
To build a machine-learning model to classify different crops using multi-temporal data from Sentinel-2 and different machine learning techniques.
Methodology: Using Random Forest algorithm for better accuracy.
Students:
Akshay Sharma,Aman Kumar Singh, Vyoman Jain

Faculty Name:
Dr Ayan Nandy

Objective:
To solve bin-packing problems in polynomial time by a non-deterministic Turing machine.
Students:
Sai Praneeth Diddigam

Faculty Name:
Manish Hurkat

Objective:
To make games lighter to store and run with low-level programming and easier usability.
Students:
Yash Agarwal, Varshith Muthya Vankamamidi, Vishal Shukla

Faculty Name:
Prof Kumar Nitesh

Objective:
To create an energy-efficient clustering algorithm using PSO.
Students:
Charitha Madala, Svayam K Gopal

Faculty Name:
Dr Vikas Upadhyaya

Objective:
Object detection has been an important issue in computer vision with applications involved with locations and movements of the target object. The rising use of digital cameras for applications like security purposes leads to the need for an automatic method that will yield efficient detection of objects. As computer vision and visual recognition is advancing, the industry has created a wide variety of computer vision products and services like video surveillance, medical image analysis, face detection and recognition and many more.
Students:
NC Mohit, Mudit Dixit, Yuvraj Singh

Faculty Name:
Dr Vikas Upadhyaya

Objective:
To analyse pre-existing GAIT recognition methods, determine a methodology to calculate accuracy of the GAIT recognition methods, suggest modifications and optimisations for better accuracy and computational efficiency, with respect to time and memory.

Methodology:
GAIT data acquisition, pre-processing, period extraction, feature extraction and classification.
Students:
Deena Nath Srivastava, Pranay Mokida

Faculty Name:
Dr Yogendra Pal

Objective:
To make the case for the effectiveness of YouTube in advancing student comprehension of learning concepts. The findings of this study are expected to contribute new knowledge to the existing body of education management, instruction and learning literature.
Students:
Abhinav Gupta, Srikeerthana Reddy, Yukta Sharma

Faculty Name:
Prof Eswaran Narasimhan

Objective:
To investigate effective procedures to minimise the instances of crew scheduling by looking ahead and cutting costs.
Students:
Yash Jain

Faculty Name:
Prof Sudip Sanyal

Objective:
To align the agent-based Model and Lotka-Volterra model to analyse ecological systems. The agent-based Model will perform realistic simulations while the Lotka-Volterra model will provide a mathematical analysis of the model. The models will work hand-in-hand to provide superior results.
Students:
Nitish Ranjan

Faculty Name:
Prof Sudip Sanyal

Objective:
To analyse the electoral process as the whole and determine the effect of different propaganda mechanisms (election campaigns) to influence the decision of the voters. The researchers aimed to design a model to predict the vote share of each political party in a particular state/constituency using real world data.
Students:
Pearl Miglani

Faculty Name:
Prof Sudip Sanyal

Objective:
To use the concept of random forest to train uncorrelated models by randomising the observations of the training set with replacement.
Students:
Md Zubair Hussain Emon, Samarth Gangwal, Sagar Makar and Manikanta Reddy

Faculty Name:
Jetendra Joshi and Dr Prashant Srivastava

Objective:

  • To study various methods/techniques of IOT systems and its implementation used in retail advertisement.
  • To provide a solution for virtual fitting room, with cloud integration and computer vision for image capturing.
  • To enhance user experience with the resultant display of virtually fitted clothes on the smartphone with an integrated payment option.
Students:
Gaurav Sengar, Harsh Vardhan, Muskaan Mahindrakar, Sarthak Khabiya

Faculty Name:
Meera S Datta

Objective:
To develop a QR-code based system to provide universities with an end-to-end solution from registration to campus tour and feedback to visitors, including back-end integration with university ERP system.

Methodology:
Examining existing solutions, providing a complete design for the QR-code based visitor self-navigation system and demonstrate a prototype that will cover at least six sites of interest on the campus.

Capstone projects

As the name signifies, capstone projects tie in all the learning from the university and employ it in the service of a project, which has at its core, a problem from the industry. Capstone projects offer students the opportunity to collate their learnings from multiple disciplines and bring to the fore their understanding of the problem. There are two capstone projects in successive semesters, which enable students to continue their research into a singular problem the following semester as well.

The projects are curated by industry faculty and presented to students in their barest form. Students are encouraged to follow up with industry representatives to acquaint themselves first hand with the problems as well as the requirements. They must meet other industry experts who can provide more inputs. Benchmarking is done by exposing possible solutions to the market to facilitate the production of a more elegant solution.
Students: Siddhant Sharma, Shresth Rana, Ayush Gupta

A Django-based web application that will act as a medium for interfacing with the Hand Gesture recognition system. The application will have the functionality of selecting the desired mode of translation i.e., Hand gesture to speech or hand gesture to text.

  • Recognition of hand gestures and translation of the respective gesture to text to facilitate communication between people with speech disorder.
  • Recognition and translation of hand gestures to speech aids communication with visually impaired people.
  • Use of Google Text to synthesise natural-sounding speech with 100+ voices, available in multiple languages and variants.
Students: Siddhant Sharma,Arpita Singh,Bhavya Narang, and Hritik Minhas

The purpose of this SRS is to outline both the functional and non-functional requirements of Pregnable Web. In addition, the document also provides a detailed profile of the external interfaces, performance parameters, and design constraints imposed on the implementation. It presents the requirements having qualities like correctness, unambiguity, completeness, consistency, verifiability, modifiability, and traceability.

The document can act as a foundation for efficient and well-managed project completion and further serve as an accurate reference in the future for further developments. This web application will help users to apply their concepts of various cybersecurity techniques and tools by providing a single interface, to practice all kinds of vulnerabilities (Top 10 OWASP Vulnerabilities). People can practice: File inclusion, File Upload, SQL injection, XSS, security mis-configuration attacks, etc., or use this website to test their tools.
Students: Aman Gupta, Sajja Srilikhith, Shanu Nirwan, Tanmay Chaturvedi Securitas is an online web application that encourages users to scan their websites for vulnerabilities, misconfigurations and other security issues. The prime objective of this application is to allow users to easily integrate security testing into their workflows, reduce increased costs of setting up a security testing environment, and managing the issues identified.

Using this platform, users can scan their websites for vulnerabilities, have a dashboard to track the status of the vulnerabilities and implement a fix. They can also automatically generate a scan report. The app maintains a database of previous scans whose findings can be referred to in the future.

Students: Parmar Harsh Yogeshbhai, Sristi Agrawal, Shanu Nirwan, Nidhi Khemka

The project deliverables are:

  • To identify the requirement of the Convolutional Neural Network method for handwritten recognition.
  • To develop a handwritten document recognition system using Convolutional Neural Network.
  • To evaluate the accuracy of the Convolutional Neural Network model for classifying handwritten text.

Students: Vankamamidi Muthya, Varshith, Yuvraj Singh, Sahil Singh, Tripti Lamba, Kanishya Mohan

Users seek a trusted medium through which their financial demands are fulfilled. Building a simple web application is not preferable because the user’s money can be stolen, transactions can be manipulated, balance can be altered, etc. This application uses Blockchain technology for transaction processing and settlement. The most important factor of this application is user safety.

Students: Ritav Das, Bora Srikeerthana Reddy, Riona Chakrabarti, Abhinav Gupta

Understanding hidden patterns beneath a trend is key to taking ecommerce growth in the right direction. This application — DataMetric is an app that specialises in ad-hoc analysis of ecommerce data that gets to the root of the problems and opportunities. It helps one see all their customer segments on a dashboard, choose any custom segments on any dashboard and get instant historical comparisons.

Students: N C Mohit, Sachit Pandey, Bhowmik Abhilash Ashim, Pratyaksh Mathur

The purpose of this project is to develop an application that allows users to get an accurate count of people present at a particular time at a single venue using computer vision-aided modules. The inputs can be in a number of formats which include static image files or dynamic inputs like webcam feed and video files. An upload option will be available for the same aforementioned inputs. The final application will be a user-friendly, easy-to-operate interface. This will help any and all end-users to use this application without any hassles.

Students: Yukta Sharma, Kawal Nain Singh Batra, Arjun Bakshi, Vishnu Sharma, Tanish Gupta

There has been extensive research in the field of self-driving cars. Over the past few years, many governments and companies have invested heavily in this niche product. We aim to implement an algorithm that detects the curvature of the road based on a fed input of a road journey (front view). Another algorithm will detect whether a motor (interpreted as a steering wheel) should turn left or right.

Students: Swattik Chakrabarty, Aniket Chakraborty, Shrey Bhardwaj, Sahasrabdi Bhattacherya, Ritu Sihag

This project deals with the major venue categories in the neighbourhoods of Kolkata and would specifically help businesses to start new restaurants, hotels, pizza places, etc. The project aims to make a clustering model to investigate and analyse Kolkata neighbourhoods and recommend suitable spots to launch desired business ventures. The target audience is business and restaurant owners.

Students: Kanchan Ninad Krishna, Nikhil Khandelwal, Ish Chaudhary

The application of data mining technology in real estate industry is a front field. Challenges include the establishment of data warehouse in the real estate industry, data mining efficiency especially with large-scale data, data mining methods appropriate for the real estate industry and so on. With more in-depth study on the application of data mining in the real estate industry, Real Estate Search system works on more useful information and knowledge will be mined out, which will be very helpful for government to institute industry policies as well as developers to make right decisions.

Students: Darsh Manish Gandhi, Kailash Karthik Sekhar, Muskan Goel, Anoop Gupta

The goal of this project is to create an application that allows users to predict the age and gender of a person using CNN algorithms. Real-time images of users are captured on the spot while filling a particular form and then the image is validated on the CNN model to predict the age and gender of the person. For the same aforementioned inputs, an upload option will be provided. The final program will have a simple, user-friendly interface. This will make it possible for any end-user to operate the application without trouble while being aware of their surroundings.

Students: Mohammed Faisal, Thadishetty Somanath, Vamshi, Tammana Karthik, Mayank Garg

The goal of image captioning is to automatically generate descriptions for a given image, i.e., to capture the relationship between the objects present in the image, generate natural language expressions and judge the quality of the generated descriptions. The purpose of this project is to automate the end-to-end task of getting meaningful and hidden information from the image uploaded by the user with a user-friendly interface. This project is based on the Convolutional Neural Networks and Long Short-Term Memory models of deep learning along with other functionalities. The deep learning model is trained with numerous images in order to get accurate information from the image.

Students: Akshat Bhandari, Arjun Seth, Divtej Singh Bindra, Mayank Gubba, Aman Mehra

The website — Cryptos, reports on the trading activities of thousands of markets but does not directly sell any crypto currency. The best way to find where to buy is by looking at the markets section for the crypto currency. Cryptos aims to do this by making price tracking simple and seamless. It is based on Blockchain technology.


The website will have the following key features –

  • Live chart for the visitors to get a snap about the live market prices.
  • A crypto currency exchange bot so that the user can compare the prices of different crypto currencies from different websites and decide from where he gets the best prices and can buy the crypto currency from that website.
  • Crypto currency Converter Calculator, through which users can convert the prices of crypto currency according to the values they put in the calculator.
  • Forecast the crypto currency prices using all the trading features.
  • Chatbot to tell the real-time best buying price for a crypto currency from a particular market. They shall also know about the best-selling price from a market which has the highest price at that point of time

Students: Nitish Ranjan, Aman Kumar Singh, Akshay Sharma, Vyoman Jain

The process of determining which class a traffic sign belongs to is known as traffic sign classification. Smarter cars could be constructed if traffic signs can be recognized automatically. Without a traffic signs recognition system, it would be very difficult for smarter cars to work efficiently and exist in the future. The goal is to automatically detect traffic signs along the road, such as speed limit signs, yield signs, merge signals, and so on.

Students: Ankit Gupta, Sahil Singh Rawat, Siddhant Sharma, Anjan Neema, Hritik Dalal

With this Blockchain solution, charities can publicly and irrevocably commit the receipt of the donation for public knowledge. Donors can rest easy knowing that their donation was received and is accounted. The application provides a secure, privacy-conscious, public ledger for charities to irrevocably commit a record of donations.

Students: Akshat Jain, Dishank Kalra, Avinash Yuvraj Patil

Stroke is the second leading cause of death and disability worldwide with 15 million new acute stroke cases every year and 285,00,000 disability-adjusted life-years. Most of the cases are of silent stroke where users don’t even realise its symptoms. The goal of this web application is to alert users to a possible future stroke. Around 80% of stroke cases can be prevented by a basic diagnosis. The stroke predictor will be able to save a substantial amount of the patient’s medical expenses as it will be able to predict the stroke early. Early diagnosis can also be a lifesaver.