Final Year Major Project Initiation for 7th Semester Students
The Final Year Students currently in 7th Semester are to initiate their final year major project. While the final year project is a core essential part of your BTech degree, it is also highly valued for future career, since it supports students engaging in realistic activities which reinforce their understanding of the discipline, and draws on skills acquired in different modules throughout their degree.
- Choose a topic which where you will apply knowledge and skills you have gained from the courses taught and the skills you have gained through internships, self-study etc. Students are expected to apply good practice they have already learned during previous semesters, as well as learning any new technologies and other material which may be necessary to progress their work.
- Try to choose a topic which will be a great value addition to your career.
- Each student will work under a supervisor, who would normally be from the Computer Science Department, but supervisors from other departments or premier institutes/Industry are acceptable on case-to-case basis (see point no 7). Broad areas in which Department Supervisors will offer guidance is enlisted in the following table.
- Talk with your supervisor to choose topics that solve real world problems, society problems, technical problems and topics that aims to handle current and future industry trends
- A Final year project has to have a major implementation part, either in code or hardware or both. It cannot be a completely theoretical topic.
- There are four “deliverables” — an initial formal title and abstract of their project (by 20th October, 2020), a complete Design Document after End-Term Exams of 7th semester, a progress report/presentation at around Feb 2021, and a final demonstration with complete report submission at the end of 8th
- The Department also encourages Inter-disciplinary, Inter-University, Industry-collaborative projects.
For Inter-Disciplinary Projects (for example Biotechnology-Computer Science, Electronics-Computer Science etc.) you can have two or more supervisors from all the concerned Departments
For Inter-University projects you can have supervisors from GEHU or from Premiere Institutes (IITs , NITs and IIITs only). A co-supervisor from the Department can be taken.
For Industry Collaborative Projects you can have supervisors from Prominent Industries (Major organizations only like IBM, Oracle, Amazon etc). A co-supervisor from the Department can be taken.
For Inter-Disciplinary, Inter-University and Industry-Collaborative projects you need to take prior permission. Send a mail to : indialorATgmail.com - Projects can be done individually or in groups. Maximum four students is allowed in a group.
- Please fill up the initial details and abstract in the given link by 20th Oct, 2020. For group projects please ensure that only one of you is submitting, DONOT submit multiple entries. Link: https://forms.gle/bRTzUieppMDryGkd9
Sl No | Faculty | Areas for Supervision / Projects |
1 | Akanksha Kapurwan | Programming Languages, Web Technologies |
2 | Akansha Gupta | Machine learning, Artificial Intelligence, Soft Computing |
3 | Akshay Rajput | Machine learning, social media data mining, NLP, Artificial Intelligence |
4 | Ankit Tomar | Social distancing alert based system in deep learning using crowd density estimation./ Deep Learning,
Crowd emotions recognition using advanced deep learning algorithms./ Deep Learning, People anomaly detection using advanced deep learning algorithms./ Deep Learning |
5 | Ankur Choudhary | Broad Area : Routing protocols for Wireless Sensor Networks
Sample Project Topics: Expected – basic understanding of Wireless Sensor Networks. Task- Work out a well established hierarchical routing protocol, preferably using MATLAB (not restricted), further the student is expected to extend this worked out implementation.
Expected – basic understanding of Wireless Sensor Networks. Task- Work out any two well established classical flat routing protocols, preferably using MATLAB (not restricted), further the student is expected to carry out a relative study between the worked out implementations. |
6 | Ashish Garg | Machine Learning, Data Analytics, Machine Learning |
7 | Ashwini Kumar | Natural Language Processing, Speech Recognition, Deep Learning |
8 | Deepak Uniyal | Natural Language Processing, Twitter Data Analysis, Information Retrieval |
9 | Devyani Rawat | Programming Languages, Data Analytics |
10 | Dibyahash Bordoloi | Superscalar Processor Architectures, Speculation in Processors, Virtual Scene Generation |
11 | Dr. Bhaskar Pant | Machine Learning, Artificial Intelligence, Bioinformatics, Data Mining |
12 | Dr. Devesh Pratap Singh | Wireless Sensor Networks, System Programming |
13 | Dr. Durgaprasad Gangodkar | Computer Vision, Cloud Computing, Multicore Computing, Big Data Storage |
14 | Dr. Manoj Diwakar | Medical Image denoising, Image Enhancement using fusion approach, Image Security using encryption/watermarking |
15 | Dr. Mohammad Wazid | ML security, Blockchain based security protocols, Security and privacy protocols in healthcare informatics |
16 | Dr. Preeti Mishra | Cloud Security, Android Security, Docker Security, IoT Security |
17 | Dr. Sachin Sharma | IoT, Cloud Computing, VANET |
18 | Dr. Santosh Kumar | Ubiquitous Computing, Software Engineering |
19 | Dr. Sharad Gupta | Image Processing, Machine Learning |
20 | Dr. Sourabh Jain | IOT based Manhole Detection and Monitoring System,
IOT Based Automatic Vehicle Accident Detection and Rescue System, IOT Based Toll Booth Manager System |
21 | Dr. Vijay Singh | IoT, Recommender Systems, Data Analytics, Cloud Computing, Web Technologies |
22 | Dr. Vikas Tripathi | Computer Vision , Machine learning, Image Processing |
23 | Garima Sharma | Data Mining, Machine Learning, Data Analysis |
24 | Hemant Singh Pokhariya | Land cover classification of remote sensing data,
Optimized machine learning scheme of land cover Classes, LANDSAT data, Effect of Urbanisation on other land cover classes |
25 | Himanshu Rai Goyal | Wireless Sensor Networks, IoT |
26 | Kireet Joshi | Data Mining, Machine Learning, Software Engineering |
27 | Manish Mahajan | Anomaly Analysis, Cryptography |
28 | Manish Sharma | Web Technologies, Artificial Intelligence, Mobile Applications |
29 | Neha Tripathi | Software Engineering |
30 | Nisha Chaube | Programming Languages |
31 | Noor Mohd | Intrusion Detection System,Mobile Adhoc Networks, Wireless Sensor Networks,Self Configurable Networks |
32 | Palak Agarwal | Web Technologies, Programming Languages |
33 | Pankaj Kumar | Systems Programming, Programming Languages |
34 | Parul Madan | Databases, Web Technology, Wireless Sensor Networks |
35 | Piyush agarwal | IoT, Big Data Analytics |
36 | Prabhjot Singh | Crowd counting using deep learning , Deep learning, Computer Vision , Natural Language Processing |
37 | Priyank Pandey | Databases, Web Technologies, Machine Learning, Natural Language Processing |
38 | Ramesh Singh Rawat | IoT, Multimedia |
39 | Ruchira Rawat | Programming Languages, Algorithms |
40 | Sanjeev Kukreti | Web Technologies |
41 | Sarishma | Blockchain, Cloud security, Docker |
42 | Saurabh Kumar Mishra | Algorithms, Data Mining , Sentiment Analysis |
43 | Siddharth Gupta | Machine Learning, Deep Learning, Mobile Communications(4G Volte) |
44 | Sumit Pundir | Computer Networks |
45 | Swati Devliyal | IOT,ITS,ML |
46 | Upendra Ashwal | Data Structures |
47 | Vikas Tomer | Data Science, Machine Learning |
48 | Vishan Kumar Gupta | Data Science, Artificial Intelligence |
49 | Vishu Tyagi | Opinion Mining, Information Retrieval, Recommender System |