- Provide rigorous mathematical background with practical use-cases in machine learning in order to apply classroom concepts to real-world machine learning applications.
- Provide enhanced programming skills to attract relevant (Machine learning based) industry partners for placements.
- Emphasize on collaborations/internships with industry partners and academic laboratories in India and abroad, and Indian NGO/Government agencies.
- To Equip our students with theoretical and practical tools essential for the new-age signal processing and machine learning applications.
- Leverage on the mathematical strengths of an incoming M.Tech. and focus on providing fundamentals pertaining to Machine Learning and advanced signal processing.
- Develop strong programming skills essential for real - world problems.
For "M.Tech. in ECE with specialization in ML" the student must:
- Complete the following core courses of the specialization area.
- Machine Learning OR Statistical Machine Learning
- Probability and Random Processes
- Applied Optimization Methods for Machine Learning
- If opted for Thesis/Scholarly paper, it should be in the specialization domain. The advisor will certify this fact.
- At least 4 credits should be from specialization electives in addition to the core courses, if opted for “M.Tech. with Thesis option” .
- At least 12 credits should be from specialization electives in addition to the core courses, if opted for “M.Tech. with scholarly paper (8 credit) option” .
- At least 16 credits should be from specialization electives in addition to the core courses, if opted for “M.Tech. with scholarly paper (4 credit) option” .
- At least 20 credits should be from specialization electives in addition to the core courses, if opted for “M.Tech. without thesis and scholarly paper option” .
|Core||Specialization Elective||Thesis/SP||Other Courses||Total|
|M.Tech. with thesis||12||4||16||16||48|
|M.Tech. with Scholarly Paper (8 cr.)||12||12||8||16||48|
|M.Tech. with Scholarly Paper (4 cr.)||12||16||4||16||48|
|M.Tech. without thesis and scholarly paper option||12||20||0||16||48|
- Computer Vision
- Semi-supervised learning
- Deep Learning
- Medical imaging
- Image processing
- Computational biology
- IoT and distributed ML
- Radar System
- Interpretable AI
The following faculty members are offering courses and guiding thesis and scholarly papers in the area of Machine Learning.
- Dr. Angshul Majumdar
- Dr. Anubha Gupta
- Dr. A V Subramanyam
- Dr. Pravesh Biyani
- Dr. Ranjitha Prasad
- Dr. Saket Anand
- Dr. Shoba Sundar Ram
- Dr. Tammam Tillo
While internship is not a requirement for the M.Tech. degree, students are encouraged to do an internship to gain industry experience. To facilitate internships, the institute has made arrangements with some corporations to host interns from this program. Guidelines are given here
Last updated: 06-08-2021