Program Offers
The IDDD- CPS programme is offered by an interdisciplinary group involving faculty members from Electrical engineering, Chemical Engineering, Computer Science and Applied Mechanics.
Core group
- Sridharakumar Narasimhan (CH)
- Ramkrishna Pasumarthy (EE)
- V Kamakoti (CS)
- Babji S (AM)
- Nirav Bhatt (BT)
Curriculum
The IDDD curriculum is designed to cover the fundamentals concepts and tools of disciplines involved in studying CPS. Three core courses provide a background of control theory, mathematical and data sciences, and cyber security. Two labs are designed to provide computational and experimental background in the internet of things, smart infrastructure such as health care, transport and water networks. The students are then free to choose 4 electives from the elective list. These electives are a mix of advanced topics in control theory, data analysis, IoT, communications etc. The students can choose courses in their areas of interest.
4 core theory courses
Core 1- Basket: Control theory
(9 credits)
Core 2- Basket: Data science/Maths
(12 credits)
Core 3: Cyber security
(12 credits)
Core 4: Communication networks for IoT
(9 credits)
2 core lab
EE 4708, Data analytics
(6 credits)
CPS lab
(6 credits)
2 electives- Semesters 7,8,9
advanced control, sensors, actuators, mathematics, IoT, communications
Minimum 18 credits
Project (Summer, Semester 9 and 10)
(85 credits)
Total Credits
157 (minimum)
Interdisciplinary DD in Cyber Physical Systems -course curriculum
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Core 1 Basket: Control Theory |
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Sl.No |
Course No |
Course Name |
L |
T |
E |
P |
O |
C |
|
1 |
CH5120 |
Modern Control Theory |
3 |
0 |
0 |
0 |
6 |
9 |
|
2 |
EE5413 |
Linear Dynamical Systems |
3 |
0 |
0 |
0 |
6 |
9 |
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Core 2 Basket : Mathematics/Data Science |
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Sl.No |
Course No |
Course Name |
L |
T |
E |
P |
O |
C |
|
1 |
CH5019 |
Mathematical Foundations of Data Science |
4 |
0 |
0 |
0 |
8 |
12 |
|
2 |
EE5412 |
Mathematical methods in Systems Engineering |
4 |
0 |
0 |
0 |
8 |
12 |
Laboratory courses
- EE 4708 (Data analytics)
- CH5xxx CPS lab (new)
Project
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Sl.No |
Course No |
Course Name |
L |
T |
E |
P |
O |
C |
|
Summer |
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|
1 |
IDXXXX |
Project I |
0 |
0 |
0 |
0 |
20 |
20 |
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Total Credits |
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|
20 |
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Semester 9 |
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|
1 |
IDXXXX |
Project II |
0 |
0 |
0 |
0 |
30 |
30 |
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Total Credits |
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|
30 |
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Semester 10 |
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1 |
IDXXXX |
Project III |
0 |
0 |
0 |
0 |
35 |
35 |
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Total Credits |
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|
|
|
35 |
Electives
|
Course No |
Course Name |
|
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CH5230 |
Data-driven modelling of Process Systems |
9 |
|
CH5170 |
Process Optimization |
9 |
|
CH5020 |
Statistical design and analysis of experiments |
9 |
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CH5115 |
Parameter and state estimation |
10 |
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EE6432 |
Stochastic Control |
12 |
|
EE6433 |
Distributed Optimization for Control |
9 |
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EE6430 |
Fundamentals of Linear Optimization |
9 |
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EE6415 |
Nonlinear Control Systems |
9 |
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EE6412 |
Optimal Control |
9 |
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EE5156 |
Internet of Things and Management of discrete entities |
9 |
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EE5180 |
Introduction to Machine Learning |
12 |
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EE5141 |
Introduction to Wireless and Cellular Communication |
9 |
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CS6650 |
Smart Sensing for Internet of Things |
12 |
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CS6700 |
Reinforcement Learning |
12 |
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CS6330 |
Digital System Testing and Testable Design |
12 |
|
AM5140 |
Biomedical Instrumentation |
9 |