M.Tech Programme · EE2 · Electrical Engineering · IIT Bombay

Control & Computing

15 courses  ·  4 semesters  ·  166 total credits  ·  83 electives

Sem 1 Sem 2 Sem 3 Sem 4 Electives

Semester 1

Total: 34 credits
1

First Course in Optimization

EE659

6
2

Applied Linear Algebra

EE635

6
3

Multivariable Control Systems

EE640

6
4

Seminar

EE694

4
5

Communication Skills

EE899

6
6

Elective 1

—

6
Semester Total 34

Semester 2

Total: 72 credits
1

Nonlinear Dynamical Systems

EE613

6
2

Optimal Control Systems

EE622

6
3

Matrix Computations

EE636

6
4

Control and Computation Laboratory

EE615

6
5

Project Stage 1

EE797

42
6

Elective 2

—

6
Semester Total 72

Semester 3

Total: 6 credits
1

Elective 3 and/or Institute Elective

—

6
Semester Total 6

Semester 4

Total: 54 credits
1

Project Stage 2

EE798

48
2

Elective 3 and/or Institute Elective

—

6
Semester Total 54

Programme Total

166 Credits

15 courses

4 semesters

83 electives

Available Electives

Electives (80)

1

Statistical Signal Analysis (Prereq for EE608)

EE601

6
2

Digital Signal Processing & its Applications

EE603

6
3

Error Correcting Codes

EE605

6
4

Finite Fields and its Applications

EE649

6
5

Foundation of VLSI CAD

EE677

6
6

Behavioural Theory of Systems

EE714

6
7

Computational Electromagnetics

EE725

6
8

Decentralised control of complex system

EE749

6
9

Science of Information, Statistics & Learning

EE763

6
10

Applied Mathematical Analysis in Engineering

EE759

6
11

Introduction to Stochastic Optimization

EE736

6
12

Robust Control

EE 6111

6
13

Adaptive Signal Processing

EE608

6
14

Estimation and Identification

EE638

6
15

Markov Chains & Queuing System

EE621

6
16

Wavelets

EE678

6
17

An Introduction to Number Theory & Cryptography

EE720

6
18

Advanced Probability for random processes for engineers

EE734

6
19

Topics in Cryptology

EE793

6
20

Cryptocurrency and Blockchain Technologies

EE465

6
21

Space flight dynamics

AE713

6
22

Navigation of Autonomous Vehicles

AE688

6
23

Guidance of Aerospace Vehicles

AE686

6
24

Motion planning and coordination of autonomous vehicles

SC627

6
25

A First Course in Optimization

EE659

6
26

Information Theory and Coding

EE708

6
27

Introduction to Stochastic Control

EE737

6
28

Decentralized Control of Complex Systems

EE749

6
29

Advanced Network Analysis

EE760

6
30

Advanced Topics in Signal Processing

EE779

6
31

Large Sparse Matrix Computations

EE710

6
32

Advanced Computing for Electrical Engineers

EE717

6
33

Mathematical and Statistical Methods in Chemical Engineering

CL602

6
34

Process Modelling and Identification

CL625

6
35

State Estimation Theory and Applications

CL653

6
36

Computational Methods in Chemical Engineering

CL701

6
37

Information Theory and Coding

EE708

6
38

Games and Information

SC631

6
39

Optimization Techniques

IE601

6
40

Adaptive Control Theory

SC617

6
41

Advanced Network Analysis

EE760

6
42

Processor Design

EE739

6
43

Power System Dynamics and Control

EE658

6
44

Electrical Machine Analysis and Control

EE656

6
45

Advanced Process Optimization

CL647

6
46

Advanced Process Control

CL686

6
47

Embedded Control System

SC700

6
48

Introduction to Linear Filtering and Beyond

SC612

6
49

Embedded Systems Design

EE712

6
50

Introduction to Stochastic Control

EE737

6
51

Combinatorial Optimization

EE732

6
52

Combinatorics/CS604 Combinatorics

SI419

6
53

Decision Analysis and Game Theory

IE616

6
54

Integer Programming: Theory and Computations

IE716

6
55

Networks, Games and Algorithms

IE718

6
56

Convex Analysis

IE804

6
57

Machine learning theory

CS726

6
58

High Performance Scientific Computing

ME766

6
59

Topics In cryptology

EE793

6
60

Robotics

ME604

6
61

Intelligent Feedback and Control

SC645

6
62

Principles of Data and System Security

CS745

6
63

Guidance and control of unmanned autonomous vehicles

AE700

6
64

Motion planning and coordination of autonomous vehicles

SC627

6
65

Embedded Systems Design

EE712

6
66

Embedded systems

CS684

6
67

Embedded Control System

SC700

6
68

Foundations of Machine Learning

CS725

6
69

Introduction to Machine Learning

EE769

6
70

Probabilistic foundations of AI (previously CS726)

CS791

6
71

Advanced topics in machine learning

EE782

6
72

Foundations of Intelligent and Learning Agents

CS747

6
73

Introduction to Stochastic Optimization

EE736

6
74

Markov Decision Processes

IE708

6
75

Decision Analysis and Game Theory

IE616

6
76

Games and Information

SC631

6
77

Networks Games and Algorithms

IE718

6
78

Game Theory and Algorithmic Mechanism Design

CS6001

6
79

Combinatorics

SI419

6
80

Combinatorics

CS604

6

Non-EE Electives (3)

1

Estimation and Identification

EE638

6
2

Introduction to Linear Filtering and Beyond

SC612

6
3

State Estimation Theory and Applications

CL653

6

Notes

→ The thesis must lead to work of reputably publishable, patentable, or deployable quality.

→ Any course above 5xx level offered at IITB can be considered as an elective with faculty advisor approval.

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