Teaching | SAJID Lab

EEE 6516 (October 2026)

Thu, 01 Oct 2026 00:00:00 +0000

First class will be held online

The first class of EEE 6516 (Week 1, Lecture 0: an introduction to quantum computing and the course) will be held online on Zoom.

Zoom link:

Course announcements: For the latest announcements, materials and submissions, please use the class Team in your Microsoft Teams account. If you have not been added to the class Team, please e-mail the course instructor.

In 2025 the Nobel Prize in Physics was awarded for showing that an electrical circuit (a superconducting chip with a Josephson junction) can behave as a single quantum object, with quantised energy levels and quantum tunnelling. Circuits of this kind are the ancestors of today’s superconducting qubits. Quantum computing is therefore not only a subject for physicists. Its hardest problems are electrical-engineering problems: microwave control and readout, cryogenic electronics, photonics, signal processing, coding theory and the security of communication systems.

This course builds quantum computing from what an EEE graduate already knows: linear algebra, phasors, signals, probability and digital logic. No background in quantum mechanics is assumed. Every idea is also tested in simulation, using free, open-source software that runs on your own laptop.

Course Information


Course	EEE 6516 – Quantum Computing (postgraduate)
Instructor	Dr. Sajid Muhaimin Choudhury, Professor, Department of EEE, BUET (SAJID Lab)
Office	EEE 222, ECE Building, BUET
E-mail
Classes	Tuesdays, two lectures of 75 minutes. Week 1 has one introductory class (online, see above); Week 7 has no lectures (midterm-assignment week); Week 13 is for final-project presentations
Communication	Microsoft Teams (materials, announcements, submissions, messages)

Syllabus

Course Content

Introduction to quantum computing; Postulates of quantum mechanics; Qubits and single-qubit gates; Operators and quantum measurement; Quantum information processing, superposition, entanglement, no cloning theorem, and quantum teleportation; Quantum circuits, controlled operation and measurement, universal quantum gates; Quantum algorithms: Deutsch-Jozsa algorithm, Grover’s algorithm, Shor’s algorithm, quantum Fourier transform and phase estimation; Density matrices and Bloch sphere representation of quantum variables; Quantum error correction and fault-tolerant architecture; Physical realization of quantum computers: harmonic oscillator, optical quantum computers, trapped ions, superconducting qubits, and new implementation schemes.

Prerequisites

Python, linear algebra and probability at the level of a BSc in EEE.
No quantum mechanics is assumed. Chapter 1 builds the mathematical toolkit (complex vectors, Dirac notation, operators and eigenvalues).

Course Outcomes (CO)

After completing this course, students will be able to:

CO No.	CO Statement	Domain and Taxonomy Level	Delivery Method(s)	Assessment Tool(s)
CO1	Apply the postulates of quantum mechanics and the linear algebra of qubits to compute states, gate actions, measurement probabilities and expectation values of single- and multi-qubit systems, including entangled and mixed states	C3: Cognitive / Apply	Lectures, handouts, worked examples, in-class activities	Class tests, term final
CO2	Analyse quantum algorithms (Deutsch–Jozsa, Bernstein–Vazirani, Grover, QFT, phase estimation, Shor), error-correcting codes and physical qubit platforms, and evaluate their resource costs and limitations against classical baselines and noise	C4: Cognitive / Analyse; C5: Cognitive / Evaluate	Lectures, handouts, simulations	Class tests, term final, midterm assignment
CO3	Implement, simulate and verify multi-qubit circuits and quantum dynamics with open-source simulators, including noise, interpret the results statistically, and communicate a reproducible simulation study	P4: Psychomotor / Mechanism; C6: Cognitive / Create (report)	Simulation exercises, live demonstrations, project supervision	Midterm assignment, final project (report, code, presentation)

Weekly Plan

Classes are on Tuesdays. Class tests are held outside lecture time.

Week	Lectures	Topics
1	0	Introduction to quantum computing and to the course (online)
2	1–2	Chapter 1: why quantum computing; complex vectors, Dirac notation, operators, eigenvalues
3	3–4	Chapter 2: states and measurement; single-qubit gates, Bloch sphere
4	5–6	Chapter 2: dynamics, observables, shot noise · Chapter 3: composite systems, two-qubit gates
5	7–8	Chapter 3: circuit model, universality; Qiskit, Cirq, PennyLane · Chapter 4: entanglement
6	9–10	Chapter 4: teleportation, superdense coding, CHSH · Chapter 5: oracles, Deutsch–Jozsa
7	—	No lectures: midterm-assignment week
8	11–12	Chapter 5: Grover search · Chapter 6: quantum Fourier transform
9	13–14	Chapter 6: phase estimation; order finding and Shor’s algorithm
10	15–16	Chapter 7: density matrices; quantum channels and noise
11	17–18	Chapter 8: error correction; stabilisers, surface code, fault tolerance
12	19–20	Chapter 9: superconducting qubits; trapped ions, photons, neutral atoms
13	—	Final-project presentations

Assessment

Grading Policy

Component	Weight	Notes
Class tests	15%	Three tests, 5% each, held outside lecture time
Midterm assignment	25%	Individual simulation study with a personal parameter set
Final project	30%	Groups of 2–3: reproduce and extend a published result by simulation; report, code and a 12-minute presentation
Term final	30%	As per the published routine

Assessment Milestones

Week	Milestone
5	CT1 (Chapters 1–2)
6	Midterm assignment released
7	Midterm assignment due (end of the week)
8	Final-project groups and paper proposal due
9	CT2 (Chapters 3–5)
11	CT3 (Chapters 6–7); final-project progress check
12	Final-project report and code due
13	Final-project presentations (12 minutes + Q&A)

Midterm Assignment and Final Project

Both are simulation projects.

Midterm assignment (individual). You implement a circuit or protocol from Chapters 2–5, predict its behaviour analytically, simulate it, and study one non-ideal effect such as noise. Each student receives a personal set of parameters.
Final project (groups of 2–3). Your group chooses a peer-reviewed paper whose central circuit or simulation fits on a laptop, either from the curated list or with the instructor’s approval at the proposal stage. You then:
1. reproduce one key figure or table;
2. extend it in one direction, for example noise level, problem size, a different simulator or error mitigation;
3. verify the results with analytic checks, fixed random seeds and stated tolerances.
Your code must regenerate every figure from a single command. Report templates (LaTeX, Overleaf-compatible) are provided on Teams.

Late Submission

Up to 2 days late: 10% penalty.
More than 2 days late: 25% penalty.

Policies

Incomplete Grade Policy

An I grade is given only if you have completed the midterm assignment and the final project (report and presentation), and miss the term final for reasons beyond your control. Apply to the Head of the Department of EEE within one week of the start of the final examinations. If you missed the assignment or the final project, you cannot receive an I grade, and you will be graded according to the grading policy. If you are unsure whether you can continue, please withdraw from the course.

Make-up Class Test Policy

A make-up class test is given only to students who missed a class test for circumstances beyond their control. It must be taken before the end of classes of the semester.

Academic Integrity and Generative AI

Plagiarism in a report or in code results in zero for that assessment. Reused code must be cited, including the paper’s own code if it is published. Copying another student’s or group’s code or results is plagiarism.
Generative AI: limited use. The analytic predictions, the design of your verification tests and the interpretation of your results must be your own work. Help with coding, debugging or language is allowed, but you must declare it in your report.
You must be able to explain every line of your code and every number in your report in the Q&A. Marks for a part can be withheld if you cannot explain it.

Textbooks and Resources

Course Materials

Chapter handouts and lecture slides for EEE 6516 (primary; on Teams).

Textbook

M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information, 10th anniversary edition, Cambridge University Press, 2010.

Software

All simulations run locally on your own laptop. No cloud account, token or paid service is needed.

Software	Version used in the course	Use
	—	First step: states and gates as arrays
+	2.5.2 / 0.17.2	Circuits, algorithms, noise models
	5.3.1	Density matrices, dynamics, hardware models
	1.7.0	Alternative circuit simulator (from Lecture 7)
	0.45.1	Alternative circuit simulator (from Lecture 7)
	1.16.0	Error-correction (stabiliser) simulation

Please install the course environment before Lecture 1, following Section 1.10 of the Chapter 1 handout.

Why Should an EEE Graduate Student Take This Course?

It is electrical engineering. A superconducting quantum computer is a microwave transmitter and receiver around a chip cooled to about 10–20 mK. Trapped-ion and neutral-atom machines are built from lasers, optics and detectors. Error correction combines coding theory with real-time decoding, and Shor’s algorithm has driven the move to new post-quantum cryptography standards (NIST FIPS 203, 204 and 205, published in August 2024).
EE and ECE departments teach it. For example:
- MIT 6.6410J Quantum Computation;
- Cornell ECE 5330 Quantum Physics and Engineering;
- Stony Brook ESE 512 Introduction to Quantum Systems Engineering;
- Purdue’s ECE Quantum Computing series.
It builds on the skills you have and adds new ones. You bring linear algebra, phasors, probability, digital logic, electromagnetics and Python. The course adds qubit calculations, the analysis of algorithms and hardware against classical baselines, and reproducible simulation. These open thesis directions in quantum devices, cryogenic microwave electronics, photonics, control and post-quantum security.

Course content follows the approved BUET syllabus for EEE 6516. Week-by-week topics may be adjusted during the term; announcements on Teams take precedence over this page.

EEE 415 (Jan 2026)

Thu, 01 Jan 2026 00:00:00 +0000

Announcement

We will use Microsoft Teams for disbursing class materials for the course. Please contact your respective course instructor if you have not been added to the class team “EEE 415 C (July 2023)”.

Introduction

The syllabus of this course has been changed and the course has been completely redesigned from grounds up.

Syllabus (as approved in 2022)

Fundamentals of microprocessor and computer design, processor data path, architecture, microarchitecture, complexity, metrics, and benchmark; Instruction Set Architecture, introduction to CISC and RISC, Instruction-Level Parallelism, pipelining, pipelining hazards and data dependency, branch prediction, exceptions and limits, super-pipelined vs superscalar processing; Memory hierarchy and management, Direct Memory Access, Translation Lookaside Buffer; cache, cache policies, multi-level cache, cache performance; Multicore computing, message passing, shared memory, cache-coherence protocol, memory consistency, paging, Vector Processor, Graphics Processing Unit, IP Blocks, Single Instruction Multiple Data and SoC with microprocessors. Simple Arm/RISC-V based processor design with VerilogHDL

Introduction to embedded systems design, software concurrency and Realtime Operating Systems, Arm Cortex M / RISC-V microcontroller architecture, registers and I/O, memory map and instruction sets, endianness and image, Assembly language programming of Arm Cortex M / RISC-V based embedded microprocessors (jump, call-return, stack, push and pop, shift, rotate, logic instructions, port operations, serial communication and interfacing), system clock, exceptions and interrupt handling, timing analysis of interrupts, general purpose digital interfacing, analog interfacing, timers: PWM, real-time clock, serial communication, SPI, I2C, UART protocols, Embedded Systems for Internet of Things (IoT)

Grading Policy

Class Attendance (10%) – Class participation and attendance will be recorded in every class. 30 Marks as per university AC policy
Continuous Assessment (20%) – 1 assignment (20) – Mandatory 3 Class tests, best 2 counted (40)
Final Examination (70%)– A comprehensive term final examination will be held at the end of the Term following the guideline of the Academic Council

Weekly Schedule

As per the routine published in the Department of EEE website.

Textbooks

[Harris] Sarah Harris, David Harris – “Digital Design and Computer Architecture, ARM Edition, Morgan Kaufmann (2015) - Chapter 6,7,8

[Patterson] David A. Patterson and John L. Hennessy, “Computer Organization and Design – The Hardware / Software Interface ARM edition” Morgan Kaufmann - Chapter 1

[Zhu] Yifeng Zhu “Embedded Systems with ARM Cortex-M Microcontrollers with Assembly Language and C”

Semester Plan

Week	Lectures	Topic	Textbook
1	1-3	Fundamentals of microprocessor and computer design, processor data path, architecture, microarchitecture, introduction to CISC and RISC, complexity, metrics, and benchmark.	Patterson 1
2	4-6	Assembly Language.	Harris 6.1-6.3
3	7-9	Assembly Language Programming.	Harris 6.3
4	10-12	Machine Language, Compiling, Assembling.	Harris 6.4
5	13-15	Performance Analysis, Single Cycle and Multicycle Processor.	Harris 7.1-7.4
6	16-18	Pipelining, Hazards, Advanced Microarchitecture.	Harris 7.5,7.7
7	19-21	Memory Systems – Cache and Virtual Memory.	Harris 8.2-8.4
8	20-24	Introducing Embedded System Design, IoT, Arm Cortex m4.	Lecture Slides
9	25-27	General Purpose Input Output.	Zhu 14
10	28-30	General Purpose Timers.	Zhu 15.1-15.3
11	31-33	Interrupts.	Zhu 11, 15.4
12	34-36	ADC + DAC.	Zhu 20,21
13	37-39	Serial Communication.	Zhu 22

EEE 416 (Jan 2026)

Thu, 01 Jan 2026 00:00:00 +0000

Announcement

We will use Microsoft Teams for disbursing class materials for the course. Please contact your respective course instructor if you have not been added to the class team.

2023Introduction

In the 2023 syllabus the 416 course will be heavily project focused. We will use the project of EEE 416 as a primary replacement of the Capstone Project, for culmination of program outcomes.

Syllabus

EEE 416

The sessional courses will be conducted in two parts. In the first part of the sessional course, the students will perform experiments in relevance with the EEE 415 course. In the second part of the course, the students will perform design projects to achieve specific program outcomes.

EEE 415

Course Objectives

To perform experiments in relevance with the theoretical concepts of the course EEE 415: Microprocessor and Embedded Systems
To conduct design projects in order achieve specific program outcomes described in the Course Outline

Course Outcomes

Upon successful completion of the course, students will be able to

CO No.	CO Statement	Corresponding PO(s)*	Domains and Taxonomy level(s)**	Delivery Method(s) and Activity(-ies)	Assessment Tool(s)
CO1	Utilize VerilogHDL, ARM assembly, C programming and microcontrollers boards for implementing and analyzing theoretical concepts at software and hardware levels	PO(e)	P4, C4	–	Lab Performance, Lab Test, Quiz, Viva, Project
CO2	Design an embedded system with appropriate considerations to safety, cultural, societal, and environmental considerations	PO(c)	C6	–	Project Report and Hardware demonstration
CO3	Assess impact of embedded systems project design on Societal, Health, Safety, Legal and Cultural Issues	PO(f)	C5	–	Presentation and Report
CO4	Evaluate Sustainability the and Impact of the Designed embedded systems Project in the Societal and Environmental Contexts	PO(g)	C5	–	Presentation and Report
CO5	Demonstrate membership and leadership in designing embedded system related problem solving	PO(i)	P7	–	Project logbook , Peer assessment, Viva, Presentation
CO6	Communicate effectively on embedded system related design with presentation and detailed report	PO(j)	A2	–	Video Presentation, Design Report
CO7	Demonstrate project management and cost analysis for embedded system project	PO(k)	A3	–	Project Report and Presentation

_ * Cognitive Domain Taxonomy Levels: C1 – Knowledge, C2 – Comprehension, C3 – Application, C4 – Analysis, C5 – Synthesis, C6 – Evaluation, Affective Domain Taxonomy Levels: A1: Receive; A2: Respond; A3: Value (demonstrate); A4: Organize; A5: Characterize; Psychomotor Domain Taxonomy Levels: P1: Perception; P2: Set; P3: Guided Response; P4: Mechanism; P5: Complex Overt Response; P6: Adaptation; P7: Organization Program Outcomes (PO): PO(a) Engineering Knowledge, PO(b) Problem Analysis, PO(c) Design/development Solution, PO(d) Investigation, PO(e) Modern tool usage, PO(f) The Engineer and Society, PO(g) Environment and sustainability, PO(h) Ethics, PO(i) Individual work and team work, PO(j). Communication, PO(k) Project management and finance, PO(l) Life-long Learning

For details of program outcome (PO) statements, please see the departmental website or course curriculum _

KPA Mapping

Weekly Plan

Week	Mode	Topic
1	Experiment 00	Introduction to Lab, Lab Policies and Tools
2	Experiment 01	Arm Cortex M: GPIO: Interfacing LED, Push-Button and Stepper Motor	CO1 (PO(e))
3	Experiment 02	Arm Cortex M: Interrupt and Timers I	CO1 (PO(e))
4	Experiment 03	Arm Cortex M: Interrupt and Timers II	CO1 (PO(e))
5	Presentation	· Project Proposal Presentation · Describe specific technical requirements to be attained during the project · Describe sustainability and impact of the work in societal and environmental contexts	CO4 (PO(g))
6	Experiment 04	Arm Cortex M: Analog Interfacing	CO1 (PO(e))
7	Experiment 05	Arm Assembly Language and Architecture	CO1 (PO(e))
8	Experiment 06	Arm Micro Architecture: Single Cycle, Multi Cycle and Pipelining	CO1 (PO(e))
9	Project Progress Demonstration/ Presentation	· Project Progress Demonstration/ Presentation-1 · Present/demonstrate the technical progress of the project · Describe contextual knowledge to assess societal, health, safety, legal and cultural issues relevant to the project	CO2 (PO(c)) CO4 (PO(f))
10	Assessment	Lab Test	CO1 (PO(e))
12	Lab Quiz and Viva	Sessional Quiz	CO1 (PO(e)) CO2 (PO(c))
11	Project Demonstration/ Presentation	· Project Progress Demonstration/ Presentation-2 · Present/demonstrate the technical progress of the project · Describe multidisciplinary aspects of the project · Describe how each team member has been effectively working (individually and as a member or leader) to attain the goals (Self- and peer-assessment of students)	CO5 (PO(c) CO7 (PO(i))
13	Final Presentation	· Describe how engineering management principles and economic decision-making applied to the project · Use multimedia and necessary documentation (user manual, video demonstration and project report) to clearly communicate the project	CO7 (PO(k)) CO6 (PO(j))
14	Project Demonstration	· Practical demonstration of the project: show evidence that specific technical requirements have been attained by the project	CO2 (PO(c))

Distribution of Marks

Class Participation and Attendance 10%
Lab Reports 5%
Lab Experiments 10%
Lab Test 15%
Sessional Quiz 15%
Final Project 45%
Total 100%

Lab Usage Policy

No Food or Drink is allowed in the laboratory.
At the beginning of each lab, please check out the “Embedded Systems Kit” box from Mr. Selim, writing your name and information in logbook. Please check individually if each component is in the box.
Report any missing parts at the beginning of the lab.
You will be financially responsible for unreported missing items
Do not separate / tear the jumper cable collection.
Before connecting the USB port, double check the power and ground connection of your externally connected components.

EEE 400

Tue, 01 Apr 2025 00:00:00 +0000

EEE 400 - Thesis

Course announcements: For latest announcements and updates, please refer to the Team UG QPACERS (DSMC Research Group) in your Microsoft Teams account. Please contact me if you have not been added to the Team.

Course Content (As approved by the Academic Council)

The students will perform experimental and/or theoretical investigation of a research topic related to electrical and electronic engineering discipline Students will attend seminars, review research literature and related contemporary aspects of the topic, identify problem, formulate a proposal to solve a specific problem related to the topic, interpret data, and analyze the problem using first principles of mathematical, natural or engineering sciences. Students will conduct investigations of the problem using research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of information to provide valid conclusions. Students will understand and adhere to professional ethics and ethical principles of research. The students will be required to present a progress report at the end of the first semester, and present and submit a thesis at the end of the work.

Course Objectives

To perform experimental and/or theoretical investigation of a research topic
To review research literature and related contemporary aspects of the topic,
To identify, formulate a proposal to solve a specific problem related to the topic, interpret data, and analyze the problem using first principles of mathematical, natural or engineering sciences
To conduct investigations of the problem using research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of information to provide valid conclusions
To attend seminars and communicate effectively with oral presentation and detailed thesis report
To understand and adhere to professional ethics and ethical principles of research

Knowledge required

Fundamental understanding of concepts of Electrical and Electronic Engineering, Different concepts, tools and software specific to the research problem

Course Outcomes

After completing this course, students will be able to

CO No.	CO Statement	Corresponding PO(s)*	Domains and Taxonomy level(s)**	Delivery Method(s) and Activity(-ies)	Assessment Tool(s)
CO1	Identify, formulate, research literature, interpret data, and analyze problems using principles of mathematical, natural and engineering sciences	PO(b)		--	Thesis Book Thesis Presentation
CO2	Investigate of problems using research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of information to provide valid conclusions.	PO(d)			Thesis Book Thesis Presentation
CO3	Apply knowledge of mathematics, science, and engineering to solve research problems	PO(a)			Thesis Book Thesis Presentation
CO4	Demonstrate adherence to professional ethics and ethical principles of research	PO(h)	C5	--	Thesis Book
CO5	Communicate effectively with oral presentation and detailed thesis report	PO(j)	A2	--	Thesis Book Thesis Presentation
CO6	Research contemporary aspects related to the problem and topic through detailed literature review and understand	PO(l)	P6	-	Thesis Book Thesis Presentation

*Cognitive Domain Taxonomy Levels: C1 – Knowledge, C2 – Comprehension, C3 – Application, C4 – Analysis, C5 – Synthesis, C6 – Evaluation, Affective Domain Taxonomy Levels: A1: Receive; A2: Respond; A3: Value (demonstrate); A4: Organize; A5: Characterize; Psychomotor Domain Taxonomy Levels: P1: Perception; P2: Set; P3: Guided Response; P4: Mechanism; P5: Complex Overt Response; P6: Adaptation; P7: Organization

Program Outcomes (PO): PO(a) Engineering Knowledge, PO(b) Problem Analysis, PO(c) Design/development Solution, PO(d) Investigation,
PO(e) Modern tool usage, PO(f) The Engineer and Society, PO(g) Environment and sustainability, PO(h) Ethics, PO(i) Individual work and team work,
PO(j). Communication, PO(k) Project management and finance, PO**(l)** Life-long Learning

* For details of program outcome (PO) statements, please see the departmental website or course curriculum

Mapping of Knowledge Profile, Complex Engineering Problem Solving and Complex Engineering Activities

K1	K2	K3	K4	K5	K6	K7	K8	P1	P2	P3	P4	P5	P6	P7	A1	A2	A3	A4	A5
🗸	🗸	🗸	🗸				🗸	🗸	🗸	🗸				🗸	🗸	🗸	🗸		🗸

Lecture Plan

Weekly meeting and discussion with Supervisor regarding thesis

Mandatory attendance of at least 3 technical/professional development seminars throughout the semester

Timeline	Milestone	CO	PO
Semester I: Before Midterm	Attend Seminar on Responsible and Ethical Conduct of Research	CO4	PO(h)
Semester I: Week after Midterm	Thesis proposal presentation	CO1	PO(b)
Semester I: Week after Midterm	Thesis proposal presentation	CO6	PO(l)
Semester I: Final Week	Thesis progress report	CO2	PO(d)
Semester I: Final Week	Thesis progress report	CO3	PO(a)
Semester II: Week after Midterm	Thesis progress presentation Thesis draft/outline submission	CO5	PO(j)
Semester II: After Final Exam	Final Thesis presentation Thesis book submission	CO1	PO(b)
		CO2	PO(d)
		CO3	PO(a)
		CO4	PO(h)
		CO5	PO(j)
		CO6	PO(l)

Thesis Evaluation and Assessment Policy

Students will submit initial draft copy of thesis to their respective supervisors by the 14th week of 2nd semester
Students will submit 3 hard copies of their updated draft thesis to their respective thesis supervisor and external examiners by / before 1 week of the thesis presentation date.
The supervisor will check plagiarism of the thesis with plagiarism check software
Examiners will evaluate the draft thesis book and final presentation as per rubric.

Evaluation Rubric

Course Outcome	Mapped PO	Course Outcome Text as per syllabus	Assessment Criteria	Marks allocation (supervisor)	Marks allocation (external 1)	Marks allocation (external 2)
CO1	PO(b)	Identify, formulate, research literature, interpret data, and analyze problems using principles of mathematical, natural and engineering sciences	Introduction chapter of the thesis	70	30	30
CO2	PO(d)	Investigate of problems using research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of information to provide valid conclusions.	Methodology, Results and Discussion Chapters of the Thesis	70	30	30
CO3	PO(a)	Apply knowledge of mathematics, science, and engineering to solve research problems	Thesis progress reports / presentations	70
CO4	PO(h)	Demonstrate adherence to professional ethics and ethical principles of research	iThenticate report, supervisor assessment	70
CO5	PO(j)	Communicate effectively with oral presentation and detailed thesis report	Final Presentation, Overall structure of thesis	70	30	30
CO6	PO(l)	Research contemporary aspects related to the problem and topic through detailed literature review and understand	Literature Review, Bibliography, Future work of thesis	70

Mandatory Final Thesis Submission

As per BUGS decision (BUGS Meeting No 11/2023), as a mandatory requirement for graduation, students must submit a hard copy thesis, in approved template, duly signed by their respective supervisors, to the Faculty of EEE library, and submit the acknowledgement slip from the library to their respective advisors. Respective advisors will only forward the application of graduation after the receipt of the acknowledgement slip. Faculty of EEE library will store the thesis for at least 3 years. Such hard copy of thesis will not be publicly uploaded into the website.

Thesis Template and Format

Please see page.

Teaching | SAJID Lab

EEE 6516 (October 2026)

Course Information

Syllabus

Course Content

Prerequisites

Course Outcomes (CO)

Weekly Plan

Assessment

Grading Policy

Assessment Milestones

Midterm Assignment and Final Project

Late Submission

Policies

Incomplete Grade Policy

Make-up Class Test Policy

Academic Integrity and Generative AI

Textbooks and Resources

Course Materials

Textbook

Further Reading

Software

Why Should an EEE Graduate Student Take This Course?

EEE 415 (Jan 2026)

Announcement

Introduction

Syllabus (as approved in 2022)

Grading Policy

Weekly Schedule

Textbooks

Semester Plan

EEE 416 (Jan 2026)

Announcement

2023Introduction

Syllabus

EEE 416

EEE 415

Course Objectives

Course Outcomes

KPA Mapping

Weekly Plan

Distribution of Marks

Lab Usage Policy

EEE 400

EEE 400 - Thesis

Course Content (As approved by the Academic Council)

Course Objectives

Knowledge required

Course Outcomes

Mapping of Knowledge Profile, Complex Engineering Problem Solving and Complex Engineering Activities

Lecture Plan

Thesis Evaluation and Assessment Policy

Evaluation Rubric

Mandatory Final Thesis Submission

Thesis Template and Format