AAI-CPE-EE 800

Advisor: Dr. Kevin Lu, Teaching Professor, Electrical and Computer Engineering (ECE)

Contact Information: Burchard B-308E, kevin.lu@stevens.edu 

GitHub: https://github.com/kevinwlu/iot

$ git clone https://github.com/kevinwlu/iot.git

Office Hours: Tuesday and Thursday 12:00 PM to 2:30 PM

Prerequisite: None

Corequisite: None

Cross-listed with: None

Enrollment via Google Form and Workday Student

IEEE Editorial Style Manual

IEEE Publication Templates 

IEEE Xplore 

Project Titles

Overview presentation by Prof. Kevin Lu

Course requirements

This course is a research course designed for master's students to solve a specific challenging research problem in the fields of electrical engineering, computer engineering, and applied artificial intelligence. It is not a course designed for students to learn a particular language or system. Instead, students are required to develop a new model, algorithm, architecture, design, or protocol to solve a challenging research problem.

• Students are required to identify a specific challenging research problem and discuss the problem with their project advisors. Depending on the scale of the problem, the project advisor may decide it's an individual project or team project.

• Each student are required to enroll in EE 820A and attend all the seminar talks.

• Each students must work on the project at least 10 hours a week and meet his/her project advisor on a weekly basis to discuss the research. A weekly progress in expected.

• Students are expected to meet the advisor on a regular basis to discuss the project progress.

• Required submissions:

  • A 1-2-page research proposal; due at the end of the second week of the semester.

  • A 3-4-page mid-stage report; due in the middle of the semester.

  • A 6-8-page final report and 1 1-page poster; due in the final exam week.

  • All submissions will be jointly graded by the project advisor and Prof. Min Song.

Critical components of the final report

• Section I: Introduction. Problem introduction, challenges, and the related work

• Section II: Formal definition and/or formulation of the problem

• Section III: Solution ( a new model, algorithm, architecture, design, or protocol

• Section IV: Numerical results and analysis

• Section V: Conclusion

• References

Grading procedures

• 2% Research proposal

• 15% Mid-stage report

• 20% Final report Sections I and II

• 25% Final report Section III

• 20% Final report Section IV

• 5% Final report Sections V and references

• 3% Poster design

• 10% Meetings and discussions