Curriculum

The course introduces basic reinforcement learning for undergraduate students. It introduces the minimum mathematics necessary to understand reinforcement learning and helps students to get interested in it through easy examples and Python practice. The students can learn basic concepts such as Markov decision process, dynamic programming, TD learning, and Q-learning, and also can learn the latest deep reinforcement learning techniques.

This course will review key concepts of semiconductor device physics and survey fundamental theory and novel ideas of realizing “beyond Moore” technology and devices. In addition to the traditional approach to semiconductor devices based on the effective mass approximation and drift-diffusion equation, the first-principles approach starting from atomistic viewpoint and quantum transport equation will be presented and emphasized. Students will be guided to carry out computer programming and hands-on computer simulations by learning several important numerical analysis techniques.

In addition to the security and privacy of our everyday life, uses of cryptography have been continuously expanding from quantum cryptography to blockchain/cryptocurrency. Instead of understanding detailed mathematical theories behind cryptography, the purpose of this class is to learn basic cryptography, cryptographic protocols, and the current and future applications of cryptography. As a case study, we will review details of the blockchains technology.

This lab course will allow students to learn TensorFlow Lite and deploy it on wearable and sensor-equipped microcontrollers. The course will start with a series of labs to give students basic skills and experience in this area. Building on this knowledge, students will then form teams to propose, design, and develop a novel interactive wearable computing prototype that solves a genuine user problem in an area such as authentication, accessibility, training, or mobility.

The course gives an introduction in the basics of quantum computing, focusing on the hardware choices theat need to be made, the possible micro-architecture but will also insist on the development of quantum applications. The latter will involove the presenation of the quantum gates and will provide exercises to the students to develop small scale quantum circuits.
The intended quantum platform that can be used by the students is the Qiskit platform, developend by IBM, and which is freely available on the Interntet.
There will be another and second part of the course as we will also focus on the use of DNA as a data storage technology. As the terms suggests, it is based on the omnipresent DNA and it has already been developed as a storage device. The students will get exercises that will show how digital data can be store in a DNA format and how the DNA-data can be translated in quantum concepts such that algorithms can be executed.

This course explores the role of artificial intelligence (AI) in cyber psychological warfare and cognitive strategy design. Students will learn the fundamentals of cyber psychological warfare and analyze how AI affects human behavior, psychology, and decision-making. Throughout this course, students will develop strategic approaches incorporating psychological and cognitive elements powered by AI while considering the ethical implications and societal responsibilities of these technologies.

In this course, the technology trend and basic concept of the information display devices will be studied. In particular, a fundamental theory of light emission for display, driving method for display, thin film transistors, LCD, QD, ELD, PDP, OLED, FED, and e-Paper will be introduced and examined.

This course introduces fundamental concepts of quantum physics in the context of future electrical engineering (EE) applications and will be run alternatively by Device and Wave Divisions. Provided by the Device Division, the focus of this semester will be on the basic principles of quantum phenomena and representative models of quantum systems within the context of semiconductor physics and nanoelectronic devices. Computer simulations will be utilized to enhance the understanding of quantum phenomena.

Textbook: A. F. J. Levy, “Applied Quantum Mechanics, 2^nd Ed.” (Cambridge, 2006)

Quantum information technologies make it possible to achieve efficient computation and a higher level of security in communication over classical counterparts. The course introduces basics concepts and tools to understand quantum information processing and also provide examples of quantum algorithms and quantum key distribution protocols.

This course introduces the foundations of computational imaging and then covers the process of modeling imaging tasks as inverse problems and solving them using classical and modern reconstruction methods. It demonstrates how computation expands imaging capabilities through applications like lensless imaging and computational microscopy.