Computer Science

This course includes knowledge of common methods in asymmetric encryption, as well as possible attacks in faulty implementations of these methods: RSA, El-Gamal, Diffie-Hellman-Key-Exchange, elliptic curves, and selected methods of Post-Quantum-Cryptography. Students who completed this course possess profound knowledge of cryptographic methods. They are able to correctly and securely use cryptographic protocols. They are proficient in verifying the security of One-Way-Functions and (Pseudo-)Random-Number-Generators. Furthermore, they are able to recognize and avoid typical mistakes in asymmetric encryption.

This course provides an introduction to the key concepts, issues, and methods in human-computer interaction and interaction design. Through a combination of lectures and exercises, it covers usability, designing user-friendly systems, and evaluating user interfaces. The course discusses theories of human-computer interaction, the special challenges associated with the design of user-friendly interactive systems, advantages and disadvantages of different forms of interaction, building user interfaces and prototypes of user interfaces, and how to examine the usability of IT systems in a rigorous way.

This course covers various aspects of multi-core programming. Topics include programming models for multi-threading (Pthread), GPUs (CUDA), and the theoretical backgrounds behind them. Students also implement and optimize various emerging applications such as matrix multiplication, reduction, and deep learning kernels.

Through this course, students will learn basic optimization knowledge, be able to formulate a practical problem into a solvable optimization model, solve the problem using existing commercial or open source software or design their own algorithms to solve the problem.

This course mainly includes the introduction of convex analysis basics, linear and linear cone programming, optimal condition Lagrange duality, some basic optimization algorithms and their applications in finance, signal processing, machine learning and statistics.

This course instructs on python programming from a digital humanities perspective. It begins with the basics using interactive notebooks that require no installation. First, the course covers the basics of programming such as data types, loops, and variables. Later it explores and solves language-based and digital humanities problems using new programming skills and natural language processing (NLP) tools. Python 3 will be used in this course.

This course introduces the issues of digital ethics and AI faced by individuals and organizations. It covers the ethical principles governing the behaviors and beliefs about how we use technology, and how we collect and process personal information in a manner that aligns with individual and organizational expectations for security and confidentiality. It addresses challenges in balancing technological desirability with social desirability while developing digital products and services. Key topics include Professional Ethics, Artificial Intelligence Ethics and Governance, Automation and Autonomous Systems, Digital Ethics by Design, Data Protection in ICT, Human Machine Interaction, Computing for Social Good, Digital Intellectual Property Rights, and Digital Divide, Equity, Accessibility, and Inclusion.

This course introduces the mathematical formalism of quantum information theory. Topics include a review of probability theory and classical information theory (random variables, Shannon entropy, coding); formalism of quantum information theory (quantum states, density matrices, quantum channels, measurement); quantum versus classical correlations (entanglement, Bell inequalities, Tsirelson's bound); basic tools (distance measures, fidelity, quantum entropy); basic results (quantum teleportation, quantum error correction, Schumacher data compression); and quantum resource theory (quantum coding theory, entanglement theory, application: quantum cryptography). 

This course explores research issues in the newly emerging field of mobile computing. Many traditional areas of computer science and computer engineering are impacted by the constraints and demands of mobility. Examples include network protocols, power management, user interfaces, file access, and security. 

This course emphasizes hands-on laboratory experience and teaches students research background, relevant theories, and basic laboratory techniques relevant to their field of study. Students formulate a research plan, implement it by conducting experiment-based research, and convey the results in scholarly presentations. Students submit a written research report at the end of the course.

The Individual Research Training Senior (IRT Senior) Course is an advanced course of the Individual Research Training B (IRT B) course in the Tohoku University Junior Year Program in English (JYPE) in the spring semester. Though short-term international exchange students are not degree candidates at Tohoku University, a similar experience is offered by special arrangement. Students are required to submit: an abstract concerning the results of their IRT Senior project, a paper (A4, 20-30 pages) on their research at the end of the exchange term, and an oral presentation on the results of their IRT Senior project near the end of the　term.