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Computer Science

Tasos Kyrillidis

Instructor listed on Rice's public Course Schedule.

Average rating

3.7

11 temporary mock ratings

Difficulty

2.7

course-linked average

Courses

5

in seeded sections

No matched public profile yet

This instructor is listed in Rice's public course schedule, but Perch did not find a reliable match in the public People of Rice profile directory.

Courses taught

COMP 282

Computational Optimiz. For AI

This course provides the mathematical and computational foundations necessary for understanding mod-ern AI/ML systems, with a focus on optimization and computational perspectives. The course interweaves three main threads: (1) computational linear algebra through the lens of optimization problems, (2) multi-variate calculus and optimization concepts essential for understanding learning algorithms, and (3) practical implementation using Python’s scientific computing ecosystem. Students will learn to implement and analyze fundamental algorithms for machine learning, developing both theoretical understanding and practical coding skills. The course emphasizes computational efficiency, algorithm implementation, and the connections between mathematical theory and practical AI applications. This class is intended to prepare students for upper-level AI classes.

Computer ScienceNone3 credits
3.77.7hKyrillidis, Tasos

COMP 390

Computer Science Projects

Theoretical and experimental investigations under staff direction. Repeatable for Credit.

Computer ScienceNone1-3 credits
4.26.2hAliakbarpour, Maryam, Chen, Hanjie, Chen, Ken, Cox, Alan L., Cutler, Scott, Ferreira Flores, Rodrigo, Hang, Kaiyu, Johnson, Dave, Kavraki, Lydia, Kyrillidis, Tasos, Lopes da Silva, Arlei, Myers, Risa, Nakhleh, Luay, Ng, T. S. Eugene, Patel, Tirthak, Sano, Akane, Schreib, Rebecca, Sedlazeck, Fritz, Subramanian, Devika, Treangen, Todd, Unhelkar, Vaibhav, Vardi, Moshe, Veeraraghavan, Ashok, Warren, Joe D., Wong, Stephen

COMP 490

Computer Science Projects

Theoretical and experimental investigation under staff direction. Repeatable for Credit.

Computer ScienceNone1-4 credits
4.06.7hAllen, Genevera, Byrne, Michael, Cox, Alan L., Ferreira Flores, Rodrigo, Goldman, Ron, Hang, Kaiyu, Joyner, Mack, Kyrillidis, Tasos, Mamouras, Konstantinos, Myers, Risa, Patel, Ankit, Schreib, Rebecca, Shrivastava, Anshumali, Tunnell, Chris, Unhelkar, Vaibhav, Wang, Yuke, Xing, Jiarong, Yao, Vicky

COMP 590

Computer Science Projects

Advanced theoretical and experimental investigations under staff direction. The student must have a full-time internship to receive 4 credits for this course. Repeatable for Credit.

Computer ScienceNone1-4 credits
3.45.7hAliakbarpour, Maryam, Baraniuk, Richard G, Chen, Hanjie, Chia, Nai-Hui, Cox, Alan L., Fallah, Alireza, Goldman, Ron, Hang, Kaiyu, Jermaine, Christopher, Joyner, Mack, Kavraki, Lydia, Kyrillidis, Tasos, Lopes da Silva, Arlei, Mamouras, Konstantinos, Mellor-Crummey, John, Myers, Risa, Nakhleh, Luay, Ng, T. S. Eugene, Ordonez Roman, Vicente, Patel, Ankit, Patel, Tirthak, Rixner, Scott, Shrivastava, Anshumali, Simar, Ray, Treangen, Todd, Unhelkar, Vaibhav, Vardi, Moshe, Wang, Yuke, Warren, Joe D., Wei, Chen, Wong, Stephen, Xing, Jiarong, Yao, Vicky

COMP 800

Graduate Research

Repeatable for Credit.

Computer ScienceNone1-15 credits
4.28.5hAliakbarpour, Maryam, Braverman, Vladimir, Chen, Hanjie, Chia, Nai-Hui, Cooper, Keith, Cox, Alan L., Fallah, Alireza, Goldman, Ron, Hang, Kaiyu, Hu, Ben, Jermaine, Christopher, Johnson, Dave, Kavraki, Lydia, Kyrillidis, Tasos, Lopes da Silva, Arlei, Mamouras, Konstantinos, Mellor-Crummey, John, Nakhleh, Luay, Ng, T. S. Eugene, Ordonez Roman, Vicente, Patel, Ankit, Patel, Tirthak, Phillips, George, Rixner, Scott, Shrivastava, Anshumali, Subramanian, Devika, Treangen, Todd, Unhelkar, Vaibhav, Vardi, Moshe, Varman, Peter, Wallach, Dan S., Wang, Yuke, Warren, Joe D., Wei, Chen, Xing, Jiarong, Yao, Vicky

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