Master Degree Program in
Master of Science In Computer Systems and Engineering
The MSCSE program is designed for students who intend to become professional engineers in the high-technology industry, as well as for those who desire a modern, general education based on the problems and the promises of a technological society.
- To provide each student the best education by tailoring each student’s study plan based on the student’s background and interests. To provide in-depth professional training with state-of-the-art learning resources to the student.
- To provide relevant laboratory experience throughout each program as an integral part of the education.
- To nurture a learning environment which leads to professional values recognizing high quality and integrity in a true engineer.
- To provide graduate students an opportunity to pursue advanced training and professional development to practice their profession with increased competence.
A minimum of 30 semester units of graduate study are required for the Master of Science in Computer Systems and Engineering program (MSCSE). They include a few required core courses, a number of elective courses based on the student’s selection of technical pursuit, and a required capstone course. The computer systems engineering coursework will develop technical skills beneficial to the student for career planning. The student also has the opportunity to take elective courses outside of computer systems engineering to broaden the student’s skillset. The student must meet prerequisite requirements when taking any course. Upon clearing background preparation work, the student starts to take courses to meet the degree requirements. The student must begin his/her graduate study with the subjects listed in the Core Course section.
Andreas Ramos
was the head of Global SEO at Cisco, where he used 40 languages in 84 countries. He has managed global SEO and Google Adwords for Harvard and MIT where he used 300,000 keywords in thirty languages. He currently manages SEO and Google Adwords for Stanford. He was the director of the digital agency at Acxiom where he worked with global corporations. He has founded two digital marketing agencies. He has written fourteen books on digital marketing. One book was published in China by Tsinghua University Press. His books have been translated to six languages. He was the technical editor of the leading book on SEO, which was published by IBM Press. He also teaches digital marketing at INSEEC, a leading French business school.
Daniel Zanger, Ph.D.
has over 20 years of experience in both industry and the federal government, working extensively in the fields of theoretical and applied machine learning, data analysis, optimization, statistical database privacy, cryptology, quantum computing, and others. He has applied techniques from these fields to problems in such areas as text mining, image processing, operations research, and multi-sensor fusion. Dr. Zanger has authored numerous publications in refereed journals and conference proceedings in various technical fields including mathematics (partial differential equations), probability theory, information retrieval, statistical learning theory (applied to finance), operations research, and database privacy. He holds a Ph.D. in Mathematics from the Massachusetts Institute of Technology (MIT) as well as a B.A. (with Highest Honors), also in Mathematics, from the University of California at Berkeley.
Danian Gong
Currently work at CADENCE Design Systems as Sr. Principle Engineer, responsible for developing high performance microprocessor; also serves as adjunct professor in CSTU, where he teaches Artificial intelligence and deep learning. Study and work Experience： 1996 Graduate from Zhejiang University, Hanzhou，bachelor degree in EE major. 2001 Graduate from Tsinghua University, Beijing, Ph.D and master degree in EE major. 2001-present, R&D management and development in Silicon Valley High Tech companies