90 likes | 387 Views
Mathematics & Information Engineering Interdisciplinary Programme (MIEG) Bob Li & Chandra Nair Dept of Info Eng. Mathematics & Information Engineering Interdisciplinary Programme (MIEG) . Degree: B.Sc. in Mathematics and Information Engineering
E N D
Mathematics & Information Engineering Interdisciplinary Programme (MIEG) Bob Li & Chandra Nair Dept of Info Eng
Mathematics & Information Engineering Interdisciplinary Programme (MIEG) • Degree: B.Sc. in Mathematics and Information Engineering • Enables students to develop in-depth mathematical thinking and solid engineering skills • Jointly offered by Department of Information Engineering & Department of Mathematics • Scholarships in both departments are available to MIEG majors
M + IE connections a quick list Mathematics Information Engineering Digital Signal Processing Image Processing Digital Compression Discrete Fourier Transform Discrete Time Series Analysis Recursive Regression Statistical Analysis Data Analysis Random Processes Martingale Real Analysis Probability Theory Combinatorics Adaptive Algorithms Machine Learning Neural Networks Genetic patterns Encryption Network Security Traffic Analysis Switching Information Theory Error Correction Codes Network Coding Number Theory Linear Algebra Galois Theory Algebraic Curves Ring Theory Graph Theory
Engineer vs. Mathematician • Engineer ≈ inventor: applies scientific principles to develop useful objects in the real world • Mathematician ≈ discoverer: discovers beautiful phenomenon in the “perfect” world defined by axioms Information engineering Mathematics
Engineer vs. Mathematician • Engineer ≈ inventor: applies scientific principles to develop useful objects in the real world • Mathematician ≈ discoverer: discovers beautiful phenomenon in the “perfect” world defined by axioms MIEG
Major required subjects MATH 1050 – Foundations of modern mathematics MATH 1030 & MATH 2040 – Linear algebra MATH 2010 & 2020 – Advanced Calculus MATH 3280 or ENGG 2430 – Probability MATH 2070 – Algebra MATH 2230 – Complex variables MATH 2050 – Real analysis CSCI 2100 – Data Structures IERG 2051 – Signal Processing ENGG 2310/3820 – Communication Systems / Lab IERG 3080 – Software Design Principles IERG 3310/3921 – Computer Networks / Lab
Admission quota • For year-1 Enrichment Math students = 7 (out of 27) • For year-1 Engineering students 25 (out of 500)
Some recent MIE graduates • Ka Kit Lam – graduated 2011 – Ph.D. candidate, EECS, UC Berkeley • Li Cheuk Ting – graduated 2012 – Ph.D. candidate, EE, Stanford • Yin Zi – graduation expected 2013 – Ph.D. admission, EE, Stanford