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ECS at UTD Ivor Page Associate Dean for Undergraduate Education Four degrees . TE CS EE SE Makeup of a degree: . 42 hours State mandated core curriculum (English/math/science/gov’t/history/soc’sci) Major required courses: 53 – 69 hrs Electives: 12 – 21 hrs Total hours: 120 – 128 hrs, must include 51 upper division hours. Computer Science . Computer Graphics C++/Java Discrete Math Programming languages Data Structures and Algorithms Automata Theory Telecomm’s Networks Computer Architecture Linear Algebra Probability theory and Statistics Operating Systems Software Engineering Electrical Engineering . Digital Systems Digital Circuits Communication Systems Probability Theory & Statistics Electronic Circuits Differential Equations Signals and Systems Electronic Devices Electromagnetic Engineering Electrical Network Analysis Advanced Engineering Math Systems and Controls Telecomm’s Engineering Computer Architecture . Digital Signal Processing Differential Equations Computer Networks Operating Systems Signals and Systems Electrical Network Analysis Probability Theory & Statistics Advanced Engineering Math Digital Communications Digital Systems Discrete Mathematics Algorithms Data Structures Communication Systems Wireless Communication Telecom Switching & Transmission Software Engineering C++/Java . Discrete Math Operating Systems Computer Architecture Programming languages Data Structures and Algorithms Software Architecture Linear Algebra Probability theory and Statistics Software Engineering Software Requirements Software Testing, Verification, Validation and QA The Fast Track Program Seniors with good GPAs can take up to 15 hrs of graduate coursework while they are undergraduates. On graduation, they automatically become MS students (no GRE requirement), and the graduate hours they have already taken are subtracted from their MS requirements. The MS only requires a further 33-15 = 18 hours after the BSc. Why You Will Succeed at UTD Experienced Faculty Instructors – no TAs Teaching ECS courses. Great Tutorial Support From Students and From UTD’s Learning Resource Ctr. Drop and Repeat Policies Designed to Give You a Second Chance. Great Professional Advisors To help you through the tough times To help you navigate the system and graduate on time. Why You Will Succeed at UTD Great faculty advisors to help you with career choices and degree planning. Research faculty – opportunities for you to contribute to finding new knowledge. Work while you learn! One of the largest co-op programs in the nation. If You Can Get Into UT Dallas, We’ll Work Hard to Help You Graduate. A Simple Puzzle. At a school picnic there is a tug-of-war competition. There are N students and you know their individual weights. Divide the students into two teams such that the number of students on each team differs by at most one and the total weights of the teams are as close as possible. A Simple Puzzle - Solution The only known way to solve this problem is to try every possible way of halving the N students. That’s N! (N/2!)2 subsets, and for N=100, that’s about 2100 ≈ 1030 subsets. Another simple puzzle Given a set of N positive integers. Is there any subset of these numbers whose sum equals some target value T? The only known way is to try all subsets. That’s 2N subsets in the worst case. If N=100. 2100 is about 1030. The age of the universe is only 1028 nano-seconds. It’s how you look at it: . Are these three views of the same cube? It’s how you look at it 1 R? 1 1 1 1 1 It’s how you look at it Replace the rest of the network with Resistor R 1 R 1 R R = 1 + R/(1+R) Solving for R, R = (1+√5)/2 (1+√5)/2 is known as the Golden Ratio, Ø . It occurs frequently in nature. It’s how you look at it Fibonacci Numbers are defined as: Fibn+1 = Fibn + Fibn-1 : 1, 1, 2, 3, 5, 8, 13, … The ratio of two consecutive Fibonacci Numbers approaches the Golden Ratio, Ø : 1/1 = 1, 2/1 = 2, 3/2 = 1.5, 5/3 = 1.66’, 8/5 = 1.6, 13/8 = 1.625, 21/13 = 1.61538, Ø = 1·618033989 Binet's Formula: Fibn = round(Øn/√5 ) Golden Ratio Ø= 1 1 + 1 1+1 1+1 1+… Ø =√(1 + √(1 + √(1 + …))) Fibonacci Spirals Fib(n) = Øn/√5 That darned fly: . Distance d Train A Traveling at x mph Train B Traveling at y mph A fly travels back and forth between the trains at speed z mph (z>x+y). How far does the fly travel before the trains crash? What if the track is an arbitrary shape? Forget the track shape The fly and the shape of the track don’t matter if we know the distance traveled by the trains. We only need the time at which the trains collide. Then we take the speed of the fly and multiply by its flying time. Forget one of the trains Convert the two-train problem into a 1train problem by adding the speeds of the trains. The new sub-problem is as follows: How long does it take a train traveling at x+y mph to travel a distance d? Then, we multiply by the speed of the fly, z. Moore’s Law The logic density of silicon integrated circuits has closely followed the curve (bits per square inch) = 2^(t - 1962) where t is time in years; that is, the amount of information storable on a given amount of silicon has roughly doubled every year since the technology was invented. Moore’s Law This relation, first uttered in 1964 by semiconductor engineer Gordon Moore (who co-founded Intel four years later) held until the late 1970s, at which point the doubling period slowed to 18 months. Smaller chips mean faster speeds. Research Strengths I . Micro-Electronics:low power digital, analog, RF, Nano-scale components. Plasma research Optical Fiber communications: high speed switching, WDM, new modes. Quantum-well devices Coding Theory Wireless: propagation, modulation, CDMA, etc. Digital Signal Processing: fundamental algorithms, applications How small is small? Current integrated circuits have features that are smaller than 0.3 microns (millionths of a meter). Nano-devices have features 200 times smaller. A finger nail grows approximately 1/8 inch per week. That’s about 5 microns per second. Research Strengths II . Telecomm’s networks: Fundamental protocols, verification, network simulation Ad-hoc networks: clustering, routing, slot allocation Embedded Systems Distributed Algorithms Programming Languages Component reuse Computer Graphics, animation Research Strengths III . Graph Layout Multimedia Artificial Intelligence, computer vision Computability Traffic Light Controls Computer Arithmetic Digital Forensics Computer Architecture