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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