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Do What You Love

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Why You Should Go To Graduate School in Computer Science – PowerPoint PPT presentation

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Title: Do What You Love


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Do What You Love
  • And God saw every thing that he had made, and,
    behold, it was very good. Genesis
    131
  • Delight thyself also in the LORD and he shall
    give thee the desires of thine heart.
    Psalms 374
  • Your work is going to fill a large part of your
    life, and the only way to be truly satisfied is
    to do what you believe is great work. And the
    only way to do great work is to love what you do.
    Commencement address by Steve Jobs, CEO of Apple
    Computer and of Pixar Animation Studios,
    delivered on June 12, 2005.

3
What is There to Love?
  • Research
  • What problem do you want to solve?
  • Who cares about this problem and why?
  • What have others done to solve it?
  • What is your solution to the problem?
  • How can you demonstrate this is a good solution?
  • Independent thought, creativity
  • Being able to make a difference in the world
  • Rigorous and rewarding

4
What is There to Love?
  • Teaching
  • Being able to present ideas and results clearly
    to others
  • Helping students to learn, grow, become better
    children of our Heavenly Father
  • Contribute to the mission of the university...
  • ... to assist individuals in their quest for
    perfection and eternal life. That assistance
    should provide a period of intensive learning in
    a stimulating setting where a commitment to
    excellence is expected and the full realization
    of human potential is pursued.

5
M.S. Degree
  • Mastery of a discipline
  • More in-depth CS knowledge
  • Specialized knowledge in your chosen area of CS
    (your thesis)
  • Greater job opportunities
  • Your specialization and problem-solving skills
    will be important and impressive to employers
  • Career Flexibility
  • Do you really know what you will want to be doing
    in 10 years?
  • Most people make multiple career changes

6
Ph.D. Degree
  • You get to do more of what you want
  • More research, more independent work
  • More freedom less guidance
  • Contributing to state-of-the-art
  • Different world of employees
  • You interview for different jobs more selective
    job opportunities
  • Expected that you shape your own and your
    companys direction lead and initiate
  • Making versus implementing decisions

7
Ph.D. - Two Routes
  • Academia
  • Different types of universities teaching versus
    research, small versus large, public versus
    private
  • Higher risk research
  • Publication (conferences journals)
  • Research funding proposals
  • Research Lab (industry or government funded)
  • Google, Microsoft, IBM, Intel, VMware, etc.
  • More stable funding
  • Research driven by needs of company or government

8
Salary
  • This is not what you should use to make your
    decision
  • General rule in many companies the more
    education you have the higher your salary
  • Lots of exceptions
  • Starting your own company
  • Getting in early with a startup that succeeds
  • Management MBA
  • The amount of money you make depends on your
    drive and your circumstances

9
Making a Decision
  • Be Patient
  • There are always more job offers
  • don't be rushed
  • Financial support available
  • PhD students generally funded
  • MS students may be funded but expect to pay your
    way
  • Time frames for completing degree
  • 2 years for M.S.
  • 5 years total for Ph.D. if concurrent with M.S.
  • When should you do it
  • Before you develop an expensive lifestyle
  • Very few people go back after leaving school

10
What to Do Now
  • Classes
  • Get good grades, work hard
  • Shift your attitude from surviving classes to
    learning concepts
  • Develop a portfolio of projects you have
    finished, both for classes and outside of classes
  • Get to know the faculty
  • Visit their web pages, read their papers
  • Take their classes do well in them!
  • Talk to them
  • Try to get involved in undergraduate research
  • Pray what is appropriate for you?

11
What to Do as a Graduate Student
  • Pick an Advisor
  • You should
  • like your advisor
  • like your advisor's research area
  • be willing to work for him/her
  • Your advisor is investing a lot in you (he/she is
    staking a portion of their career on you)
  • Try to be a full-time student
  • BYU requires Ph.D.s to be resident full-time
  • Plan to finish your thesis or dissertation before
    you leave

12
Why CS graduate work at BYU?
  • Nationally-recognized faculty solving problems
    that make a difference in the world
  • Funded research programs by Adobe, Google, NSF,
    DARPA, and many other industrial partners
  • Open access to nationally ranked super computer
  • Funded research opportunities with tuition
    benefits for qualified students

13
Applying to Graduate School
  • Application Items
  • Specify area(s) of research, possible adviser(s)
    talk to faculty ahead of time
  • Letter of intent
  • Why BYU? Why computer science?
  • What research areas are you interested in and
    why?
  • Letters of recommendation
  • At least two from profs (use M.S. Adviser if
    applicable)
  • Other GRE, transcript (if not BYU undergrad)
  • International TOEFL, financial certification
    form
  • Deadlines

Fall Term Winter Term
January 15 August 15
14
Research Areas in our Department
  • We would like to introduce you to our research
    areas
  • A mission statement for each lab
  • What to look for
  • Make a note of faculty you are interested in
  • Look for classes to take at 400 level
  • Contact faculty for more details on their
    research, undergraduate and graduate research
    opportunities

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Data MiningChristophe Giraud-Carrier
  • The Data Mining Lab researches and develops
    methods to improve the process of extracting
    actionable knowledge from data
  • Preparation CS478, CS470
  • Lab Meetings (Fall 05) Tuesdays 1000-1100
    in 1138 TMCB
  • We have several (urgent) projects suited for
    undergraduate training and research with
    industrial partners (contact cgc_at_cs.byu.edu)

Special Introduction to Data Mining Meeting
on Oct. 25th Dont miss it!
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Natural Language Processing
S
PP
IJ
IN NNP

Welcome
to N.L.P.
18
Information Dynamics Group
Sean Warnick (CS) in collaboration
with Christophe Giraud-Carrier, Jeff Humpherys,
Kevin Seppi, and others
Use mathematical systems theory to design
algorithms for scientific processes such as 1)
Modeling learning from data 2) Feedback
Control decision support 3) Verification
systematic experimentation 4) Optimization
tractable computation
Computational Economics
Environmental Management
Intelligent Manufacturing
Systems Biology
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  • Research in Mobile and Wireless Computing
  • Wireless Personal Area Networks (WPANs)
  • IrDA, Bluetooth, WirelessUSB performance analysis
  • Quality of Transport (QoT)
  • Dynamic heterogeneous transport selection
  • Poket Doktor
  • Wireless healthcare application

Dr. Charles Knutson
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Research Problem How to establish trust between
strangers online?
Internet Security Research Lab
http//isrl.cs.byu.edu
COURSE PREPARATION
CS 465 Computer Security
CONTACT
Our approach Automated trust negotiation
authenticates strangers in open systems based on
their attributes
Dr. Kent E. Seamons
REASERCH OPPORTUNITIES
seamons_at_cs.byu.edu
LAB MEETING TIME
Undergraduate MS PhD
Tues/Thurs 3pm, 2221 TMCB
22
Dan Ventura Neural Networks and Machine Learning
Laboratory Wednesdays 1200pm
Teaching machines to learn and to learn how to
learn
Learning Model A
What kinds of learning models are available
and what can they do?
Which learning model is best for a particular
learning problem?
Learning Model B
. . .
Learning Model Z
Related Courses cs252, cs478, cs470
23
Dr.Tony Martinez
  • Goals and Contributions of the NNML
  • Improved learning algorithms and models
  • Combine best of neural network, symbolic, and
    other machine learning paradigms
  • Diverse research opportunities including
    algorithm proposal, applications, theoretical
    issues and more
  • Suggested undergraduate electives 478, 470
  • Meetings times Wednesdays 12-1pm, 1130 TMCB
  • Contact Dr. Tony Martinez (martinez_at_cs.byu.edu,
    3360 TMCB) for more information regarding joining
    the NNML group.

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Human-Centered MachineIntelligenceMichael
Goodrich
  • Human-Robot Interaction
  • UAV-Enabled Wilderness Search and Rescue
  • Multi-Agent Learning
  • Undergrad research opportunities available
  • Lab meetings Wednesday at 1pm in 3365 TMCB

26
Computational SciencesLaboratory
  • DNA Sequence Alignment
  • Gene Finding
  • Active Region Detection
  • Species Evolution
  • New Phylogenetic Algorithms
  • Protein Prediction
  • Protein - Drug Interaction
  • Open-Source Tools
  • Soda, TCS
  • Supercomputer Applications
  • Mark Clement Quinn Snell

27
3D Computer Graphics and Virtual RealityDr.
Parris Egbert
Photorealistic Rendering
Cognitive Modeling in Graphics
Virtual Environment Creation and Navigation
Physically based modeling and rendering
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Bill Barrett
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More Image Magic
Smoothing
Nudging
Filling
Prof. Bryan Morse
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Hyperspace Research Group
  • Mission statement computer graphic presentation
    of data, objects, and phenomena with 4 or more
    simultaneous dimensions
  • Preparatory course CS 455
  • CS Departments oldest, continuous research
    project, involving graduates and undergraduates
  • Worlds leader in Cartesian hyperspace graphics
  • Robert P. Burton
  • 3326 TMCB
  • rpburton_at_cs.byu.edu

31
Dr. Tom Sederberg
1989 1999 2009
Research areas Computer Graphics, Geometric
Modeling Courses CS455, CS557 Research
Opportunities Family History Technology
32
Data Stream Management
  • Mission Statement support on-line
    analysis/applications of rapidly changing data
    streams in sensor networks
  • Current Research Topics
  • Dynamic load shedding
  • Data stream mining
  • Continuous query processing
  • Streaming applications
  • Etc.
  • Preparatory Courses CS 653 (Info. Retrieval), CS
    452
  • Research lab Advanced Database Applications Lab
  • Lab location 2245 TMCB
  • Lab Director Dr. Dennis Ng (3322 TMCB)

Fig. The dynamic load shedding system for joining
data streams in sensor networks
33
Peer-to-Peer Information Sharing
  • Scott N. Woodfield
  • User Friendly Meta-Models for Conceptual
    Modeling
  • Highly Redundant, Distributed, Heterogeneous
    Information Storage
  • Peer-to-Peer Networking for Fast, Reliable
    Communication
  • Applications of the Above to Genealogical
    Applications

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Information ExtractionDave Embley
From the Web
From Images of Historical Documents
Mission Statement Find, Extract, Structure,
Index, Query, Integrate, Summarize. Required
Preparation CS452 Useful Preparation CS470,
CS478, CS579. Fall05 Lab Meeting Time
Wednesdays 300 400 in the CS conference
room. Undergrads Welcome one current senior
honors thesis have sponsored several ORCA
grants.
http//www.deg.byu.edu/
36
Conclusion
  • I am both hopeful and expectant that from this
    university there will rise brilliant stars in
    drama, literature, music, art, science, and all
    the scholarly graces. This university can be the
    refining host for many such individuals who, long
    after they have left this campus, can lift and
    inspire others around the globe.
    President Spencer W. Kimball (Educating Zion, p.
    77)
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