Transcript welcome - Carnegie Mellon University

Charalampos (Babis) E. Tsourakakis
3rd Year Graduate Student
Open House
February 26th , 2010
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Carnegie Mellon University is a historical
university with living history.
Herbert Simon
Alan Frieze
Avrim Blum
Manuel Blum
Tom Mitchell,
Head of MLD
Carlos Guestrin John Lafferty
Alen Newell
Stephen Fienberg
Larry
Wasserman
Admission
highly
competitive!
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International Student (Hellene, ECE NTUA)
2007-2009 worked with Christos Faloutsos on
Data Mining (Tensors, Graphs and Large
Scale Data Mining using Hadoop)
Switched at the end of the second year.
Now,
Algorithm Design (TCS)
Manifold Learning (ML)
Breast Cancer Evolution (App)
Gary Miller
e.g., Miller Primality Test
Russell Schwartz
e.g., decoding human genome
Change/add
advisor
Immigration course: (if you want)
Data analysis
faculty gives talks,
project,
you choose advisor
speaking skills
( get MS)
Start doing research!
(publish 1st paper)
Finish!
Propose
Summer
internships
time
0
1
2
3
Coursework: 5 core courses:
• Intermediate statistics, ML
• Stat ML, Algorithms, Data mining
+3 electives (1 from statistics)
4
5…
Conduct research
TA for 2
classes
Enjoy dept. tea gathering and TGs
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Very critical choice for your career.
Great faculty to choose from.
Make a good choice by:
 choosing a project that excites you
 making sure that you and your advisor have the
same research “mentality” (Ask yourself, do you
like more applications, theory, a mixture of them
and what proportion from each)
 reading papers of your potential advisors
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Year 1:
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Intermediate statistics
Intro machine learning
Stat. machine learning
Algorithms
Year 2:
 Data mining
 Advanced Discrete Math:
Additive Number Theory
 Advanced Discrete Math:
Mixing times and Markov
Chains
 Computational Methods for
Biological Modeling and
Simulation
(Some of my electives)
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Many ML classes
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Graduate ML
Statistical ML
Graphical models
Convex optimization
Graduate AI
Learning theory
Bayesian methods
Comp bio + learning
Computational Complexity
Randomized algorithms
Approximation algorithms
Lots of area-specific machine
learning (text, bio, brain, …)
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Requirements
 Speaking skills
 Data analysis project
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You have an advisor(s)
 who is (are) “responsible” for you
meetings
 You fill out a form
 All the faculty discuss every student
 You (and your advisor(s)) get feedback
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MLD Seminars:
 MLD/Google seminar
 Intelligence seminar
 Machine learning lunch
▪ organized by students
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Many other seminars:
 Theory, LTI, Robotics,…
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MLD weekly tea gathering
TGs (Thank Goodness It’s Friday)
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A city which has two main advantages which
are typically inversely proportional:
 Many things to do around, good restaurants, nice
coffee shops, bars, pubs, dancing places etc.
 Inexpensive.
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Easy to travel to other beautiful cities which
are near, e.g., Philadelphia, New York City,
Toronto.
You can feel all
four seasons
while in Pittsburgh
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Different Health Plans
 Basic (<~1K for a year)
 Enhanced
 +Dental
 +Vision
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CMU Health Services
UPMC
My personal experience so far has been more
than good.
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Most of the students live in Squirrel Hill,
Shadyside, Oakland.
Other neighborhoods: Bloomfield, Point
Breeze, Regent Square.
If you do not own a car, make sure that you
pick a place with many buses coming by from
there (e.g., Squirrel Hill, Shadyside)
Great places to live for really good prices.
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An excellent environment for conducting
research, having pleasant breaks (great
coffee on the 3rd floor), interesting research
discussions on a whiteboard, Tea Parties.
Biking
Canoeing
Caving
Swimming
Climbing
Ski (Seven Springs
Resort) with
student prices ~15$
Hiking
Kayaking
Tennis
Scuba Diving
Skydiving
Chess Club
Gym
Volleyball, Basketball
Badminton
Dancing
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Publications
Travelling.
I have visited Belgium, France, Greece, Italy,
Stanford, New York.
Meeting Scientists from all over the world
Attend highly interesting talks (some of
them).
Communicate your ideas, get people to learn
about your research.
See and explore new places.
When you set out on your journey to Ithaca,
pray that the road is long,
full of adventure, full of knowledge….
…Always keep Ithaca in your mind.
To arrive there is your ultimate goal.
But do not hurry the voyage at all…
Welcome to CMU and
Congratulations again!
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Joseph Bradley for sharing previous year’s
slides.
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Jernej Barbic
http://www-rcf.usc.edu/~jbarbic/cmu-start.html
Diane Stidle
“Mother” of
MLD