CSE Undergrad News

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Overview:

4/7 – Weekly Typed

4/10 – Programming Competition Prep

Weekly Typed

Monday, April 7, 2014; 6 – 7:30pm; CSE 203

Ty Overby will be giving a presentation / code-lab about Scala, his favorite Object Oriented and Functional programming language. You are encouraged to bring laptops to the talk to participate.

Join the Facebook event: https://www.facebook.com/events/1421886981399509

Programming Competition Prep

Thursday, April 10, 2014; 4 – 5pm; CSE 403

“10 reasons why YOU should care about programming competitions”

Daniel Epstein (UW CSE, PhD Student) will cover why programming competitions will make you a better software developer and programmer, help you find a job, and most importantly, why they’re tons of fun! He’ll offer some tips for clever problem solving, go through problems from previous contests and their solutions, and demonstrate some common pitfalls.

Please fill out this interest survey: https://catalyst.uw.edu/webq/survey/apacible/230992

Join the Facebook event: https://www.facebook.com/events/540277926089641

All Engineering & Computer Science Majors
Entrepreneurship Information Lunch
Tuesday, April 8
12:30–1:20
CSE 691

RSVP Here

Curious about the startup scene? Looking for the skills and experience you need to take your idea to the next level?  Join us for lunch and learn about all the ways YOU can get involved in entrepreneurship at UW!

Some of the things we’ll talk about include:

•         The new Entrepreneurship Minor for non-business majors
•         The highly-competitive Lavin Entrepreneurship Program for all majors
•         The UW Business Plan Competition (awarded $1,397,000 in prize money to 112 student companies)
•         The UW Environmental Innovation Challenge (awards $22,500 in prize money annually)
•         Startup UW – the club for student entrepreneurs on campus

You bring your curiosity – we’ll bring lunch!  RSVP here.

Can’t make it to lunch on Tuesday? Come have lunch at one of our OPEN HOUSES at the Buerk Center on Wednesday or Thursday! All majors welcome!

April 9 & April 10
Dempsey 211
12:30-1:20

RSVP Here

Don’t miss the robotics colloquium this week!

Please join us for the following talk:

Can We Predict Viral Memes?
Yong-Yeol Ahn, Indiana University Bloomington

Wednesday, March 19, 2014, 3:30 p.m.–4:30 p.m.
Mary Gates Hall, Room 420

University of Washington, Seattle campus

Some videos, pictures, and memes spread through billions of people while others quickly die out. Is it because of the innate quality of the memes or because of the celebrities like Justin Bieber? Or, is it just random? In this study we focus on the early diffusion pattern of memes in terms of underlying social network structure and demonstrate that the future success of a meme can be predicted by quantifying its early spreading pattern, particularly using the community structures in the network.

Bio: Yong-Yeol Ahn is an assistant professor of Informatics and Computing at Indiana University, Bloomington. He received his Ph.D. in Statistical Physics from KAIST, South Korea in 2008 and worked as a postdoctoral research associate at Northeastern University and a visiting researcher at the Dana-Farber Cancer Institute before moving to Indiana University. His research focuses on the structure of networks in various complex systems such as society, culture, and living organisms.

For more information on this and other talks please visit: http://data.uw.edu/seminar

For regular postings about talk, you should sign up for the talks list, but occasionally we will post them here.

http://www.cs.washington.edu/events/colloquia/

Please join the eScience Institute today, March 5, at 4:30 pm in the Bill and Melinda Gates  Commons (CSE 691).  Pizza at 4:15 PM.

Chris Bretherton, Professor, (UW Departments of Atmospheric Sciences and Applied Mathematics):

Big Data meets Big Models: Weather Forecasting and Climate Modeling’

Big models and big data have long been a fixture of weather and climate modeling.  Computer-generated global weather forecasts are initialized from millions of diverse observations from satellites,  weather balloons, surface weather stations, ships and buoys.  As we will describe, data assimilation,  the process of optimally blending these observations into the forecast model, is the most computationally challenging aspect of making a global forecast, and is a critical element of forecast  skill.  Climate models are like weather forecast models, but run out tens to thousands of years with  fuller treatment of earth system processes like ice, biology, and chemistry, generating enormous  archives of model output.  The international climate modeling community has evolved interesting  infrastructure and social institutions that enable a diverse community of interested users to obtain  standardized results from leading climate models developed around the world, to capture aspects of  climate modeling certainty and uncertainty and help inform decision-makers and the interested public.

Biography:

Chris Bretherton is an atmospheric scientist who studies cloud formation and turbulence and improves  how they are simulated in global climate and weather forecast models. His research includes  participating in field experiments and observational analyses, three-dimensional modeling of fluid  flow in and around fields of clouds, and understanding how clouds will respond to and feed back on  climate change. Computer code developed by his research group for simulating cloud formation by  atmospheric turbulence is used in the two leading US climate models. He was a lead author of the  Intergovernmental Panel on Climate Change Fifth Assessment Report in 2013, Chair of a 2012 National Academy report entitled A National Strategy for Advancing Climate Modeling, and a former director of  the University of Washington Program on Climate Change. In 2012, he received the Jule G. Charney  Award, one of the two highest career awards of the American Meteorological Society.

Please join the eScience Institute on Wednesday, February 5th at 4:30 pm in the Gates Commons (CSE 691).   Refreshments will be provided.    PLEASE NOTE NEW SEMINAR LOCATION.

 Joseph L. Hellerstein (Google):

Lessons Learned from Teaching Biochemistry to Computer Scientists

In the Fall of 2013, I taught an introductory course on biochemistry as a CSE 599 class. My objective was to help CS students and faculty acquire knowledge that will allow them to operate as peers with researchers in the life sciences. The course focused on proteins, enzymes, and a molecular understanding of the “central dogma” of biology – replication, transcription, and translation.  

At first glance, biochemistry seems far afield from computer science, especially for students with no recent background in chemistry (and who have never taken organic chemistry, the standard pre-requisite for biochemistry). However, I discovered that much of biochemical knowledge involves concepts and tools that are an integral part of computer science. 

First, a lot of the difficulty with learning biochemistry is that it deals with complex structures such as large molecules, cells, and organs. It turns out that tools such as the Unified Modeling Language (UML) are extremely effective for representing complex biochemical structures. Indeed, my class often had great discussions about the design of UML structures for proteins and metabolites; these discussions were an excellent vehicle for understanding concepts in biochemistry.

A second impediment to learning biochemistry, in my opinion, is that it is taught with an impoverished discussion of the computational problems being addressed by life processes. One example of this is cellular pathways. These are workflows. But I have never seen biochemists use the rich representations and tools of computer science in their discussion of pathways. Another example of computational problems solved by life processes is cellular transport of molecules, such as the transport of secretory proteins. Much of the complexity here is about the way addressing and routing works, something that is fairly digestible to a mature computer science student.

This lecture will discuss the pedagogy that worked well, what didn’t work, and how I plan to radically restructure the class when I teach it in Spring quarter.

Bio

Joseph Hellerstein is an Engineering Manager at Google, Seattle and a Senior Data Science Fellow with eSciences at the University of Washington. 

Upcoming Seminars:

* February 12, 4:30 PM (CSE 691)

 Joel Zylberberg  (UW Applied Mathematics)

Computational Neuroscience: from the top-down, the bottom-up and everything in between

* February 19, 4:30 PM (CSE 691)

Steven Roberts  (UW Aquatic & Fishery Sciences)

TBD

* March 5, 4:30 PM (CSE 691)

Chris Bretherton  (UW Atmospheric Science and Applied Mathematics)

Big Data meets Big Models: Weather Forecasting and Climate Modeling

Nat Guy

5-year Nintendo Employee

UW CSE PMP Student

Aero/Astro Student

CSE 403 TA

Software Development

in the Gaming Industry

Thursday, Oct. 31, 2013

9:30 – 10:20am

EEB 105

Nat draws on his work experience at Nintendo and

the advice of friends in the industry to present a

glimpse of software development in a specialized

application domain, the gaming industry. This talk

covers project roles, engineering specializations,

and common tools and languages used during the

development process taking a game from idea to

finished product. He also discusses career paths

and major players including Seattle-based

companies.

Everyone is welcome to attend.