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Code Freeze 2019: Machine Learning

Date of Event: 
Wednesday, January 16, 2019 - 8:30am to 5:00pm
Location: 
McNamara Alumni Center
Venue information

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Registration for Code Freeze 2019 is now closed.


The University of Minnesota's Software Engineering Center and DevJam bring you the 14th annual Code Freeze symposium. This year's program chairs are Stephen Taylor of DevJam and Sanjai Rayadurgam from the University of Minnesota. The program promises to make for another exciting day.

This year, our theme is Machine Learning.

Machine learning is becoming ubiquitous in software-controlled systems. A variety of techniques enable such systems to learn complex patterns, mimic sophisticated behaviors, and exhibit superior skills to address challenging tasks in a variety of application domains. The increasing use of ML also brings into focus questions related to reliability, robustness, trust, safety, and ethics. In this event we will examine how these algorithms work, when they might fail and how we might deal with the consequences, and what new domains and opportunities do these techniques open up for software applications. We will hear from leading researchers and engineers who have used ML "in the trenches".

We are delighted to have three excellent keynote speakers this year:

Scott Ernst, Director of Data Science and Engineering at When I Work
Scott is currently the Director of Data Science & Data Engineering at When I Work, a Minneapolis-based startup. He has a Ph.D. in computational physics that focused on large-scale astrophysical and magnetohydrodynamic plasma simulations. Over the last decade Scott has worked in various data science, visualization, engineering and architecture roles. These include leading the data science team for an international research project modeling dinosaur behavior on the world’s largest dinosaur track-site and creating 3D digital visualizations for clients all over the world such as National Geographic, National Public Radio (NPR), Carnegie Natural History Museum, Los Angeles Natural History Museum, Asahi Shimbun (朝日新聞), Tokyo Natural History Museum and Jurassica in Switzerland. Scott is also the creator of Cauldron, a data science notebook that expands notebook-based computing beyond interactive usage for production applications.
Sarah Aerni, Director of Data Science at Salesforce Einstein
Sarah Aerni is a Director of Data Science at Salesforce Einstein where she leads teams building AI-powered applications across the Salesforce platform. Prior to Salesforce she led the healthcare and life science and federal teams at Pivotal. She co-founded a company offering expert services in informatics to both academia and industry. She holds a Ph.D. in Biomedical Informatics from Stanford University where she focused on research at the interface of machine learning and the biology of cancer, aging, and development.
Tim Menzies, Professor of Computer Science at North Carolina State University
Tim Menzies (IEEE Fellow, Ph.D., UNSW, 1995) is a full Professor in CS at North Carolina State University where he teaches software engineering, automated software engineering, and foundations of software science. He is the directory of the RAISE lab (real world AI for SE) that explores SE, data mining, AI, search-based SE, and open access science. He is the author of over 250 referred publications and editor of three recent books summarized the state of the art in software analytics. In his career, he has been a lead researcher on projects for NSF, NIJ, DoD, NASA, USDA, as well as joint research work with private companies. For 2002 to 2004, he was the software engineering research chair at NASA's software Independent Verification and Validation Facility. Prof. Menzies is the co-founder of the PROMISE conference series devoted to reproducible experiments in software engineering (http://tiny.cc/seacraft). He is an associate editor of IEEE Transactions on Software Engineering, ACM Transactions on Software Engineering Methodologies, Empirical Software Engineering, the Automated Software Engineering Journal the Big Data Journal, Information Software Technology, IEEE Software, and the Software Quality Journal. In 2015, he served as co-chair for the ICSE'15 NIER track. He has served as co-general chair of ICSME'16 and co-PC-chair of SSBSE'17, and ASE'12.

Conference sessions will take many forms: presentation, demonstration, and hands-on. We will have breakout sessions from experts describing how they use Machine Learning and AI systems in their domains, what works and what doesn't.

Registration: Cost for the full day is $120 for the general public and $90 for alumni of the Software Engineering (MSSE) and Computer Science (CS) programs.
Parking: Parking is not included in registration fee. The University Ramp, located on University Avenue next to McNamara Alumni Center, charges $12 normal daily rate. Here is an overview map of various parking options on the East Bank. (the venue is opposite the southwest corner of TCF Bank Stadium).
Anti-Harassment Policy: Code Freeze is dedicated to a harassment-free conference experience for everyone. Our anti-harassment policy can be found here.

Registration for Code Freeze 2019 is now closed.

SCHEDULE:

Check-in 8:30 - 9:00 Registration & Breakfast
Welcome 9:00 - 9:15 DevJam and UMN
Scott Ernst 9:15 - 10:15 Essentials of Effective Machine Learning
AM Break 10:15 - 10:30
Sarah Aerni 10:30 - 11:30 Achieving Salesforce-Scale Machine Learning in Production
AM Breakouts 11:40 - 12:40
Morning Breakout Sessions
Topic Speaker
Safely Driven: How Trimble is Applying Deep Learning and Pragmatic Practices to Help Make the Roads Safer for Everyone
(Johnson Great Room)
Miles Porter and Jordan Burandt
Fair AI in Practice
(Heritage Gallery)
Rachel Bellamy, Ph.D.
Your Laptop isn't Production: Engineering your ML Models into Production
(Swain Room)
Donald Sawyer and Chris Klaue
Augmenting Reality at Law Firms
(Ski-U-Mah)
Jennifer Roberts
The Real World Application of ML to Cybersecurity
(Memorial Hall)
Tim Crothers
Lunch 12:40-1:40 D'Amico catering
PM Breakouts 1:40 - 2:40
Afternoon Breakout Sessions
Topic Speaker
Unsupervised AI: When AI Stops Copying and Starts Partnering with People
(Johnson Great Room)
Noah Horton
Fair AI in Practice
(Heritage Gallery)
Rachel Bellamy, Ph.D.
Exploring the Structure of Data at Scale
(Swain Room)
Rudy Agovic, Ph.D.
New Trends in Silicon and Hardware - Changes Driven by a New Compute Paradigm
(Ski-U-Mah)
Sarosh Irani
Building an End-to-End Data Science Practice in an Agile Framework
(Memorial Hall)
Susan Van Riper, Ph.D.
Tim Menzies 2:45 - 3:45 SE for AI for SE
PM Break 3:45 - 4:00
John Carlis and David Hussman Memorial Open Sessions 4:00 - 4:45 Breakout sessions using the "fish-bowl" format where speakers and participants can think and deliberate on the day's topics. In a fish-bowl all participants can take the stage and propose and respond to topics.
Closing Remarks 4:45 - 5:00 UMN and DevJam
Reception5:00 - 6:00Post-conference social

Thank you to Code Freeze 2019 Sponsors!

Platinum Sponsor:

Gold Sponsors:

SoleraIdentifix logo

Target logo

InfiniteCampus logo

Titan Data logo

Silver Sponsors:

Best Buy logo