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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

Interested in being a sponsor for the event? Please contact Molly Bendzick.

REGISTER here for Code Freeze 2019!


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.
Bonnie Holub, Principal Data Scientist and Director of Data Sciences at Teradata
Bonnie Holub, Ph.D. has spent her career correlating disparate sets of big data for actionable results. She leads Data Science in the Midwest GEO as Teradata Consulting’s Principal Data Scientist. Bonnie holds a Ph.D. in Artificial Intelligence and has served a variety of roles including: VP Talent Analytics at Korn Ferry, Master Data Scientist at Cognizant, Analytics Director at PwC, and Enterprise Data Warehouse Program Manager at UCare Health Insurance. She has been an entrepreneur founding several companies, the most successful of which is Adventium Labs, an AI and secure software research organization based in Minneapolis, MN. She has taught at the graduate level and been involved with the founding of several successful Big Data, Data Science, and AI programs at several universities. She is a regular lecturer at Carnegie Mellon University and other flagship AI institutions. She has served on boards of directors for various institutions including the Minnesota High Tech Association, the St. Paul Area Chamber of Commerce, Dodge Nature Center, the Graduate Programs in Software at the University of St. Thomas, High Tech Kids, and Ever-Green Energy.
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.

REGISTER here for Code Freeze 2019

SCHEDULE:

Check-in 8:30 - 9:00 Registration & Breakfast
Welcome 9:00 - 9:15 DevJam and UMN
Bonnie Holub 9:15 - 10:15 Machine Learning and Artificial Intelligence - A Magic Moment?
AM Break 10:15 - 10:30
Tim Menzies 10:30 - 11:30 SE for AI for SE
AM Breakouts 11:40 - 12:40 Continue to check back for more breakout session information!
Breakout Sessions
Topic Speaker
Your Laptop isn't Production: Engineering your ML Models into Production Donald Sawyer and Chris Klaue
Safely Driven: How Trimble is Applying Deep Learning and Pragmatic Practices to Help Make the Roads Safer for Everyone Miles Porter and Jordan Burandt
Exploring the Structure of Data at Scale Rudy Agovic
The Real World Application of ML to Cybersecurity Tim Crothers
Augmenting Reality at Law Firms Jennifer Roberts
New Trends in Silicon and Hardware - Changes Driven by a New Compute Paradigm Sarosh Irani
Building an End-to-End Data Science Practice in an Agile Framework Susan Van Riper, Ph.D.
Lunch 12:40-1:40
PM Breakouts 1:40 - 2:40
Scott Ernst 2:45 - 3:45 Elements of Effective Machine Learning
PM Break 3:45 - 4:00
Deep Dives 4:00 - 4:45 Breakout sessions where you, the audience, and the speakers can think and deliberate on the day's topics. More details to come!
Closing Remarks 4:45 - 5:00 UMN and DevJam
Reception5:00 - 6:00Post-conference social

Thank you to Code Freeze 2019 Sponsors!

Interested in being a Sponsor? Please contact Molly Bendzick

Platinum Sponsor:

Gold Sponsors:

SoleraIdentifix logo

Target logo

InfiniteCampus logo

Titan Data logo

Silver Sponsors:

Best Buy logo