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Data Science Ambassadors Program highlighted during 2020 Academic Data Science Summit & Annual Meeting

The Data Science Ambassadors program was highlighted to an international audience during a lightning talk at the 2020 Academic Data Science Alliance Summit and Annual Meeting presented by Jeff Oliver entitled Data Science Support through Graduate Fellowship Programs.
Data Science Institute Supports UA Grad Research
Ariyan Zarei processes and analyzes aerial and ground images of crops in order to estimate their different agricultural phenotypes. Marina Kisley infers patterns from astronomical data to enhance our understanding of the universe. And Artin Majdi helps efforts to detect valley fever by exploring chest X-ray images via deep learning, a subset of machine learning, and introduces a non-invasive method for measuring Skin Conductance Response (SCR), a phenomenon that can reveal emotion.
Learn more about these projects
Machine Learning Literacy Workshop held Feb 8, 2020

The Machine Learning Literacy Project (MLLP) was a one-day workshop held in ENR2 at the University of Arizona on Saturday February 8, 2020. The workshop came about to address the serious need of preparing students for the modern Machine Learning-literate workforce. Due to the amazing things that can now be done using ML, the demand for its use in every discipline from Science and Engineering, to Law, to the Humanities, exceeds the current workforce capacity.
The MLLP workshop was designed to meet this demand by accomplishing the following outcomes for its undergraduate and graduate student attendees: students
· Learned basic ML concepts through high-level talks from research experts at UArizona
· Learned how ML is being applied and has advanced research in their domain
· Gained experience in working collaboratively in inter- and multidisciplinary teams
· Researched, prepared and delivered short presentations on their findings to a diverse audience
· Learned about other opportunities at UArizona for data science learning and applications
There were over 80 participants from 25 majors at the event in addition to over 20 volunteers and 3 speakers. Students learned about and presented on topics ranging from ML-assisted surgery to ML usage in Linguistics and Education.
Workshop schedule and information: https://sites.google.com/view/mlhackathontest/home
Data Science at UA: Open House

Updates from Data7, TRIPODS, and CyVerse
The Latest Opportunities in Data Science

Learn how a UA Data Science Ambassador can help your College with Data Science Literacy!
Read about Google's PhD Fellowship Program
First and Second Cohorts of Data Science Ambassadors

All Colleges were invited to nominate 2019-2020 Data Science Ambassadors. Deadline June 1, 2019.
2018-2019 Data Science Ambassadors: Champions for Data Science Literacy
--Kristy Makansi, RDI Communications
From astronomy to zoology, researchers use data to better understand their subject areas, develop and test hypotheses, and make new discoveries. But not every researcher is a data science expert. That’s where the Data Science Ambassadors come in.
Data Science Ambassadors (DSAs) are graduate students with the requisite knowledge and expertise to help researchers in their respective colleges develop data science skills. With a $1,000 stipend for an academic year commitment, DSAs receive training and support as they work to help others in their subject areas tap into the potential of data science.
Under the direction of Jeffrey Oliver and Vignesh Subbian, the DSA program is currently supported by and offered in the Colleges of Agriculture & Life Sciences, Engineering, Science, and Social & Behavioral Sciences.
Brian Maitner, a DSA in the College of Science, is a PhD student in Ecology & Evolutionary Biology who studies the processes that generate and maintain biodiversity at a global scale. Data science is critical to his field because “a single person can’t possibly collect the type of data needed to address the questions I’m interested in. Data science is needed to cobble together enough data in a useful way to address global questions.”
As an ambassador, Brian has provided coding help, particularly emphasizing Open Source solutions, and is running a weekly NetLogo workshop. Additionally, he’s working with the Introductory Biology Lab Director, Ryan Ruboyianes, to develop simulations that students can run on their own computers and smart phones and that help clarify some of the important ideas presented during lab.
A phenoclimatologist in the School of Natural Resources and Environment and the Laboratory of Tree-Ring Research, Amy Hudson is a DSA in the College of Agriculture and Life Sciences. As part of her DSA work, she and another ambassador, Jiali Han, have been instrumental in helping organize the first Women in Data Science – Tucson event. Hudson is grateful to the role other researchers have played in helping her learn to code and to “untangle an analysis.” Being an ambassador, she says, is a way to “pay these actions of mentorship forward in a more structured framework.”
Since becoming an ambassador, Hudson has been an instructor for two Data Software Carpentry workshops, including one titled Geospatial Lessons in R. When she arrived at the classroom on the first day, she saw that six of the 30 learners were fellow students in her department. She jumped in and approached the course as a cohort event. “We were laughing and groaning over learning this new skill together. Everyone was supporting each other, and it really made me proud and happy to be there to help out.”
For Joseph Long, whose work focuses on high-contrast astronomical imaging in the search for exoplanets, data science is one of the tools that makes his work possible.
“Data science is an umbrella term for a set of computational and statistical techniques, combined with the infrastructure for applying them to large data sets,” Long says when asked to describe data science. And Long certainly works with large data sets. His current project involves applying dimensionality reduction techniques to sequences of tens of thousands of images of a single star to model patterns of starlight and then subtract those patterns in the hopes of revealing a planet in the star’s orbit.
One of the ways Long is helping others leverage the power of data science in their own work is to get people out of their offices to share challenges, lessons learned, and insights gained.
“In addition to organizing a monthly talk/tutorial series on computing topics that is open to the whole university community, I set up a Slack channel to facilitate sharing questions and fostering discussion within our graduate student Slack organization.”
For Maitner, Hudson, and Long, participating in the DSA program is an effective way to spread the word about data science while also enhancing their understanding of the tools that enable their own work. Other DSAs include Jiali Han (College of Engineering), Xiang Liu (College of Agriculture & Life Sciences), Don Merson (College of Social and Behavioral Sciences), Matt Miller (College of Science), and Cristian Román-Palacios (College of Science).
If you would like to work with a DSA, submit a request at datascience@email.arizona.edu. If you would like your college to get involved in the DSA program, please contact one of the program directors for information.
Data Science Fellow has a Hand in the First Image of a Black Hole

Data7 has a hat off to CK Chan, our Data Science Fellow who leads the Computations and Software Working Group for the Event Horizon Telescope project. This worldwide effort helps astronomers study objects predicted by Einstein's theory of General Relativity. You can read more HERE: https://eventhorizontelescope.org/
UA Center for Innovation in Brain Science awarded a $1.8 million NIH grant

Read the exciting news about the Center for Innovation in Brain Science!
Women in Data Science Tucson Regional Event


The Women in Data Science (WiDS) initiative aims to inspire and educate data scientists worldwide, regardless of gender, and support women in the field. WiDS started as a conference at Stanford in November 2015. Now, WiDS includes a global conference, with 150+ regional events worldwide; a datathon, encouraging participants to hone their skills; and a podcast, featuring leaders in the field talking about their work, and their journeys. On Friday, April 5th, 2019 WiDS-Tucson was held in the ENR2 building room S-107 from 8:30am-4:00pm, with a Happy Hour following.
WiDS-Tucson 2019 was amazing! Over 100 people attended and enjoyed a day of learning about Data Science efforts in many fields, with a lot of networking to share ideas. A very big Thank You to our Speakers, Data Blitz, and/or a poster presenters. All presenters did an excellent job and many positive comments were heard throughout the day. If you missed some of the sessions, here are links to recordings:
Aspinall Keynote, Kennedy, Zhang
Prof Dev Panel, AM DataBlitz Talks
PM DataBlitz, Borens Keynote, Hurwitz, Ida, Inspiration Panel
LaFleur, Riemer PM Concurrent Session
Look for our next WiDS-Tucson in the spring of 2020! To receive updates, subscribe to the WiDS-Tucson email list here: http://eepurl.com/gnSmOD
You can Follow @TucsonWids on Twitter and "Like" our Facebook page: https://www.facebook.com/Wids-tucson-371018400385649/
If you're interested in joining the WiDS-Tucson planning committee, join our listserv: https://list.arizona.edu/sympa/info/wids-tucson/
Check out the carousel of photos from WiDS-Tucson 2019 below:
Pilot Project: Using NLP and ML to help Cancer Survivors

Participants are paired with a telephone-based health coach who encourages them to exercise and to eat a healthy diet, through regularly scheduled phone conversations. The LIVES study has garnered over 10,000 hours of such exchanges. Can Data Science techniques help predict outcomes of these interventions based on sentiment analysis of these conversations? Can we find better ways to coach individuals that would increase likelihoods of successful behavior modification?


This project will provide foundational tools and techniques to process audio streams in near real time, providing assessments of conversations, with novel strategies that can be employed in other health intervention studies. Drs. Crane and Jansen will be utilizing outcomes of this endeavor to apply for an NIH Director’s New Innovator Award (DP2) in 2019.