Meet A Data Scientist-Yelena Yesha

In her IDSC roles, Dr. Yesha assists faculty in engaging government and industrial partners to collaborate with the University, and consults faculty on developing research ideas into innovations.

Dr. Yesha is also a tenured Distinguished University Professor at the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County, and, she is the Director of the National Science Foundation Center for Accelerated Real Time Analytics (CARTA). She received her B.Sc. degrees in Computer Science and in Applied Mathematics from York University, Toronto, Canada, in 1984, and her M.Sc. degree and Ph.D. degree in Computer Science from The Ohio State University in 1986 and 1989, respectively.

Dr. Yesha has published 11 books as author or editor, and more than 200 papers in prestigious refereed journals and refereed conference proceedings, and she has been awarded external funding in a total amount exceeding 40 million dollars. She is currently working with leading industrial companies and government agencies on new innovative technology in the areas of cybersecurity and big data analytics with applications to electronic commerce, climate change, and health. Dr. Yesha is a fellow of the IBM Centre for Advanced Studies.

Forbes magazine looked at Dr. Yesha’s accomplishments in technology in a two-part profile:  Part I: Dr. Yelena Yesha: Meet The Tenacious Pioneer Pushing Innovation To Address Real World Problems and Part II: Dr. Yelena Yesha: Pushing Technology Boundaries To Solve The World’s Biggest Problems.

 

Past Sessions:

>YELENA YESHA 1/27/2021  Click for Video and Summary. TALK TITLE: “Data Science:  A Paradigm of Actionable Knowledge” 

 

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>KEN GOODMAN 1/14/2021  Click for Video and Summary. TALK TITLE: “Data Science + Ethics – UM’s Role in the New Research” 

 

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>TIM NORRIS 12/9/2020 TALK TITLE:  “Data Science + Ethics – UM’s Role in the New Research”

Opening with a parallel to the writings of Enlightenment-era thinker John Locke on the changes in property and governance and shift to capitalism at that time as it relates to data science in making today’s world a better place, self-described “bit pusher” Tim Norris shared his fascinating journey into a career as an “embedded data curator.”

 

Tim is passionate about making data more useful, sharing it, and not storing it away; It’s important that we curate the data and tell stories with it. In this commonly used DIKW pyramid representation, the base layer “the World” was missing—he added it—as it helps to illustrate his objection to the term “information ecosystem” because that takes away “the world”. He was taught Statistics by a Buddhist monk who emphasized that your interpretation of the data is what counts the most.

 

In this vein, he offered this quote:

Tim’s fascinating career in mapmaking data evolved as did the technology used. He learned that the data doesn’t tell the story. Humans tell the story. “It takes a certain amount of understanding of data to manipulate it and communicate the results.”  The current global governance tendency toward open data is great but there are still many obstacles to data sharing.

The Q and A touched on the “So what?!” of working with data and who benefits from data extracted from us as we go about our lives. Data is a public good, but who should pay for the costs of gathering and processing it? A data tax maybe?

• Tim recommended everyone watch The Social Dilemma (currently on Netflix).
• He also noted that Wall Street’s Standard & Poor’s is now the “world’s largest, global resource for index-based concepts, data, and research.”

Click here for Tim’s full Powerpoint presentation (use arrow keys to navigate).  Here is his github profile.

 

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>BEN KIRTMAN 11/18/2020

The second talk featured Dr. Ben Kirtman, a Professor of Atmospheric Sciences at the University of Miami Rosenstiel School of Marine and Atmospheric Science. Dr. Kirtman uses atmosphere-ocean general circulation models to study the predictability and variability of the Earth’s climate system. Dr. Kirtman also teaches graduate courses on the general circulation of the atmosphere and El Niño/Southern Oscillation, and climate prediction and predictability. Originally from Santa Barbara, California, Dr. Kirtman shared a funny story about his early start with computers and his (harmless) hacking efforts that got also his [also brilliant] Dad in a little ‘hot water’.  Relating subsequently having to monitor flooding in his basement (related to El Niño) as a punishment, he’s come a long way! He’s understandably proud of the fact that the University of Miami has been the lead in the multi-agency, multi-institutional effort to improve NOAA’s seasonal and sub-seasonal operative forecasts since 2015.  His NMME (North-American Multi-Model Ensemble, on the chart below in light pink NCAR_CCSM4) forecasting system consists of coupled models from US modeling centers including NOAA/NCEP, NOAA/GFDL, IRI, NCAR, NASA, and from Canada’s modeling center. It has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation, and has proven to produce better prediction quality (on average) than any single model ensemble.

The talk went from touching on the disparate data sources that go into forecasting El Niño and La Niña, to using machine learning to capture the Gulfstream’s interactions with the atmosphere (parameterization/parametrization), and ended with questions from the audience on the future of machine learning in climate prediction.

Dr, Kirtman concluded with emphasizing that “What question are you trying to solve?” should drive what data/methods you use. He conveyed that new climate model(s) will be a blend with machine learning, which may lead to breakthroughs on how models work.

Dr. Kirtman also teaches dynamic meteorology and atmospheric thermodynamics to undergraduates, and he mentors graduate students in the Meteorology and Physical Oceanography graduate program, as well as post-doctoral researchers.

His research is a wide-ranging program designed to understand and quantify the limits of climate predictability from days to decades. His research also involves understanding how the climate will change in response to changes in anthropogenic (e.g., greenhouse gases) and natural (e.g., volcanoes) forcing. This research involves hypothesis testing numerical experiments, using sophisticated state-of-the-art climate models and experimental realtime prediction. His group uses and has access to a suite of climate models, climate data, and high performance computational platforms.

 

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>ALBERTO CAIRO 11/4/2020

(Read the post-series-launch story here.)

The first talk featured Dr. Cairo, director of IDSC Visualization, Data Communication, and Information Design; the Knight Chair in Visual Journalism; and an assistant professor in the Department of Journalism and Media Management and the Department of Interactive Media.  Dr. Cairo has an extensive career in the news industry and has consulted with media organizations and educational institutions in more than 30 countries. He currently works as a consultant for Google and the Congressional Budget Office. Microsoft has called Dr. Cairo a pioneer who’s always been “at the vanguard of visual journalism.”  He is the author of the several books, including:

• How Charts Lie: Getting Smarter About Visual Information (W. W. Norton 2019)
• The Functional Art: An Introduction to Information Graphics and Visualization (Peachpit Press/Pearson Education 2012), and
• The Truthful Art: Data, Charts, and Maps for Communication (Peachpit Press/Pearson Education 2016).

He has also written popular articles for numerous publications, such as The New York Times and Scientific American. In 2019, he was named an honorary member of the International Statistical Institute.

In his 11/4 presentation, Dr. Cairo shared the following tips/tools:

• Mike Monteiro’s book “Ruined by Design” (Listen to Mike Monteiro’s speech “The Smallest Sliver of Hope” from the IDSC-hosted Data Intersections 2020 on our YouTube channel.)
• https://twotone.io A tool to create sound from data: open source, free, works on the browser
• https://colorbrewer2.org to make sure visualization can be read by color-blind viewers
• TOOLS he likes for #communicatingdata
  • https://www.datawrapper.de/
  • https://flourish.studio/
  • https://www.adobe.com/products/illustrator.html
  • https://www.tidyverse.org/
• TOOLS he likes for #exploringdata
  • https://www.r-project.org/about.html
  • https://www.python.org/
  • https://www.tableau.com/trial/tableau-software
  • https://powerbi.microsoft.com/en-us/
• TOOLS he likes for #mappingdata
  • Commercial  https://www.arcgis.com/index.html
  • Free https://qgis.org/en/site/