Translational Data Analytics
@ Ohio State Fall Forum
October 8, 2015 2 – 5:30 p.m. Thompson Library Campus Reading Room
2:05 – 2:20 p.m.
Opening Comments
Philip Payne, PhD, FACMI
The Ohio State University
2:20 – 3 p.m.
Data Science: Machine Learning
for the Real World
Tony Jebara, PhD
Columbia University
3:05 – 3:25 p.m.
Advancing Population Health
Through TDA@OhioState
Randi Foraker, PhD
The Ohio State University
3:30 – 4:10 p.m.
Hierarchical Materials Informatics
Surya Kalidindi, PhD
Georgia Institute of Technology
TDA@OhioState
4:15 – 4:35 p.m.
Computationally Efficient GenomeScale Evolutionary Inference:
Creating a Sustainable Future for
African Smallholder Farmers
Laura Kubatko, PhD
The Ohio State University
4:40 – 5:20 p.m.
From Analysis to Presentation
Robert Kosara, PhD
Tableau Software
5:25 – 5:30 p.m.
Closing Comments
David Manderscheid, PhD
The Ohio State University
5:30 – 7 p.m.
Reception
discovery.osu.edu/TDA
A DISCOVERY THEMES INITIATIVE
Philip Payne, PhD, FACMI
Director, Translational Data Analytics @ Ohio State
Professor and Chair, Department of Biomedical Informatics,
College of Medicine
Associate Director for Data Sciences,
Center for Clinical and Translational Science
The Ohio State University
go.osu.edu/payne
Opening Comments
Tony Jebara, PhD
Associate Professor, Computer Science
Columbia University
go.osu.edu/jebara
Data Science: Machine Learning for the Real World
Columbia University launched the Data Science Institute (DSI) in early 2012 to
develop technologies that unlock the power of global data to help solve some
of society’s most challenging problems. Today, it spans well over 100 faculty
members. The institute is home to six centers that foster interdisciplinary collaboration and serve as engines
of translational research and education in the data sciences. The centers include Health Informatics,
Cybersecurity, Financial Analytics, Smart Cities, New Media, and Foundations of Data Science. The DSI
was founded through a grant from the City of New York and is now also supported by federal funding and
philanthropic foundations as well as an industrial affiliates program. It offers undergraduate, master’s, and
professional degrees in data science and has a thriving entrepreneurship program for seeding startup
companies. I will discuss some of the collaborations that have emerged across the university campus thanks
to the DSI. In particular, I will focus on a number of vignettes detailing our work in leveraging data science,
machine learning, and graphical modeling to analyze financial markets, news streams, neuronal data,
power-grids, image data, and social media.
Randi Foraker, PhD
Assistant Professor
Department of Epidemiology, College of Public Health
Department of Biomedical Informatics, College of Medicine
The Ohio State University
go.osu.edu/foraker
Advancing Population Health Through TDA@OhioState
Improving population health remains a complex challenge. The Ohio State
University is uniquely positioned to find solutions to the environmental, social, biological, and clinical
barriers to wellness. Translational Data Analytics @ Ohio State operates in a culture of collaboration, with
growing faculty expertise in relevant areas, and with the ability to build and strengthen existing external
partnerships. In this talk, I will present SPHERE, an interactive health visualization tool, as an example of
innovation which grew out of the data analytics tradition at Ohio State. I will discuss aspects of SPHERE that
are complementary to TDA members’ expertise, and suggest future directions and opportunities for new
and existing faculty to advance population health.
Surya Kalidindi, PhD
Professor, George W. Woodruff School of Mechanical Engineering
Georgia Institute of Technology
go.osu.edu/kalidindi
Hierarchical Materials Informatics
Hierarchical materials informatics focuses on the development of data science
algorithms and computationally efficient protocols capable of mining the essential
linkages in large multiscale materials datasets (both experimental and modeling),
and building robust knowledge systems that can be readily accessed, searched, and shared by the broader
community. Given the nature of the challenges faced in the design and manufacture of new advanced
materials, this new emerging interdisciplinary field is ideally positioned to produce a major transformation in
the current practices. The novel data science tools produced by this emerging field promise to significantly
accelerate the design and development of new advanced materials through their increased efficacy in
gleaning and blending the disparate knowledge and insights hidden in data accumulated from multiple
sources (including both experiments and simulations). I will discuss ongoing research about a specific
strategy for data science-enabled development of new/improved materials and illustrate key components of
the proposed overall framework with examples.
Laura Kubatko, PhD
Professor
Department of Statistics
Department of Evolution, Ecology, and Organismal Biology
College of Arts and Sciences
The Ohio State University
go.osu.edu/kubatko
Computationally Efficient Genome-Scale Evolutionary Inference:
Creating a Sustainable Future for African Smallholder Farmers
More than 700 million people globally rely on cassava as a primary food source, including smallerholder
farmers in several countries in East Africa. However, East African cassava is under severe threat from the
whitefly (Bemisi tabaci), a small insect that carries two viruses that infect cassava plants. Together, these
viruses can result in nearly 100% crop loss, with an estimated cost of $1.25 billion USD annually. Crucial
questions in the development of tools to combat the whitefly are how many species of whitefly actually
exist, and how diverse genetically these species might be. In this talk, I will describe my contributions
toward answering these questions as part of the Cassava Whitefly Project funded by the Bill and Melinda
Gates Foundation. In particular, I will show how genome-scale data can be efficiently summarized in a
manner that leads to accurate inference of evolutionary relationships among species with low computational
cost. This methodology will enable an improved understanding of whitefly genomics that can be translated
into new approaches to establishing cassava as a sustainable food source in East Africa.
Robert Kosara, PhD
Research Scientist
Tableau Software
go.osu.edu/kosara
From Analysis to Presentation
The academic visualization field focuses on analysis, often overlooking the
presentation and communication of data. While this is slowly changing, a lot
more needs to be done: we need to understand how people use visualization to
get points across, we need to understand the goals and intents, and we need to develop ways of measuring
success. Greater understanding will contribute to generating the solutions to real world problems that
Translational Data Analytics @ Ohio State is pursuing, such as promoting healthy communities and feeding
the global population. In this talk, I will make the case for more focus on the presentation of data using
visualization, and show some work that is pointing in the right direction.
David Manderscheid, PhD
Lead Dean, Translational Data Analytics @ Ohio State
Executive Dean and Vice Provost, College of Arts and Sciences
The Ohio State University
go.osu.edu/deanmanderscheid
Closing Comments
TDA@OhioState:
Making data work for you.
Contact
Philip Payne, PhD
Director
614-292-4778
payne.341@osu.edu
David Mongeau, MBA
Program Manager
614-292-1282
mongeau.1@osu.edu
discovery.osu.edu/TDA