2020-Data-Science-Program

KEN KENNEDY INSTITUTE

DATA SCIENCE CONFERENCE

Rice 2020 | Data Science Conference Oct. 26-28, 2020 Virtual Conference Houston, Texas dsconference.rice.edu

kenkennedy.rice.edu k2i.rice.edu

MESSAGE FROM THE CHAIR

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elcome to the 4th annual Ken Kennedy Institute Data Science Conference at Rice University. COVID-19 has forced us to hold the conference virtually this year. This has presented many challenges, but it is also an amazing opportunity to invite broad participation for what promises to be an exciting few days of talks, posters, and discussions from Data Science. The theme

of the conference has also been shaped by COVID-19. This year’s virtual conference will explore how the pandemic has influenced the use of data as well as the development and application of data science. Speakers will discuss everything from the genome analysis to data governance, from human behavior to water treatment plants, and will highlight the role of computing hardware and software in these endeavors.

For the past four years, the annual conference has been interested in exposing how data science can be used to address interesting challenges for translating data to knowledge through advances in data engineering, analytics, machine learning, deep learning, reinforcement learning, and more broadly, artificial intelligence.

The conference features talks by leading experts, which will be complemented by thematically organized sessions with talks selected from submitted abstracts in four tracks: • COVID-19 • Algorithms & Foundations • Business Impact • Healthcare This year the conference was expanded to include a special collaboration with MD Anderson that takes place on Wednesday and will offer a discussion about the Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE), which was established to create a cross-functional, institution-wide data science initiative linked to understand cancer in context of the pandemic.

On Tuesday afternoon there will be a poster session, a unique conference component that enables presenters and participants to engage more deeply around topics, as well as explore partnerships and employment opportunities.

The three-day conference offers opportunities to engage during networking breaks and the sponsor networking session on Monday afternoon. Recognizing that discovery and innovation happens at interfaces of disciplines and communities, the conference aims to bring together a diverse set of people from multiple communities spanning academia and industry. In hopes of improving connections in these virtual times, we have implemented a virtual conference platform that prioritizes networking matches based on each attendee’s interests and goals. When viewing matches, attendees can send a meeting request and message to schedule a video chat directly in the platform.

We are grateful to our sponsors, partners, and data scientists, who share our enthusiasm and who seek the opportunity to support and engage with the community. We would like to say a special thank you to our Conference Committee and Special Track Team for their many contributions to this year’s conference at this unusual time.

On behalf of the Data Science Conference Committee and Special Track Team, our fellow constituents and sponsors, Rice University, and the Ken Kennedy Institute Team, we want to thank you for being here. Enjoy the conference.

Angela Wilkins Executive Director, Ken Kennedy Institute

Lydia Kavraki Director, Ken Kennedy Institute

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PROGRAM COMMITTEES Track Chairs David Jaffray, UT MD Anderson Center Roy Keyes, Houston Data Science Group Rodney Samaco, Baylor College of Medicine Eric Venner, Human Genome Center, Baylor College of Medicine Conference Committe Denis Akhiyarov, Total Natalie Berestovsky, Bill.com Keith Cooper, Rice University Licong Cui, UTHealth Scott Ferguson, HEDS Meetup Luca Giancardo, UTHealth Max Grossman, NAG Giewee Hammond, Aramco Services Xiaoqian Jiang, UTHealth Zhandong Liu, Baylor College of Medicine Scott Morton, Rice University Risa Myers, Rice University Jan E. Odegard, The Ion Liliia Reddy, Chevron Craig Rusin, Baylor College of Medicine

Akane Sano, Rice University Santiago Segarra, Rice University Rachel Shaffer, Chevron Julianna Toms, BP Tamas Toth, ExxonMobil Jim Ward, Two Sigma Yan Xu, Houston Machine Learning Meetup Cheng Zhan, Microsoft W. Jim Zheng, UTHealth Special Track Team Gregory Barbosa, UT MD Anderson Center Elizabeth Burton, UT MD Anderson Center Caroline Chung, UT MD Anderson Center Andy Futreal, UT MD Anderson Center Lydia Kavraki, Rice University Mary McGuire, UT MD Anderson Center Sharon Pepper, Rice University Sabitha Prabhakaran, UT MD Anderson Center Stephanie Schmidt, UT MD Anderson Cancer Center Hussein Tawbi, UT MD Anderson Center John Weinstein, UT MD Anderson Center

Data Science Conference Code of Conduct The organizers invite all sponsors, volunteers, speakers, attendees, media, exhibitors and other participants to help us realize a safe and positive virtual conference experience for everyone. The Ken Kennedy Institute works to increase tolerance, opportunity, and diversity in an effort to continually encourage the open exchange of ideas. For these reasons, the Institute is committed to providing a harassmentfree experience at all the events it organizes. If you experience or witness harassment or discriminatory behavior at the conference, report this promptly to kenkennedy@rice.edu.

Audio-recording and/or videotaping and/or photography of any portion of the Ken Kennedy Institute Data Science Conference material is strictly prohibited without prior consent of the conference staff.

All conference participants are required to use their real name and contact information within the conference app.

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D ATA S C I E N C E 2 0 2 0 | M O N D AY, O C T O B E R 2 6 D D3CODE

C Session A: COVID-19

H Session D: Healthcare

K Keynote

A Session B: Algorithms & Foundations

P Poster Session

N Networking

B Session C: Business Impact

Welcome to the Conference Platform

Lydia Kavraki, Rice University, Angela Wilkins, Rice University Pre-recorded

9:15 a.m. – 9:25 a.m.

Session 1: Welcome

9:25 a.m. – 9:50 a.m.

K Session 1: Global Quieting of Anthropogenic, High-Frequency

Reginald DesRoches, Rice University, Angela Wilkins, Rice University

Seismic Noise Due to COVID-19 Pandemic Lockdown Measures

Thomas Lecocq, Royal Observatory of Belgium

9:50 a.m. – 10:15 a.m.

K Session 1: Spatial and Temporal Surveillance of Houston’s

Wastewater to Track Community COVID-19 Infection Dynamics

Lauren Stadler, Rice University

10:15 a.m. – 10:30 a.m.

Break

K Session 2: The Distraction Epidemic 10:30 a.m. – 10:55 a.m.

Ioannis Pavlidis, University of Houston Sponsored by

10:55 a.m. – 11:20 a.m.

K Session 2: Help Me Feel Better: Leveraging Technology for

Better Mental Health

Nidal Moukaddam, Baylor College of Medicine and Ben Taub Hospital Psychiatry Outpatient Clinics

11:20 a.m. – 11:35 a.m.

Break

11:35 a.m. – 12:00 p.m.

K Session 3: How the Internet Will Save Civilization

12:00 p.m. – 1:00 p.m.

N Networking Break & Lunch

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David Eagleman, Center for Science and Law, Stanford University, and Neosensory, Inc.

1:00 p.m. – 1:15 p.m.

C Session 4: Mining SARS-CoV-2 Interhost and Intrahost

Genomic Variation

Nicolae Sapoval, Yunxi Liu, Ryan Anthony, Leo Elworth, Michael Nute, Todd Treangen, Rice University; Fritz Sedlazeck, Baylor College of Medicine

1:15 p.m. – 1:30 p.m.

C Session 4: When and How Airline Bookings Will Return to

Cruising Altitude

Ross Winegar, Amy Bock, Malori Meyer, Michael Wu, Yara Liu, PROS

1:30 p.m. – 1:45 p.m.

A Session 4: AutoGAN-Distiller: Searching to Compress

Generative Adversarial Networks

Yonggan Fu, Haoran Li, Yingyan Lin, Rice University; Wuyang Chen, Haotao Wang, Zhangyang Wang, Texas A&M University

A Session 4: HALO: Hardware-Aware Learning to Optimize

1:45 p.m. – 2:00 p.m.

Chaojian Li, Haoran You, Yingyan Lin, Rice University; Tianlong Chen, Zhangyang Wang, University of Texas at Austin

2:00 p.m. – 2:15 p.m.

A Session 4: Physics-Consistent Data-Driven Waveform Inversion

with Adaptive Data Augmentation

Youzuo Lin, Los Alamos National Laboratory

2:15 p.m. – 2:30 p.m.

A Session 4: In-Situ Compression Through Adaptive Recursive

Partitioning for Multi-Dimensional Images

Rongjie Liu, Meng Li, Rice University; Li Ma, Duke University

2:30 p.m. – 3:30 p.m.

N Sponsor Networking Session

3:30 p.m. – 4:30 p.m.

N Networking Break

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D ATA S C I E N C E 2 0 2 0 | T U E S D AY, O C T O B E R 2 7 D D3CODE

C Session A: COVID-19

H Session D: Healthcare

K Keynote

A Session B: Algorithms & Foundations

P Poster Session

N Networking

B Session C: Business Impact

8:30 a.m. – 9:15 a.m.

N Networking Break

9:15 a.m. – 9:25 a.m.

9:25 a.m. – 9:50 a.m.

K Session 5: How Genomics England’s Groundbreaking

Session 5: Welcome Angela Wilkins, Rice University

COVID-19 Research Environment has Ushered in a New Era in Genomics Data Access and Collaboration

Maria Chatzou Dunford, Lifebit Biotech

9:50 a.m. – 10:05 a.m.

Break

10:05 a.m. – 10:30 a.m.

K Session 6: Real Time, GPU-Accelerated Analysis and

Visualization in the Life Sciences

Michelle Gill, Avantika Lal, NVIDIA

10:30 a.m. – 10:55 a.m.

K Session 6: Success and Remaining Challenges of SARS-CoV-2

Testing, Research, and Communication

Fritz Sedlazeck, Human Genome Sequencing Center, Baylor College of Medicine Sponsored by

10:55 a.m. – 11:10 a.m.

Break

K Session 7: Panel: Governing the Data Revolution 11:10 a.m. – 11:55 a.m.

David Jaffray, Caroline Chung, UT MD Anderson Cancer Center; Raghu Ramakrishnan, Microsoft; Maria Chatzou Dunford, Lifbit Biotech; Andre Dekker, MAASTRO Clinic,

Maastricht University, Maastricht University Medical Center+; Angela Wilkins, Rice University

11:55 a.m. – 12:45 p.m.

N Networking Break & Lunch

12:45 p.m. – 1:00 p.m.

B Session 8: Detecting Hidden Multi-Family Households for

Houston Census 2020

Zhaozhuo Xu, Alan Ji, Andrew Wood, Anshumali Shrivastava, Rice University; Beidi Chen, Stanford University

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B Session 8: Multiphase Flow Intelligent Sensing

1:00 p.m. – 1:15 p.m.

Rube Williams, Stratos Perception, LLC; Richard Kurwitz, Texas A&M University

1:15 p.m. – 1:30 p.m.

B Session 8: Deep Learning Based Seismic Denoising of Migrated

1:30 p.m. – 1:45 p.m.

Gathers for Velocity Model Building

Janaki Vamaraju, Boran Han, Shell Global Solutions US Inc.; Christian Sutton, Zaifeng Liu, Shell Exploration & Production Company; Harry Rynja, Jeremy Vila, Shell International Exploration and Production Inc.

B Session 8: Reconstruction of Missing Seismic Data Using a

Deep Learning-based Approach

Chayawan Jaikla, Stanford University; Pandu Devarakota, Shell Global Solutions Inc.; Engin Alkan, Christian Sutton, Shell International Exploration and Production Inc.

1:45 p.m. – 2:00 p.m.

H Session 8: Estimating Drugs Sensitivity on Pancreatic Cancer

as Cold Start Problem in Recommender Systems

Mohammad Taha Toghani, Rice University; Yejin Kim, University of Texas Health Science Center at Houston; Xiaoqian Jiang, UTHealth at Houston

2:00 p.m. – 2:15 p.m.

H Session 8: Use Interpretability to Help Improve Model

Performance and Human Diagnosis

Licheng Zhang, Houston Methodist; Jielin Xu, Cleveland Clinic; Peng Zhang, University of Houston; Cheng Zhan, Microsoft; Yunwei Hu, General Electric

2:15 p.m. – 2:30 p.m.

H Session 8: Novel Calculation of Pulse Pressure Variation Can

Reliably Predict Fluid Responsiveness in the NICU

Zachary Foughty, Onur Tavaslioglu, Christopher Rhee, Leah Elizondo, Craig Rusin, Sebastian Acosta, Baylor College of Medicine; Danielle Rios, University of Iowa Carver College of Medicine

2:30 p.m. – 4:00 p.m.

P Poster Presentation Session

4:00 p.m. – 4:30 p.m.

N Networking Break

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D ATA S C I E N C E 2 0 2 0 | W E D N E S D AY, O C T O B E R 2 8 D D3CODE

C Session A: COVID-19

H Session D: Healthcare

K Keynote

A Session B: Algorithms & Foundations

P Poster Session

N Networking

B Session C: Business Impact

8:30 a.m. – 9:15 a.m.

N Networking Break

9:15 a.m. – 9:25 a.m.

Session 9: Welcome & Poster Awards Angela Wilkins, Rice University

D Session 9: Nuances of Virtual Collaboration 9:25 a.m. – 9:40 a.m.

Angela Wilkins, Rice University

9:40 a.m. – 9:55 a.m.

D Session 9: Brainswarming: Leveraging Team Perspectives for

Collaborative Problem-Solving & Learning

Caroline Chung, UT MD Anderson Cancer Center

9:55 a.m. – 10:10 a.m.

D Session 9: D3CODE: Leveraging Team Science for Better

Understanding of COVID-19 in Cancer Patients

Andy Futreal, UT MD Anderson Cancer Center

10:10 a.m. – 10:25 a.m.

Break

10:25 a.m. – 11:05 a.m.

D Session 10: Rapid Fire Talks from UT MD Anderson Cancer

Center

• Scott E. Woodman - Integration and Analysis of Disparate and Multidimensional Data From Heme Malignancy Patients in the COVID-19 Era • Cristhiam Rojas Hernandez - Characteristics and Clinical Outcomes of Coagulopathy in Cancer Patients with COVID-19 • Nicolas Palaskas - Cardiovascular Disease in COVID-19 Patients with Cancer • Anai Kothari - Universal Asymptomatic Preoperative COVID Testing Prior to Time-Sensitive Oncologic Surgery • Ashley Aaroe - Investigating Neurological and Oncologic Manifestations of COVID-19 Using the D3CODE Platform • Kristy Brock - Harnessing AI and Advanced Image Analysis for COVID Detection and Classification • Jia Wu - Habitat Imaging for COVID-19: Discover Clinically Relevant and Actionable Biomarkers • Ergin Soysal - Extraction of Robust Insights from the Evolving Literature in Response to COVID-19

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11:05 a.m. – 11:20 a.m.

Break

D Session 11: Rapid Fire Talks from Rice University 11:20 a.m. – 11:45 a.m.

• Ankit Patel - Understanding Neural Networks: Representation, Learning Dynamics and Generalization

• Ashok Veeraraghavan - Scalable Health Labs at Rice • Dan Kowal - Prediction and Decision Analysis for Dynamic Data • Risa Myers - Find Data, Use Data, Teach Data • Marek Kimmel - TBA

11:45 a.m. – 12:00 p.m.

Break

12:00 p.m. – 12:30 p.m.

D Session 12: Panel: Building Collaboration in the Middle of a

Global Pandemic – Why, What and How?

Andy Futreal, Caroline Chung, David Jaffray, UT MD Anderson Cancer Center; Lydia Kavraki, Chris Jermaine, Rice University

12:30 p.m. – 1:30 p.m.

N Networking Break & Lunch

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