The 1000x Lab: First Congress
Feb 20, 7:30 AM – Feb 21, 3:00 PM
AT&T Exec. Education & Conference Center,
1900 University Ave, Austin, TX 78705
Can you make it?


Increasingly, industry leaders wish to leverage data-driven models (AI and ML) and well-calibrated simulations to lower R&D costs by replacing expensive laboratory measurements, particularly in the materials design and manufacturing business. The vision is good, but the reasoning is often flawed.  Building data-driven models and eliminating experiments are often mutually exclusive ideas in scientific discovery. The strength of data-driven models is directly proportional to the amount and quality of data that they are trained on, and experiments are where the data are produced. 

Thus, this vision of simulation and AI driven exploration and design relies on a significant change to the status-quo in many laboratories.  Of course there are shining exceptions, but in our exposure to many industrial chemistry and bio-sciences labs, we have consistently seen opportunities to increase the lab throughput by 10, 100, or even 1000x with similarly lower costs per sample. However, when suggested to an industry scientist, these ideas are often perceived as too expensive or impractical. Some of this is a skills gap. Some of it is an imagination gap. And, much of it is an examples gap. Every lab that these scientists have ever seen is designed with significant manual work to formulate samples that are then shipped out to multiple buildings/ laboratories for manual characterization.  

The goal of this project is to develop tools, methodologies, and examples that can bridge this gap for scientists so that they embrace instead of be wary of these efforts.  There are numerous mental and design shifts needed to achieve these goals, and so the primary goal of the First Congress is to identify and bring together key participants from academia, industry, and government to discuss experimental needs across these sectors, share information on the state of the art, and determine a path for how this community can collaborate, be governed, and produce meaningful results towards shared goals going forward.

First Congress Schedule

February 20, 2020


7:30  -  Breakfast

8:30  -  Opening Welcome by Roger Bonnecaze, University of Texas at Austin

8:35  -  Keynote Speech by Eric Jones, Enthought

1000x Lab: The Rationale, Enablers, and Direction

Industry Problems:

9:15  -  Industry Problem 1 by William Hartt, Proctor & Gamble

Rheological Properties of Goopy Materials - From the Laboratory to the AI Ecosystem

10:00  -  Break

10:30  -  Industry Problem 2 by Mark Simon, Saint-Gobain

Formulating Strategies for Asphalt and Silicone Applications

11:15  -  Industry Problem 3 by Peter Soler, Bristol-Myers Squibb

Biologics Formulation Development: Leveraging Automation & High-Throughput Screening

12:00  -  Lunch break

Example Solutions:

13:00  -  Michael Heiber, Enthought

Scalable, Automated Hardware Tools to Transform Polymer Thin-Film R&D

13:20  -  Eric Furst, University of Delaware

High-Throughput Rheological Measurements with Microrheology

13:40  -  Zachary Trautt, NIST

Open Hardware, Open Data, and the 1000x Laboratory

14:00  -  Filippos Tourmomousis, MIT

Rapid Prototyping for Open Metrology

14:20  -  Michael J. McCarthy, University of California, Davis

Development of a Robust Non-Newtonian Process Rheometer

14:40  -  Martin Green, NIST

Autonomous (AI-driven) Experimental Materials Science

15:00  -  Break

15:30  -  Panel Session and Q&A: Industry Problems

16:15  -  Panel Session and Q&A: Example Solutions

17:00  -  Measurement Accelerator Poster Session and Happy Hour

18:00  -  Dinner at El Mercado

February 21, 2020


8:00  -  Breakfast

9:00  -  Discussion Session Framing by Roger Bonnecaze, University of Texas at Austin

9:15  -  Discussion Session: Building The 1000x Lab

10:30  -  Break

10:45  -  Discussion Session: Building The 1000x Lab Continued

12:00  -  Lunch break

13:00  -  Summary of discussion session

14:00  -  Closing Remarks and Governance

15:00  -  End of Congress


Meet the Community


Eric Jones

Founder/CEO of Enthought

Eric holds both a Ph.D. and M.S. in Electrical Engineering from Duke University and a B.S.E. in Mechanical Engineering from Baylor University. Widely known as one of the founding fathers of Python’s scientific community, Eric drives business growth through digital transformation.
For more than 15 years, he has been an innovator in applying machine learning, image processing, 3D visualization, and parallel computing to elegantly solve the most complex business problems.
Prior to founding Enthought in 2001, Eric focused on numerical electromagnetics and genetic optimization in the Department of Electrical Engineering at Duke University.

Contact Us:

Enthought, Inc.

200 W. Cesar Chavez St., Suite 202
Austin, TX 78701


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