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TAMIDS Announces Two Further Thematic Data Science Labs for 2022

Nick Duffield, Director of the Texas A&M Institute of Data Science (TAMIDS), is excited to announce that two submissions were selected for the creation of two Thematic Data Science Labs on the Texas A&M University campus. The mission of each Lab will be to develop knowledge, resources, and community around an emerging thematic area of Data Science, encompassing research, education, and outreach. TAMIDS will support each Lab through a combination of seed funding for new research, effort from TAMIDS personnel, preferred access to existing TAMIDS programs, and organizational and logistical support. The awards for the 2022 competition go to:

  • The Design & Analytics Lab for Urban Artificial Intelligence, directed by Xinyue Ye, Department of Landscape Architecture and Urban Planning, School of Architecture & Department of Geography (Courtesy appointment), College of Arts & Sciences, with membership comprising: Galen Newman, Department of Landscape Architecture & Urban Planning, School of Architecture; Keith Biggers, Texas A&M Center for Applied Technology, Texas A&M Engineering Experiment Station; Bahar Dadashova, Texas A&M Transportation Institute; Xiaofeng Nie, Department of Engineering Technology and Industrial Distribution & Department of Industrial and Systems Engineering (Courtesy appointment), College of Engineering; David Retchless, Department of Marine and Coastal Environmental Science, Texas A&M University at Galveston; Nitesh Saxena, Department of Computer Science & Engineering, College of Engineering; Zhe Sarina Zhang, Department of Geography, College of Arts & Sciences.
  • The Digital Twin Lab, directed by Jian Tao, Department of Visualization, School of Performance, Visualization and Fine Arts, with membership comprising: Eduardo Gildin, Petroleum Engineering, College of Engineering; Juan A. Landivar, Texas A&M Agrilife Research, Corpus Christi; Xin Li, Department of Visualization, School of Performance, Visualization and Fine Arts; Walt Magnussen, Texas A&M University Internet2 Technology Evaluation Center (ITEC); Zheng O’Neill, Mechanical Engineering, College of Engineering; Jean Ragusa, Nuclear Engineering, College of Engineering; Narasimha Reddy, Electrical and Computer Engineering, College of Engineering; Andre Thomas, Department of Visualization, School of Performance, Visualization and Fine Arts.
Dr. Jian Tao, Department of Visualization, School of Performance, Visualization, and Fine Arts, Director of the Digital Twin Lab.
Dr. Xinyue Ye, Department of Department of Landscape Architecture and Urban Planning, School of Architecture & Department of Geography, College of Arts & Sciences, Director of the Design & Analytics Lab for Urban Artificial Intelligence.

According to Dr. Ye: “Big data and computational algorithms have gradually become integrated with the built environment and within human’s daily lives, leading to Urban Artificial Intelligence (AI) research and applications. As such, the TAMIDS Design & Analytics Lab for Urban AI will dynamically analyze built environments and test scenarios for sustainable growth and climate action.” Dr. Jian Tao says that, “The TAMIDS Digital Twin Lab (DTL) aims to develop innovative visualization, computing, and networking technologies and efficient theory/data-driven modeling methods to speed up the creation and deployment of digital twins for a wide spectrum of real-world applications. The lab will also actively develop and engage in education and training programs to teach and promote digital twin technologies at Texas A&M and beyond.”

TAMIDS program leaders will work with the new lab directors to promote their engagement with TAMIDS activities and programs, support their growth, and help develop synergies with the existing Thematics Labs: the Scientific Machine Learning Lab (director Ulisses Braga-Neto), the Data Justice Lab (director Lu Tang), the VIVID Lab (director Ann McNamara) and the Operational Data Science Lab (director Nick Duffield).

To learn more about the Texas A&M Institute of Data Science, visit https://tamids.tamu.edu/