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Fall 2018

October

  • "Does This Vehicle Belong to You?"
    Processing the Language of Policing for Improving Police-Community Relations

    Dr. Dan Jurafsky, Professor and Chair of Linguistics and Professor
    of Computer Science, Stanford University.

     

       Tuesday, October 9

       5 p.m. Reception
       6 p.m. Talk
       Engineering Lecture Hall L2D2

    Register here

  • Police body-worn cameras have the potential to play an important role in understanding and improving police-community relations. In this talk I describe a series of studies conducted by our large interdisciplinary team at Stanford that use speech and natural language processing on body-camera recordings to model the interactions between police officers and community members in traffic stops. We use text and speech features to automatically measure linguistic aspects of the interaction, from discourse factors like conversational structure to social factors like respect. I describe the differences we find in the language directed toward black versus white community members, and offer suggestions for how these findings can be used to help improve the fraught relations between police officers and the communities they serve.

September

  • High Performance Computing and Big Data:
    Challenges for the Future

    Dr. Jack Dongarra, Distinguished Professor, University of Tennessee, Knoxville, TN.

     

       Event is canceled!

      

     

  • Historically, high-performance computing advances have been largely dependent on concurrent advances in algorithms, software, architecture, and hardware that enable higher levels of floating-point performance for computational models. Advances today are also shaped by data-analysis pipelines, data architectures, and machine learning tools that manage large volumes of scientific and engineering data.

    We will examine some of the challenges involved with high performance computing and big data for scientific computing.

August

  • Attention and Baseball Analytics

    Dr. Ryan Ferguson, Baseball Operations R&D Analyst, Houston Astros

     

       Thursday, August 30

       5 p.m. Reception
       6 p.m. Talk
       Engineering Lecture Hall L2D2

     

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  • Baseball’s embrace of advanced statistics and data driven decisions has received an increasing amount of attention over the past decade. The World Champion Houston Astros are recognized as being on the cutting edge of using data to build and direct their team. Over the same time period, many industries are scrambling to find a way to generate novel insights from existing data and find new ways to gather data. Terms like ‘data scientist’ and ‘data engineer’ have become prevalent in job ads, but those terms are somewhat ill defined and the role of a data scientist in the context of an organization varies a great deal. Ryan (who is a psychologist, kinda) will use a brain metaphor to explain data’s role in the organization of the Houston Astros and give insight into how the Astros leverage data and technology to drive decisions and win championships. Ryan will also discuss the pitfalls and dangers of erroneous conclusions, and how integrating data experts with domain experts can hopefully reduce the prevalence of mistakes.

November

  • Bias on the Web

    Ricardo Baeza-Yates, CTO - NTENT & Director of Computer Science Programs at Northeastern University, Silicon Valley, CA.

     

       Tuesday, November 13

       5 p.m. Reception
       6 p.m. Talk
       Engineering Lecture Hall L2D2
     

  • The Web is the most powerful communication medium and the largest public data repository that humankind has created. Its content ranges from great reference sources such as Wikipedia to ugly fake news. Indeed, social (digital) media is just an amplifying mirror of ourselves. Hence, the main challenge of search engines and other websites that rely on web data is to assess the quality of such data. However, as all people has their own biases, web content as well as our web interactions are tainted with many biases. Data bias includes redundancy and spam, while interaction bias includes activity and presentation bias. In addition, sometimes algorithms add bias, particularly in the context of search and recommendation systems. As bias generates bias, we stress the importance of debiasing data as well as using the context and other techniques such as explore & exploit, to break the filter bubble. The main goal of this talk is to make people aware of the different biases that affect all of us on the Web. Awareness is the first step to be able to fight and reduce the vicious cycle of bias.

 

Summer 2018

Data Science Bootcamp

 

Engineering, business, science, politics and many others heavily utilize data for decisions making. Several topical, rapidly evolving and powerful data analysis techniques, designed to be comprehensive, with a gentle learning curve, have become available. A knowledge of these tools and techniques provides a competitive advantage: nowadays “Data Scientist” is the number one job posted in all HR systems. The HPE DSI Data Science Bootcamp aims at providing an overview and a basic hands-on experience of some of the most popular data science methods and tools publicly available. Instructors will guide participants in the use Python to analyze data, create meaningful visualizations, and leverage statistics by using powerful machine-learning libraries such as Tensorflow. A taste of the programming language R for statistical computing will also be provided as well as the opportunity to work with some tutorials implemented by NVIDIA for accelerated computing data research.

 

Data Science and You

 

What is data science? What does it take to have a career in this field? Data science is quite broad and many opportunities are available not only to data science professionals, but people with less specialized knowledge in the field. The number of data-science-related jobs is expected to increase to nearly 3 million by 2020. With such a promising outlook, it is important for students to gain knowledge about data science and learn how to begin their journey down this exciting career path. The HPE DSI is pleased to announce the offering of Data Science & You, a series of three-part workshops this summer. By attending one or more workshops attendees will…

Explore the true meaning of data science: What is it? How difficult is data science and uses in society

Presenter: Andrey Skripnikov, PhD graduate from the University of Florida, currently serving as a postdoctoral associate at the University of Houston. He also writes a weekly sports analytics column, By the Numbers for the Daily Cougar.

Hear from data science professionals about the nature of the work, career possibilities and opportunities and the rewards (financial and otherwise) of a career in this field.

Participate in hands-on presentations with Jupyter notebooks which will demonstrate data science activities such as data import and cleaning, data analysis and interpretation and visual communication. No prior background in data science or programming is required 

Every workshop hosts different data science professionals working in diverse areas and is available to all interested parties, but undergraduate students are especially encouraged to attend. Workshop topics include public policy, law, business, life sciences, engineering and health and are hosted at the CBB room 118 from 1-4:30 p.m. through the summer. Due to limited seating, please RSVP