+1 vote
asked ago by (55.9k points)
Conventional theory building, model development, and causal inference are necessary but no longer sufficient tools for Tech companies thriving in today’s economic environment. The emergence of powerful software algorithms, next-generation experiments, big data, commodification of processing power, scalable platform computing, A.I., and machine learning are generating profound change for business economists and their academic colleagues.

NABE’s TEC 2019 Conference https://nabe.com/tec2019, brings together leading thinkers in economics and data science in an intellectual exchange on how interdisciplinary developments in these fields are impacting today’s approaches, frameworks, tools, and techniques. World-class business economists at Tech companies like Amazon, CoreLogic, Facebook, Google, IBM, Indeed, Intel, Netflix, Redfin, and Zillow will elaborate on the emerging and future data science needs in economic research and practice.

If you are a graduate student, assistant professor, junior researcher, or young professional who has developed innovative ideas in the alignment of economics and data science and would like to display a new methodology, research, or technique, you are encouraged to apply to participate in the poster session.  Go to https://www.surveymonkey.com/r/3WMYCTR

The Poster Session is designed to encourage the free flow of new thoughts and ideas and research in progress. The poster session will allow you to present your work, network with others who may be working on similar projects, and receive feedback from a broad network of tech economists.

The poster sessions will take place at the Hyatt Regency Seattle on Monday, November 4, 2019. Winners will be given 3-5 minutes to present a summary of their research during that day's opening session of the conference. The Poster Sessions will continue during networking breaks in the ballroom foyer, where winners will be available to discuss their research with visual displays, and answer questions from conference attendees (times subject to change; NABE will email exact times of networking breaks one week before event). Selected applicants must be present at all sessions.

The Selection Committee will select abstracts for poster submission. Applicants will be required to submit a draft showing significant progress through a draft poster or preliminary results report. Final selection, and the opportunity to present at the conference, will be based on the selection committee's approval of progress. Applicants invited to display at the conference will receive one complimentary full registration to the 2019 NABE Tech Economics Conference!
PROCESS FOR SELECTION (two-tiered):

1.       Apply by Friday, August 2, 2019
                                  a.         Complete the application (via Survey Monkey), including contact details,
                                  b.         Submit an abstract of no more than 250 words, and
                                  c.         Copy and paste a one-page CV
 
2.       Candidates of the selected abstracts will be notified by Monday, August 19, 2019.
3.       Draft poster or preliminary results report, showing significant process, due Monday, September 9, 2019.
4.       Candidates who have demonstrated significant progress, as determined by the committee, will be selected for display at the 2019 NABE Tech Economics Conference in Seattle, WA on November 4. Those individuals will receive a complimentary registration to the conference. Notification of final selection will take place no later than Monday, September 23, 2019.  

Topics include, but are not limited to:
●     Machine Learning Studies
●     Non-traditional sources of data
●     Addressing non-representative samples and other challenges of private data sources
●     Internet experiments
●     Prediction with big data
●     Economics and deep learning
●     Economics and Artificial Intelligence
●     Visualization and communications of recommendations based on empirical analysis of big data
●     Data taxonomy, ontology, classification, and meta-tagging in the domain of machine learning
●     Approaching the problem: Inferences based on discovery of data patterns vs. Validation of theoretical, predictive models
 
Judging:
Posters will be judged on a five-point scale in the areas of Creativity, Relevance, Potential for Insight, and Feasibility.
Please note: Exhibition of commercial products or services is not permissible. One complimentary registration will be awarded per selected poster.

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