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Provided by ASME Logo The American Society of Mechanical Engineers

Student Hackathon

2020 ASME-CIE Hackathon: Identifying, Extracting, Analyzing of Value from Large Unstructured Data Sets in Mechanical Engineering

 

St. Louis Union Station Hotel, St. Louis, MO, USA
August 15-16, 2020

In conjunction with IDETC/CIE 2020

Sponsored by

ASME Computers & Information in Engineering Division (CIE) &
ASME Technical Events and Content (TEC) Sector Council

ASME Manufacturing Engineering Division (MED) Centennial Celebration Endorsed Event

Please download the ASME Hackathon 2020 flyer here and share it with your friends!

For more details and sample datasets, please visit the Hackathon GitHub

Important Dates:

  • June 19, 2020: Hackathon sign-up deadline
  • August 15th, 3 pm 2020: Hackathon Kick-off
  • August 16th, 4 pm 2020: Due for Hackathon deliverables
  • August 16th, 8 pm 2020: Awarding ceremony

Introduction

This 2020 ASME-CIE Hackathon is co-located with the International Design Engineering Technical Conferences & Computers and Information in Engineering Conference. The Hackathon is sponsored by the ASME Technical Events and Content (TEC) Sector Council and the ASME Computers & Information in Engineering Division (CIE) with the goal to build multi-stakeholder (society-university-industry) relations and impact the quality and quantity of data-skilled mechanical engineers. The ASME-CIE 2020 Hackathon is the first Hackathon event held by ASME and is expected to become one of the signature events of the American Society of Mechanical Engineering (ASME).

Award Information

  • First Place: $2,000
  • Second Place: $1,000
  • Third Place: $500

Note: Teams will be judged in each problem tropic area, and awardees will be selected separately.

Eligibility

Both students and non-students (e.g., researchers from national labs, professionals from industry, etc.) are welcome to attend the Hackathon and experience the exciting competitions. Participants can register for the event as (1) a student or (2) a non-student. Note: non-student groups include any group with a non-student member, even in the case when several members of the group are students. Per the funding objective, non-student participants are not eligible for travel awards and prizes. Each group category will be independently assessed and will receive their own rankings within the group category.

Theme

Big Data is defined as “large volumes of high velocity, complex and variable data that require advanced techniques and technologies to enable the capture, storage, distribution, management, and analysis of the information.” However, it is reported that majority of the data collected (more than 80%) is unstructured data in the form of image, video, audio, undefined text and numbers. This is true in many mechanical engineering subfields where sensors are ubiquitous and digitization is pervasive, for example, when analyzing Amazon reviews to elicit customer preferences in support of engineering design, and using images of 3D printing in support of manufacturing prognosis. While the value of unstructured data is evident by the vigor and velocity with which new tools are being created in the private sector to extract this hidden value, in mechanical engineering, the question of how to leverage the power of unstructured data to benefit product design and development, manufacturing and complex systems engineering is still yet fully answer.

The ASME-CIE Hackathon attempts to provide an open mechanism for researchers to explore new statistical and machine-learning techniques appropriate for the use of unstructured text, images, audio etc. in design, manufacturing and systems engineering, and on the other hand, to develop new educational pathways to train the next generation of data-skilled mechanical engineers. The participants will have the opportunity to learn and experience various data visualization, data mining, and machine learning methods to develop automated processes for:

  • Identification of patterns within the unstructured data that are predictive of valuable or negative attributes.
  • Use of valuable extracted content to improve predictive models.
  • Removal or correction of negative content associated with errors, bias, or privacy.

Hackathon Problems

Teamwork

Hackathon is a teamwork. You do not need to have all the skills – that’s what TEAMWORK is for! Please join us if you have:

  • Creative or innovative ideas
  • Business or marketing talents
  • Data science or statistics concepts
  • Domain knowledge and critical thinking
  • Computational linguistics skills
  • Programming skills

Hackathon Team and Presentation

  • All participants must be registered via here. Register the event and attend the Hackathon physically. Each participant brings his/her own laptop with all the necessary computing tools. Everyone will be placed in a team up to three members. You may form your own team onsite. All implementation must be based on the original work.
  • Each Hackathon team will continue their own meetings and hacking exercises during the two days between 4pm 08/15/20 and 4pm 08/16/20.
  • Each team needs to present their teamwork including the technical approach and the results.