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SUMMARY:MechE Seminar: Representing Knowledge for Data-Driven Design and M
 anufacturing
DTSTART:20220216T160000
DTEND:20220216T170000
DTSTAMP:20260407T164043Z
UID:863e0653d6e4ea6c4f6e19528a15f612f4f8efae625ff57d433b6c49
CATEGORIES:Conferences - Seminars
DESCRIPTION:Mr Haluk Akay\, Park Center for Complex Systems\, Mechanical E
 ngineering Department\, Massachusetts Institute of Technology (MIT)\nAbstr
 act: Artificial Intelligence has transformed the practice of fields such a
 s Computer Vision and Natural Language Processing to deliver revolutionary
  technology including autonomous vehicle systems and automated language tr
 anslation services. A similar data-driven transformation of design and man
 ufacturing is necessary to guide engineers through complexity to develop n
 ext-generation sustainable products and production systems. Data is abunda
 nt from digitally documented early-stage design through final production p
 rocesses\, but this data is often unstructured\, informal\, and can be qua
 litative or textual in nature. Design and manufacturing data must be compu
 tationally interpretable in order for past documented knowledge to guide f
 uture engineering decision-making. In this seminar\, I will present my res
 earch leveraging deep neural network-based language modeling to represent 
 design and manufacturing data\; specifically\, textually described knowled
 ge. I will also describe how such quantitative representation models make 
 possible a wide range of applied AI methods for performing tasks such as e
 valuating functional interdependencies and extracting functional informati
 on from past design documentation. By learning from past engineering failu
 res and achievements\, Artificial Intelligence can be used to assist human
  designers’ decision-making for meeting the needs of society and the env
 ironment through data-driven sustainability.\n\nBio: Haluk Akay is a PhD c
 andidate at the MIT Department of Mechanical Engineering\, in the Park Cen
 ter for Complex Systems\, advised by Professor Sang-Gook Kim. He received 
 his M.S. from MIT and his B.S. from Carnegie Mellon University\, both in M
 echanical Engineering. At MIT\, his doctoral research applies Artificial I
 ntelligence to design and manufacturing by developing methods for represen
 ting engineering knowledge for computational interpretability. His masters
  research focused on low-frequency vibrational energy harvesting\, designi
 ng and fabricating MEMS piezoelectric devices and wearable energy harvesti
 ng systems resulting in patented technology. Previously\, he has designed 
 power electronics for Apple and fabricated carbon fiber Formula race car e
 xteriors at Carnegie Mellon. He serves as a resident tutor in Baker House 
 at MIT.
LOCATION:https://epfl.zoom.us/j/68810111178
STATUS:CONFIRMED
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