Adrian Buganza Tepole
@abuganzat
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Associate Professor of Mechanical Engineering, Purdue University
Joined May 2013
It was great to be part of this team effort across continents!.
🚨New paper alert🚨.Delighted to share that our latest paper on predicting skin growth has just been published online in @SciReports congrats to Dr. Matt Nagle and the team! @abuganzat @michael_fop #DreamTeam 😜
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RT @AislingNiA: 🚨New paper alert🚨.Delighted to share that our latest paper on predicting skin growth has just been published online in @Sci….
nature.com
Scientific Reports - A machine learning approach to predict in vivo skin growth
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RT @PurdueME: .@Minecraft, the best-selling video game in history, is now a teaching tool for solid mechanics! @PurdueME has published the….
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We extend the framework to generate heterogeneous fields of material responses and solve finite element simulations on complex geometries.
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Unlike traditional applications of diffusion models which work on discrete data, we generate samples of continuous representations of strain energy functions based on NODEs
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We use diffusion models which are the state-of-the-art for generative AI
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We start with our polyconvex neural ordinary differential equations (NODE) to describe strain energy functions. How can we learn distribution of material responses?
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🚨New #preprint 🚨 .. 'Generative hyperelasticity with physics-informed diffusion fields'! .with @fcosahli @tajtac @ProfRausch @BilionisIlias . We use diffusion for uncertainty quantification in material models. A 🧵👇
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RT @EmlWebinar: #EML_Webinar (Young Researchers Forum) on 17 October 2023 will be given by Emma Lejeune @LejeuneLab at Boston University @B….
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RT @ZhengJia_ZJU: Please join the upcoming EML webinar given by Prof. Emma Lejeune on October 17, 2023. Zoom link: .
us06web.zoom.us
Zoom is the leader in modern enterprise cloud communications.
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Go Vahid!!.
Vahid Tac explains his research and how mechanical engineering plays a role in the fight against cancer. #GradPurdue students can submit their research for consideration in the 2024 edition of InnovatED here: @PurdueME
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iMechanica runs a Journal Club series, and for September I wrote an entry on some of the recent topics in soft tissue constitutive modeling. #AcademicTwitter #biomechanics #mechanics folks, what is on your mind?
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RT @tajtac: Our paper on data-driven viscoelasticity with Neural ODEs is published in Computer Methods in Applied Mechanics and Engineering….
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congrats!!!!!.
Happy to complete promotion and immensely grateful for the hard work of the dear group members and support of the collaborators, mentors, and colleagues!.
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We use neural ODEs to create data-driven potentials with build-in (poly)convexity in order to guarantee minimizers of the strain energy and positive energy dissipation a priori. Being data-driven, framework can capture: 🧠, 🫀,🩸-clot, 🛞. code:
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New preprint work from the lab by @tajtac in collaboration with @fcosahli and @ProfRausch: Data-driven anisotropic finite viscoelasticity using neural ODEs #MachineLearning #DataScience
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We developed challenges like building a bridge in the desert. Prof. Bill Watson and Alexander Bowman helped us frame the challenges within the Problem Based Learning (PBL) framework. If you want to use it in your class let me know! Or just use it for fun 😄4/4
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