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Domain Specific Metaheuristic Optimization

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For non-technical domain experts and designers it can be a substantial challenge to create designs that meet domain specific goals. This presents an opportunity to create specialized tools that produce optimized designs in the domain. However, implementing domain specific optimization methods requires a rare combination of programming and domain expertise. Creating flexible design tools with re-configurable optimizers that can tackle a variety of problems in a domain requires even more domain and programming expertise. We present OPTIMISM, a toolkit which enables programmers and domain experts to collaboratively implement an optimization component of design tools. OPTIMISM supports the implementation of metaheuristic optimization methods by factoring them into easy to implement and reuse components: objectives that measure desirable qualities in the domain, modifiers which make useful changes to designs, design and modifier selectors which determine how the optimizer steps through the search space, and stopping criteria that determine when to return results. Implementing optimizers with OPTIMISM shifts the burden of domain expertise from programmers to domain experts.

Megan Hofmann, Nayha Auradkar, Jessica Birchfield, Jerry Cao, Autumn G. Hughes, Gene S.-H. Kim, Shriya Kurpad, Kathryn J. Lum, Kelly Mack, Anisha Nilakantan, Margaret Ellen Seehorn, Emily Warnock, Jennifer Mankoff, Scott E. Hudson: OPTIMISM: Enabling Collaborative Implementation of Domain Specific Metaheuristic Optimization. CHI 2023: 709:1-709:19

https://youtube.com/watch?v=wjQrFeLbOiw%3Fsi%3DkMTxEkEBjoUrQDJ3

Rapid Convergence: The Outcomes of Making PPE during a Healthcare Crisis

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Kelly Avery Mack, Megan Hofmann, Udaya Lakshmi, Jerry Cao, Nayha Auradkar, Rosa I. Arriaga, Scott E. Hudson, Jennifer Mankoff. Rapid Convergence: The Outcomes of Making PPE During a Healthcare Crisis. [Link to the paper]

The U.S. National Institute of Health (NIH) 3D Print Exchange is a public, open-source repository for 3D printable medical device designs with contributions from clinicians, expert-amateur makers, and people from industry and academia. In response to the COVID-19 pandemic, the NIH formed a collection to foster submissions of low-cost, locally-manufacturable personal protective equipment (PPE). We evaluated the 623 submissions in this collection to understand: what makers contributed, how they were made, who made them, and key characteristics of their designs. We found an immediate design convergence to manufacturing-focused remixes of a few initial designs affiliated with NIH partners and major for-profit groups. The NIH worked to review safe, effective designs but was overloaded by manufacturing-focused design adaptations. Our work contributes insights into: the outcomes of distributed, community-based medical making; the features that the community accepted as “safe” making; and how platforms can support regulated maker activities in high-risk domains.