A. E. Hosoi

A. E. Hosoi

Massachusetts Institute of Technology

H-index: 29

North America-United States

About A. E. Hosoi

A. E. Hosoi, With an exceptional h-index of 29 and a recent h-index of 21 (since 2020), a distinguished researcher at Massachusetts Institute of Technology, specializes in the field of Fluid dynamics, biomechanics.

His recent articles reflect a diverse array of research interests and contributions to the field:

When is it Profitable to Make a Product Sustainable? Insights from a Decision‐Support Tool

Modeling Running via Optimal Control for Shoe Design

Data-driven control of COVID-19 in buildings: a reinforcement-learning approach

Parameterized shape adaptive materials for sportswear

Beyond fairness: Reparative algorithms to address historical injustices of housing discrimination in the US

Simple control for complex pandemics

Estimating the filtration efficacy of cloth masks

Simple control for complex pandemics (preprint)

A. E. Hosoi Information

University

Massachusetts Institute of Technology

Position

___

Citations(all)

4250

Citations(since 2020)

1819

Cited By

3178

hIndex(all)

29

hIndex(since 2020)

21

i10Index(all)

51

i10Index(since 2020)

41

Email

University Profile Page

Massachusetts Institute of Technology

A. E. Hosoi Skills & Research Interests

Fluid dynamics

biomechanics

Top articles of A. E. Hosoi

When is it Profitable to Make a Product Sustainable? Insights from a Decision‐Support Tool

Authors

Karan Bhuwalka,Jessica Sonner,Lisa Lin,Mirjam Ambrosius,AE Hosoi

Journal

Technology Innovation for the Circular Economy: Recycling, Remanufacturing, Design, Systems Analysis and Logistics

Published Date

2024/3/29

Meeting corporate sustainability goals requires policies and business models that incentivize sustainable product design. We create a simple modeling tool that examines the conditions in which it is profitable for companies to sell more sustainable versions of a product. Users can input variables that relate to consumer demand (e.g. proportion of consumers willing to pay the price premium for a sustainable product), policy (e.g. carbon tax) and costs of production including the added costs associated with incorporating sustainable materials and practices. To demonstrate the utility of our tool, we input values for sneaker production and identify the demand and policy conditions under which sustainable sneaker design leads to increased profit. Policymakers and companies can use this as a decision‐support tool to promote sustainable design for various ranges of products.

Modeling Running via Optimal Control for Shoe Design

Authors

Sarah C Fay,AE Hosoi

Journal

Journal of Biomechanical Engineering

Published Date

2024/4/1

Shoe manufacturing technology is advancing faster than new shoe designs can viably be evaluated in human subject trials. To aid in the design process, this paper presents a model for estimating how new shoe properties will affect runner performance. This model assumes runners choose their gaits to optimize an intrinsic, unknown objective function. To learn this objective function, a simple two-dimensional mechanical model of runners was used to predict their gaits under different objectives, and the resulting gaits were compared to data from real running trials. The most realistic model gaits, i.e., the ones that best matched the data, were obtained when the model runners minimized the impulse they experience from the ground as well as the mechanical work done by their leg muscles. Using this objective function, the gait and thus performance of running under different shoe conditions can be predicted …

Data-driven control of COVID-19 in buildings: a reinforcement-learning approach

Authors

Ashkan Haji Hosseinloo,Saleh Nabi,Anette Hosoi,Munther A Dahleh

Journal

IEEE Transactions on Automation Science and Engineering

Published Date

2023/9/27

In addition to its public health crisis, COVID-19 pandemic has led to the shutdown and closure of workplaces with an estimated total cost of more than $16 trillion. Given the long hours an average person spends in buildings and indoor environments, this research article proposes data-driven control strategies to design optimal indoor airflow to minimize the exposure of occupants to viral pathogens in built environments. A general control framework is put forward for designing an optimal velocity field and proximal policy optimization, a reinforcement learning algorithm is employed to solve the control problem in a data-driven fashion. The same framework is used for optimal placement of disinfectants to neutralize the viral pathogens as an alternative to the airflow design when the latter is practically infeasible or hard to implement. We show, via computational simulations, that the control agent learns the optimal policy …

Parameterized shape adaptive materials for sportswear

Authors

Jennifer Beem,Iain Hannah,AE Hosoi

Journal

International Journal of Clothing Science and Technology

Published Date

2023/9/5

PurposeConventional sportswear design does not take into account body size changes that many individuals experience (e.g. through pregnancy, puberty, menstruation, etc.). This paper aims to detail both the construction of a novel wearable shape-adaptive composite and a new meso-scale material design method, which enables the optimal creation of these structures.Design/methodology/approachThis work reports the development of a predictive computational model and a corresponding design tool, including results of a tensile testing protocol to validate their outputs. A mathematical model was developed to explore the geometric parameter space of a bi-stable composite system, which then feeds into an optimization design tool.FindingsThe authors found that it is possible to fabricate shape-adaptive composites via 3D printing bi-stable structures, and adhering them to a base textile. Experimental mechanical …

Beyond fairness: Reparative algorithms to address historical injustices of housing discrimination in the US

Authors

Wonyoung So,Pranay Lohia,Rakesh Pimplikar,AE Hosoi,Catherine D'Ignazio

Published Date

2022/6/21

Fairness in Machine Learning (ML) has mostly focused on interrogating the fairness of a particular decision point with assumptions made that the people represented in the data have been fairly treated throughout history. However, fairness cannot be ultimately achieved if such assumptions are not valid. This is the case for mortgage lending discrimination in the US, which should be critically understood as the result of historically accumulated injustices that were enacted through public policies and private practices including redlining, racial covenants, exclusionary zoning, and predatory inclusion, among others. With the erroneous assumptions of historical fairness in ML, Black borrowers with low income and low wealth are considered as a given condition in a lending algorithm, thus rejecting loans to them would be considered a “fair” decision even though Black borrowers were historically excluded from …

Simple control for complex pandemics

Authors

Sarah C Fay,Dalton J Jones,Munther A Dahleh,Anette E Hosoi

Published Date

2021/12/14

The COVID-19 pandemic began nearly two years ago, yet schools, businesses, and other organizations are still struggling to keep the risk of disease outbreak low while returning to (near) normal functionality. Observations from this past year suggest that this goal can be achieved through the right balance of mitigation strategies, which may include some combination of mask use, vaccinations, viral testing, and contact tracing. The choice of mitigation measures will be uniquely based on the needs and available resources of each organization. This article presents practical guidance for creating these policies based on an analytical model of disease spread that captures the combined effects of each of these interventions. The resulting guidance is tested through simulation across a wide range of parameters and through synthesis of infection case data on college campuses.

Estimating the filtration efficacy of cloth masks

Authors

Xinyu Mao,Anette E Hosoi

Journal

Physical Review Fluids

Published Date

2021/11/5

The current pandemic has spurred a great deal of debate about the use of cloth masks as effective alternatives to medical masks for the general public. Despite an abundance of experimental studies on the filtration of aerosols by cloth masks, there is currently a lack of analytical understanding to predict mask performance a priori. In this study, we establish a quantitative model for the pressure drop across woven heterogeneous cloth masks and their filtration efficiencies for aerosols with aerodynamic diameters less than 1 μ m. To compare the intrinsic filtration capabilities of diverse materials, we introduce a filtration quality factor. Finally, we present a decision map to illustrate the tradeoffs between filtration efficiency and breathability and to provide practical guidance on the purchase of cloth masks. For the most commonly used cotton, polyester, and polypropylene masks, the mechanical filtration capability is fairly …

Simple control for complex pandemics (preprint)

Authors

Sarah C Fay,Dalton J Jones,Munther A Dahleh,AE Hosoi

Published Date

2020

The COVID-19 pandemic began over two years ago, yet schools, businesses, and other organizations are still struggling to keep the risk of disease outbreak low while returning to (near) normal functionality. Observations from these past years suggest that this goal can be achieved through the right balance of mitigation strategies, which may include some combination of mask use, vaccinations, viral testing, and contact tracing. The choice of mitigation measures will be uniquely based on the needs and available resources of each organization. This article presents practical guidance for creating these policies based on an analytical model of disease spread that captures the combined effects of each of these interventions. The resulting guidance is tested through simulation across a wide range of parameters and used to discuss the spread of disease on college campuses.

Flagellar kinematics reveals the role of environment in shaping sperm motility

Authors

Jeffrey S Guasto,Jonathan B Estrada,Filippo Menolascina,Lisa J Burton,Mohak Patel,Christian Franck,AE Hosoi,Richard K Zimmer,Roman Stocker

Journal

Journal of the Royal Society Interface

Published Date

2020/9/30

Swimming spermatozoa from diverse organisms often have very similar morphologies, yet different motilities as a result of differences in the flagellar waveforms used for propulsion. The origin of these differences has remained largely unknown. Using high-speed video microscopy and mathematical analysis of flagellar shape dynamics, we quantitatively compare sperm flagellar waveforms from marine invertebrates to humans by means of a novel phylokinematic tree. This new approach revealed that genetically dissimilar sperm can exhibit strikingly similar flagellar waveforms and identifies two dominant flagellar waveforms among the deuterostomes studied here, corresponding to internal and external fertilizers. The phylokinematic tree shows marked discordance from the phylogenetic tree, indicating that physical properties of the fluid environment, more than genetic relatedness, act as an important selective …

Body scan processing, generative design, and multiobjective evaluation of sports bras

Authors

Audrey Bosquet,Caitlin Mueller,AE Hosoi

Journal

Applied Sciences

Published Date

2020/9/3

Sports bras are critical to the comfort and performance of female athletes, yet mechanical models of sports bras are generally not used to guide their design. Typically, assessing any sports bra’s performance requires time-consuming and expensive biomechanical testing, which limits the number of designs considered. To more broadly advance knowledge on how different design properties of sports bras affect their performance, this paper presents a new design framework to explore and evaluate the sports bra design space. The framework incorporates methods for body scan analysis, fast simulation, design generation, and performance evaluation. Using these methods together enables the rapid exploration of hundreds, or thousands, of designs—each one having been evaluated on key metrics related to sports bra performance, namely, range of motion and average pressure. With this framework, designers can potentially discover a diverse set of new, high-performing sports bra concepts, as well as gain insights into how design decisions affect performance.

See List of Professors in A. E. Hosoi University(Massachusetts Institute of Technology)

A. E. Hosoi FAQs

What is A. E. Hosoi's h-index at Massachusetts Institute of Technology?

The h-index of A. E. Hosoi has been 21 since 2020 and 29 in total.

What are A. E. Hosoi's top articles?

The articles with the titles of

When is it Profitable to Make a Product Sustainable? Insights from a Decision‐Support Tool

Modeling Running via Optimal Control for Shoe Design

Data-driven control of COVID-19 in buildings: a reinforcement-learning approach

Parameterized shape adaptive materials for sportswear

Beyond fairness: Reparative algorithms to address historical injustices of housing discrimination in the US

Simple control for complex pandemics

Estimating the filtration efficacy of cloth masks

Simple control for complex pandemics (preprint)

...

are the top articles of A. E. Hosoi at Massachusetts Institute of Technology.

What are A. E. Hosoi's research interests?

The research interests of A. E. Hosoi are: Fluid dynamics, biomechanics

What is A. E. Hosoi's total number of citations?

A. E. Hosoi has 4,250 citations in total.

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