Kosa Goucher-Lambert

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kosaobfuscate@berkeley.edu

Kosa Goucher-Lambert is an Assistant Professor of Mechanical Engineering at the University of California, Berkeley. He is an Affiliate Faculty member in the Jacobs Institute of Design Innovation and the Berkeley Institute of Design. Kosa received his B.A (2011) in Physics from Occidental College, and his M.S. (2014) and Ph.D. (2017) in Mechanical Engineering from Carnegie Mellon University. His primary research interests focus on understanding decision-making processes in engineering design using a combination of mathematical analyses, computational modeling, human cognitive studies, and neuroimaging approaches. Kosa is a recipient of the National Science Foundation CAREER Award, 2019 Excellence in Design Science Award, and several best paper awards from the American Society of Mechanical Engineers and the Design Society. Kosa primarily teaches courses on integrated product development, with an emphasis on complex socio-technical challenges.

Papers

The Evolution and Impact of Human Confidence in Artificial Intelligence and in Themselves on AI-Assisted Decision-Making in Design

Designing Privacy Risk Frameworks for Evolving Cyber-Physical Social Systems: Knowledge Gaps Illuminated by the Case of Autonomous Vehicles and Bystander Privacy

Investigating How Engineers and Designers Communicate Design Rationale

Capturing Designers' Experiential Knowledge in Scalable Representation Systems: A Case Study of Knowledge Graphs for Product Teardowns

Investigating the Roles of Expertise and Modality in Designers' Search for Inspirational Stimuli

Enabling multi-modal search for inspirational design stimuli using deep learning

Inspirational Stimuli Attain Visual Allocation: Examining Design Ideation with Eye-tracking

How does machine advice influence design choice? The effect of error on design decision making

Exploring designers’ encounters with unexpected inspirational stimuli

Like a Moodboard, but More Interactive - The Role of Expertise in Designers’ Mental Models and Speculations on an Intelligent Design Assistant

Design Strategies that Work: How Engineers Use Sequential Decision Making to Improve Design Performance in Concept Selection

Inspirational Stimuli Improve Idea Fluency during Ideation: A Replication and Extension Study with Eye-Tracking

Do human and computational evaluations of similarity align? An empirical study of product function

Evaluating Quantitative Measures for Assessing Functional Similarity in Engineering Design

Human confidence in artificial intelligence and in themselves: The evolution and impact of confidence on adoption of AI advice

Factors Impacting Highly Innovative Designs - Idea Fluency, Timing, and Order

Connecting Design Actions, Reasoning, and Outcomes in Concept Selection

Examining Goal Congruence on Engineering Design and Innovation Student Teams

Multi-modal Search for Inspirational Examples in Design

Aligning Human and Computational Evaluations of Functional Design Similarity

Framing and Tracing Human-Centered Design Teams' Method Selection: An Examination of Decision-Making Strategies

Design for Cybersecurity (DfC) Cards: A Creativity-Based Approach to Support Designers’ Consideration of Cybersecurity

The Role of Idea Fluency and Timing on Highly Innovative Design Concepts

Method Selection in Human-Centered Design Teams: An Examination of Decision-Making Strategies

A Comparison of Vector and Network-based Measures for Assessing Design Similarity

Adaptive Inspirational Design Stimuli - Using Design Output to Computationally Search for Stimuli that Impact Concept Generation

Wisdom of Micro-Crowds in Evaluating Solutions to Esoteric Engineering Problems

A Neuroimaging Investigation of Design Ideation With and Without Inspirational Stimuli- Understanding the Meaning of Near and Far Stimuli

Crowdsourcing Inspiration - Using Crowd Generated Inspirational Stimuli to Support Designer Ideation