Matthew Jörke
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ABOUT
I'm a fourth year Computer Science PhD student at Stanford University, where I am co-advised by Prof. Emma Brunskill and Prof. James Landay. My research is at the intersection of human-computer interaction and machine learning, with an emphasis on studying and designing technology to promote health and wellbeing.

I completed my undergraduate degree at UC Berkeley, where I most recently worked with David Bamman on natural language processing in the digital humanities. Previously, I worked with Cesar Torres in the Hybrid Ecologies Lab on human-computer interaction, where we characterized tacit knowledge in creative processes using time-series clustering.

PUBLICATIONS
Adaptive Interventions with User-Defined Goals for Health Behavior Change.
Aishwarya Mandyam*, Matthew Jörke*, Barbara E. Engelhardt, Emma Brunskill ML4H Findings ‘23.
A Workshop-Based Method for Navigating Value Tensions in Collectively Speculated Worlds. website
Nava Haghighi*, Matthew Jörke*, Yousif Mohsen, Andrea Cuadra, James A. Landay. DIS ‘23.
Pearl: A Technology Probe for Machine-Assisted Reflection on Personal Data.
Matthew Jörke, Yasaman S. Sefidgar, Tallie Massachi, Jina Suh, Gonzalo Ramos. IUI ‘23.
Lessons Learned for Data-Driven Implementation Intentions with Mental Contrasting.
Yasaman S. Sefidgar, Matthew Jörke, Jina Suh, Koustuv Saha, Shamsi Iqbal, Gonzalo Ramos, Mary Czerwinski. CHI Extended Abstracts ‘23.
Explanations Can Reduce Overreliance on AI Systems During Decision-Making.
Helena Vasconcelos, Matthew Jörke, Madeleine Grunde-McLaughlin, Tobias Gerstenberg, Michael S. Bernstein, Ranjay Krishna. CSCW ‘23.
Simple Regret Minimization for Contextual Bandits Using Bayesian Optimal Experimental Design.
Matthew Jörke, Jonathan Lee, Emma Brunskill. ICML ‘22 ReALML Workshop.
When Do XAI Methods Work? A Cost-Benefit Approach to Human-AI Collaboration.
Helena Vasconcelos, Matthew Jörke, Madeleine Grunde-McLaughlin, Tobias Gerstenberg, Michael S. Bernstein, Ranjay Krishna. CHI ‘22 TrAIT Workshop.
Assessing Dataset Quality using Optimal Experimental Design for Linear Contextual Bandits.
Matthew Jörke, Tong Mu, Jonathan Lee, Emma Brunskill. RLDM ‘22.
Attending to Long-Distance Document Context for Sequence Labeling.
Matthew Jörke, Jon Gillick, Matthew Sims, David Bamman. Findings of ELMNP ‘20.
Hybrid Microgenetic Analysis: Using Activity Codebooks to Identify and Characterize Creative Process.
Cesar Torres, Matthew Jörke, Emily Hill, Eric Paulos. C&C ‘19.
PROJECTS
© Matthew Jörke, 2019