Matthew Jörke
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ABOUT
I'm a fifth year Computer Science PhD candidate 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
Supporting Physical Activity Behavior Change with LLM-Based Conversational Agents.
Matthew Jörke, Shardul Sapkota, Lyndsea Warkenthien, Niklas Vainio, Paul Schmiedmayer, Emma Brunskill, James Landay arXiv pre-preprint. 2024.
Adaptive Interventions with User-Defined Goals for Health Behavior Change.
Aishwarya Mandyam*, Matthew Jörke*, William Denton, Barbara E. Engelhardt, Emma Brunskill CHIL 2024.
“They Make Us Old Before We’re Old”: Designing Ethical Health Technology with and for Older Adults.
Jianna So, Samantha Estrada, Matthew Jörke, Eva Bianchi, Maria Wang, Nava Haghighi, Kristen L. Fessele, James A. Landay, Andrea Cuadra. CSCW ‘24.
Improving Work-Nonwork Balance with Data-Driven Implementation Intention and Mental Contrasting.
Yasaman S. Sefidgar, Matthew Jörke, Jina Suh, Koustuv Saha, Shamsi Iqbal, Gonzalo Ramos, Mary Czerwinski. CSCW ‘24.
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.
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.
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