- You can email me at drc44 aat cornell ddot edu.
- I run the Reimagination Lab.
- I'm @cosleydr on Twitter and ForteTuba on Facebook.
- I also write Lightly Filtered, a blog about HCI and academic life.
Note that I'm away from Cornell for calendar year 2016 and the email address above is the best way to get hold of me for research and Cornell-related business.
My main interest for a long time has been helping people make sense of and manage information, both individually and as groups. More recently this has grown to include leveraging people's current behaviors online, along with social science theory, to produce individual and social goods that otherwise would not have been created.
More details on what this means are available in my research statement. For folks who want the overview of publications and collaborators, you can download my CV or my publications, or visit my Google Scholar profile.
These interests lead me into a number of cool domains; below are a few of the major ongoing themes. More details, and other projects, are available at the Reimagination Lab website.
This project started from a question Amit Sharma asked: What if recommender systems were designed, not for individuals and purchasing, but from the ground up for social networks? What kinds of questions, use cases, metrics, and algorithms would emerge, and how would they be different from traditional recommender systems research?
One set of questions we've focused on is at the micro-level of sharing between individuals: how do people choose to share particular items with particular audiences, and what makes people accept the things other people share? Social influence, homophily, trust, and personal preferences all likely affect these decisions, making it important to account for them in models of sharing behavior and systems that support it.
A second set is at the macro level of how items diffuse in social networks: what effect do those micro-level choices have on the patterns of preferences and diffusion we observe in real networks, and are there regularities between networks? We'd like to build nuanced diffusion models that account for these micro-level choices and explain the diffusion observed in networks better than currennt models.
This project is born out of Bin Xu's interest in ephemeral social networks and my social awkwardness in meeting other people. Borrowing from Terveen and McDonald's social matching framework, the problem isn't so much finding who to meet as in faciliating the interactions.
Bin is taking facilitating to mean giving people ways to overcome barriers to meeting others: resisting shyness, finding an occasion, having things to talk about. The current idea is that a facilitating system (providing occasion) at an event such as a conference could use information from social media profiles (having things to talk about) to make third-party introductions for people (overcoming shyness), not unlike the ones people make all the time. We'll see if it works, and what's next. :)
The project I've worked on the most is called Pensieve. It has an intense, personal inspiration: I rarely remember the past, and mostly I remember bad things. However, people (including me) often post about their past on social media, and because of norms there, tend to post good things.
Pensieve is about understanding more about what people put into social media and how technologies might use that information to improve people's well-being. On the understanding side, this includes knowing how and why people disclose information about themselves and how they currently use it to understand themselves, their friends, and their relationships.
On the technology side, this includes supporting reminiscing, visualizing one's past behavior, positive psychology exercises, and other systems for supporting reflection that we hope to build in the future.
Note that I will be away from Cornell for calendar year 2016; thus, I'm unlikely to take on new folks right now. That said...
Motivated, passionate students of any level who like this work and want to get involved are always fun to talk to. Drop me an e-mail that makes clear why you're interested, what your goals are, and what you want to contribute. It won't always work out--at times I have more or less need, funding, and advising energy--but I'm generally happy to chat.
I care deeply about teaching both undergraduate and graduate students. Most students and observing professors regard me as a solid classroom teacher, and I try to be a supportive, flexible advisor. I try to give students space to take assignments and projects in directions of their own interest, plenty of hands-on work both as individuals and groups, and copious support.
I am away from Cornell and thus not teaching courses in calendar year 2016.
- INFO 6940, Finding, Filtering, and Sharing Information, taught Fall 2015. This course was aimed at giving MPS students a broad overview over systems where people interact around information, from technical, design, evaluation, and social perspectives.
- INFO 6010, Computational Methods for Information Science Research, taught Spring 2015 and Spring 2014. This evolved from INFO 4307/6307, Learning from Web Data, taught Fall 2011 and Fall 2009.
- INFO 6940, Readings in Recommender Systems, taught Spring 2014. PhD student Amit Sharma took the lead in developing and teaching the class, and I had his back.
- INFO/CS 1300, Introduction to Web Design and Programming, taught Fall 2014 and Fall 2013.
- INFO/COMM 3450 + INFO 4940, Human Computer Interaction, taught Fall 2012 (syllabus and Piazza site), Fall 2010, Spring 2008, and Spring 2007.
- INFO/COMM 6400, Advanced Human Computer Interaction, taught Spring 2012 (syllabus and Piazza site). I also taught a combined 4400/6400 version in Fall 2010, Fall 2008, and Fall 2007.
- INFO 6940, IS PhD professionalization, taught Fall 2011 as an experiment for helping the first-year PhDs think about school.
- INFO/CS 2300, Intermedate Web Design and Programming, taught Spring 2011.
- Introduction to Operating Systems, taught 2005 at University of Minnesota.
- Software Design, taught 2000 and 1999 at James Madison University.
- Algorithm Development, taught 2000 and 1999 at JMU.
- Software Engineering, taught 1999 at JMU.
- Being Productive with Computers, taught 1999 and 1998 at JMU.
A typical teaching scene from the 2012 version of HCI (pic by Chelsea Howe).