Brown Bag Lunch Schedule

The HCIL has an open, semi-organized weekly "Brown Bag Lunch (BBL)" every Thursday from 12:30-1:30pm in HCIL (2105 Hornbake, South Wing). The topics range from someone's work, current interests in the HCIL, software demos/reviews, study design, proposed research topics, introductions to new people, etc. The BBL is the one hour a week where we all come together--thus, it’s a unique time for HCIL members with unique opportunities to help build collaborations, increase awareness of each other’s activities, and generally just have a bit of fun together. There is no RSVP; simply show up!

If you would like to give or suggest a talk, presentation, workshop, etc., send an email to BBL student co-coordinators Aashrey Sharma (aashreys@umd.edu) or Aravind JR (aravind@umd.edu). In the email, briefly describe the topic and preferred dates.

To be notified about upcoming events, please subscribe to one of these mailing lists.

Fall 2018 Schedule

Date	Leader	Topic
08/30/2018	Student Townhall	Expand Instead of the regular BBL, there will be an internal HCIL-students-only townhall meeting instead. .
09/06/2018	BBL Student Co-coordinators	Expand Come, network, make introductions, and share what you are working on.
09/13/2018	Joel Chan, Tammy Clegg University of Maryland, College Park	Expand TBA .
09/20/2018	Joel Zhang University of Maryland, College Park	Expand Research proposal centered around pain tracking and sharing. .
03/22/2017	No Brown Bag, Cancelled.
10/4/2018	Brian Ondov, Sriram Karthik Badam University of Maryland, College Park	Expand Brian’s paper talks about Evaluating Visual Comparison and seeks to understand how different encodings of data can drastically affect how we perceive quantities. More information about this project is available at http://hcil.umd.edu/visualcomparison/. Karthik’s paper is about a computing platform called Vistrates which seeks to unify the fragmented analytical workflows employed by users to analyze a group of visualizations created in different tools. .
10/11/2018	Polly Lee O'Rourke University of Maryland, College Park	Expand Improving language learning using brain simulation. .
10/18/2018	Andrea Batch University of Maryland, College Park	Expand Information Olfactation: Harnessing Scent to Convey Data Olfactory feedback for analytical tasks is a virtually unexplored area in spite of the advantages it offers for information recall, feature identification, and location detection. We have introduced the concept of information olfactation as the fragrant sibling of information visualization, and this talk will cover our theoretical model of how scent can be used to convey data. Building on a review of the human olfactory system and mirroring common visualization practice, we propose olfactory marks, the substrate in which they exist, and their olfactory channels that are available to designers. To exemplify this idea, we present viScent: A six-scent stereo olfactory display capable of conveying olfactory glyphs of varying temperature and direction, as well as a corresponding software system that integrates the display with a traditional visualization display, along with three applications that make use of the viScent system. .
10/25/2018	Student Townhall	Expand Research speed-dating .
11/01/2018	Joohee Choi University of Maryland, College Park	Expand Will Too Many Editors Spoil The Tag? Conflicts and Alignment in Q&A Categorization (CSCW Practice Talk) .
11/08/2018	Alina Striner University of Maryland, College Park	Expand Learning in the Holodeck: the Role of Multisensory Cues on Pattern Recognition in VR Designing for multiple senses has the capacity to improve virtual realism, extend our ability to process information, and more easily transfer knowledge between physical and digital environments. HCI researchers are beginning to explore the viability of integrating multisensory media (“multimedia”) into virtual experiences, however research has yet to consider whether mulsemedia truly enhances pattern recognition in virtual reality (VR). In the context of citizen science watershed habitat training, our research asks, how does realism affect observation skills in VR? Within this domain, we build a multisensory system that allows users to feel (wind, thermal, humidity) and smell landscape and environmental conditions. We then compare and report on how users make observations and infer patterns between 2 stream habitats in VR, with and without the multisensory information. Our findings reveal that multisensory information improved the number of high-level, mid-level and low-level observations participants made, and positively impacted engagement and immersion. .
11/15/2018	Student Townhall	Expand Research speed dating. .
03/22/2017	No Brown Bag, Thanksgiving Break.
11/29/2018	Lelani Battle University of Maryland, College Park	Expand A Characterization Study of Exploratory Analysis Behaviors in Tableau Exploratory visual analysis (EVA) is an interactive process comprising both focused tasks and more open-ended exploration. Visual analysis tools aim to facilitate this process by enabling rapid specification of both data transformations and visualizations, using a combination of direct manipulation and automated design. With a better understanding of users’ analysis behavior, we might improve the design of these visualization tools to promote effective outcomes. In this talk, I will present our recent work on characterizing the EVA process. We contribute a consistent definition of EVA through review of the relevant literature, and an empirical evaluation of existing assumptions regarding how analysts perform EVA. We present the results of a study where 27 Tableau users answered various analysis questions across 3 datasets. We measure task performance, identify recurring patterns across participants’ analyses, and assess variance from task specificity and dataset. We find striking differences between existing assumptions and the collected data. Participants successfully completed a variety of tasks, with over 80% accuracy across focused tasks with measurably correct answers. The observed cadence of analyses is surprisingly slow compared to popular assumptions from the database community. We find significant overlap in analyses across participants, showing that EVA behaviors can be predictable. Furthermore, we find few structural differences between open-ended and more focused analysis tasks. Finally, I will discuss the implications of our findings for the design of effective data analytics systems, and highlight several promising directions for future study. .
12/06/2018	Student Townhall	Expand TBA .
12/13/2018	Cookie Exchange	Expand We encourage you to make/buy cookies (or some related treat) and create individual bags (about six cookies in each bag, and about 4-6 bags). Then bring them in labeled on 12/13 and you can pick bags from other people to take home or eat on the spot. However, you do not need to make cookies to attend! All are welcome to come and hang out. .

Spring 2018 Schedule

Date	Leader	Topic
01/25/2018	Kickoff to a new Semester!	Expand Come, network, make introductions, and share what you are working on Please come to our first BBL of the Spring 2018 semester to introduce yourself and share what you're working on in the coming semester. The first BBL will be for us to network with each other and kickoff a great new semester.
02/01/2018	Bahador Saket Georgia Tech, Atlanta	Expand Visualization by Demonstration Abstract: A commonly used interaction paradigm in most visualization tools is manual view specification. Tools implementing manual view specification often require users to manually specify visual properties through GUI operations on collections of visual properties and data attributes that are presented visually on control panels. To interact with tools implementing manual view specification users need to understand the potentially complex system parameters being controlled. Additionally, in such tools, users need to constantly shift their attention from the visual features of interest when interacting. In this talk, I present an alternative interaction paradigm for visualization construction and data exploration called visualization by demonstration. This paradigm advocates for a different process of visualization construction. I will also discuss the trade-offs between these interaction paradigms based on the data collected from an empirical study. I will then discuss applications of the "by demonstration’" paradigm in other areas in data visualization. Bio: Bahador Saket is a third-year Ph.D. student at Georgia Tech, where he works with Dr. Alex Endert. His current research focuses on the design of interaction techniques for visualization construction and visual data exploration. Prior to joining Georgia Tech, Bahador worked at different research labs including Microsoft Research, CNS Research Center, and NUS-HCI Lab. He has published over 12 peer-reviewed articles in the leading journals and conferences in the field of human-computer interaction and data visualization such as IEEE Transactions on Visualization and Computer Graphics (TVCG), Computer Graphics Forum, CSCW, UIST, and MobileHCI.
02/08/2018	Elissa Redmiles University of Maryland, College Park	Expand Dancing Pigs or Security? Measuring the Rationality of End-User Security Behavior Abstract: Accurately modeling human decision-making in security is critical to think about when, why, and how to recommend that users adopt certain secure behaviors. We used behavioral economics experiments to model the rationality of end-user security decision-making in a realistic online experimental system simulating a bank account. We ask participants to make a financially impactful security choice, in the face of transparent risks of account compromise and benefits offered by an optional security behavior (two-factor authentication). We find that more than 50% of our participants made rational (e.g., utility optimal) decisions, and we find that participants are more likely to behave rationally in the face of higher risk. Additionally, we confirm that users are boundedly rational: they make decisions based on some risks and context, but not others, and we can model their behavior well as a function of these factors. Finally, we show that a “one-size-fits-all” emphasis on security can lead to market losses, but that adoption by a subset of users with higher risks or lower costs can lead to market gains. Bio: Elissa Redmiles is a Ph.D. student at the University of Maryland in Computer Science. Her research focuses on using computational and social science methodologies to understand and improve users' privacy and security learning processes, behavior, and perceptions. She is the recipient of an NSF Graduate Research Fellowship, a National Science Defense and Engineering Graduate Fellowship, and a Facebook Fellowship. Prior to pursuing her Ph.D., Elissa held Marketing Management and Software Engineering roles at IBM and was a Data Science for Social Good Fellow at the University of Chicago.
02/15/2018	Erin Peters-Burton George Mason University, Fairfax, VA	Expand Building Student Self-Awareness of Learning to Enhance Diversity in the Sciences Abstract: Many students are being left out of pursuing further studies in science because the current system of science education values students who learn via completion in an isolated, rather than collaborative way (Tobias, 1990). The stereotype of students who excel in science tend to be the ones who can conform to the institutional structure where the teacher is the sole source of knowledge (Friere, 2000). Through the idea of “Education as the Practice of Freedom” (hooks, 1994), the presentation will explain investigations that explore tangible ways to break down that stereotype. This research begins with the assumption that if teachers taught the ways science operates as a discipline, then students gain more power to construct their own scientific knowledge because they understand the “rules” of knowledge validation (Duschl, 1990). Learning how scientific knowledge is constructed and being self-aware of one’s own learning in science can help level the playing field so that students can do inquiry well (NRC, 1996; AAAS, 1993) and the science classroom will be a more inclusive, positive environment rather than relying on isolated competition for teaching. In this presentation, I will present an overview of research I have done over the past 10 years that focuses on helping students to become self-aware of their learning in science and how scientific knowledge is constructed. The work involves 8th grade students, undergraduates, graduate students, and professionals. The studies include constructs such as self-efficacy, motivation, metacognition, self-regulated learning, and visualization. Findings of the studies are synthesized into self-awareness priorities and how those constructs will ultimately impact social justice by providing more opportunities to see alternative perspectives and learn the “rules” of knowledge validation in science. As a result, students develop a sense of agency and an identity where anything is possible because they can learn independently in any situation. Bio: Erin E. Peters-Burton is the Donna R. and David E. Sterling Endowed Professor in the College of Education and Human Development at George Mason University. She has a B.S. in Physics from the University of Illinois, a M.Ed. in Educational Psychology and Social Foundations of Education from the University of Virginia, and a Ph.D. from George Mason University (VA) in Educational Psychology and Educational Research Methods. She has taught middle school and high school science and mathematics for 15 years prior to her academic work and was a National Board Certified Teacher in Early Adolescence Science. She has published in science education, teacher education, educational psychology, marine biology, geology education, history and philosophy of science, technology, educational leadership, and learning disability journals. Her book, Thinking Like Scientists: Using Metacognitive Prompts to Develop Nature of Science Knowledge, and her edited book, The STEM Road Map: A Framework for Integrated STEM Education have led to the curriculum series books from the National Science Teacher Association entitled, STEM Road Map for Elementary School, STEM Road Map for Middle School, and STEM Road Map for High School. In 2016 she was awarded the Association of Science Teacher Educators Outstanding Science Teacher of the Year in recognition of her work with the professional development of secondary science teachers.
02/22/2018	Norman Su Indiana University	Expand The Problem of Designing for Subcultures Abstract: Members of subcultures speak about and act with pervasive technologies in service to their distinct traditions. I will describe how outwardly subcultures maintain a unified front, yet inwardly are rich sites for compromise and confrontation over technology. I will highlight findings from work we have done with subcultures and, in particular, my own fieldwork with Irish traditional musicians. I will close by describing new design opportunities for technologies that acknowledge the remarkable solidarity and discord of subcultures. Bio: Norman Makoto Su is an Assistant Professor in the School of Informatics, Computing, and Engineering at Indiana University Bloomington. His research interests lie in human–computer interaction (HCI) and computer–supported cooperative work (CSCW). His Authentic User Experience (AUX) lab characterizes the relationship of technology with subcultures and designs systems to support their notion of authenticity. He received his Ph.D. in Information and Computer Science from the University of California, Irvine and a B.A. in Computer Science from the University of California, Berkeley. He was a postdoctoral research fellow in the School of Information and Library Studies at University College Dublin, Ireland. He has done internships at IBM, The Aerospace Corporation, and PARC.
03/01/2018	Ya-Wei Li Center for Conservation Innovation, Defenders of Wildlife	Expand Using Data and Technology to Save Endangered Species. Abstract: We will discuss how Defenders of Wildlife, a nonprofit wildlife conservation organization, is expanding its use of technology and data analytics to conserve endangered species. We will summarize our projects involving remote-sensing data to monitor wildlife habitat and compliance with conservation agreements; data mining of federal government decisions to build the largest public repository of text-searchable documents on the U.S. Endangered Species Act; natural language processing of those documents to improve public understanding of how our government conserves endangered species; use of data visualization tools to reveal patterns in large datasets; and other initiatives. We invite the audience to actively engage with us about how we can improve our work and offer ideas for future projects and potential collaborations. Bio: Ya-Wei (Jake) specializes in endangered species law, policy, and science. He leads the Center for Conservation Innovation at Defenders of Wildlife, which focuses on developing innovative and pragmatic strategies to conserve endangered and at-risk species. Before joining Defenders in 2010, Jake practiced environmental law in the private sector. Jake holds a B.S. from Drexel University and a J.D. from Cornell University Law School. At Cornell, Jake also completed graduate coursework in conservation biology and herpetology. Jacob works on linking science to Endangered Species Act policy. He works with others inside and outside of Defenders to make ESA-related data available and easily interpretable, so that policy makers and the public can make informed decisions about conservation. Before joining Defenders, Jacob was a postdoctoral fellow at University of Connecticut, and earned his Ph.D. from the University of Texas at Austin in 2013. From 2000-2008, Jacob was a field biologist with the U.S. Fish and Wildlife Service in New Mexico and Arizona, during which time he completed his Bachelor's degree in Conservation Ecology at Prescott College.
03/08/2018	Deok Gun Park University of Maryland, College Park	Expand Thinking, Autism and AGI Abstract: Despite recent advances in deep learning, we do not know yet how we can combine these application-specific models to build an artificial general intelligence (AGI). Furthermore, the data is becoming the bottleneck to scale these approaches for the multiple tasks. In this talk, I propose a theory of the thinking and a neural algorithm that can bootstrap intelligence with limited computational resources and data. This neural algorithm approximates the O(n3) parameter space of the thinking theory into the O(1) parameters to make learning tractable for the biological intelligent agents. I will explain this proposal by cognitive phenomenons that are observed in a human, such as infant language acquisition, visual and verbal thinking, personality, creativity, exploit-exploration trade off, dreaming, one-shot learning, abstract language. Bio: Deokgun Park is a Ph.D. candidate in the HCILab of the Department of Computer Science at the University of Maryland, College Park, being advised by Prof. Niklas Elmqvist. His research focuses on the computational methods for open-ended tasks. He completed M.S. in Interdisciplinary Engineering at Purdue University and M.S. in Biomedical Engineering at Seoul National University, where he obtained B.S. degree in Electrical Engineering at Seoul National University. He worked at the government research institute, industry research labs, and startups. He has published and licensed his patents to companies including Samsung Electronics.
03/15/2018	Clemens Klokmose Aarhus University, Denmark	Expand Shareable Dynamic Media: A revisit of the fundamentals of interactive computing Abstract: Developing interactive systems that support collaboration between people, distribution across heterogeneous devices and user appropriation is notoriously difficult. Today’s software rests on a foundation built for personal computing, and to properly support the aforementioned qualities we need to revisit this foundation. In this talk, I will present you with a vision called Shareable Dynamic Media, inspired by Alan Kay’s seminal vision of Personal Dynamic Media. I will present a prototype implementation of the vision called Webstrates, and demonstrate how it enables the development of software where distribution across devices, collaboration between people, and malleability and reprogrammability are the norm rather than the exception. I will show our latest project, Codestrates, that combines Webstrates with the literate computing approach of interactive notebooks. Bio: Clemens Nylandsted Klokmose is an associate professor in the development of advanced interactive systems at the Department of Digital Design and Information Studies, at the School of Communication and Culture, Aarhus University. He co-directs the Digital Creativity Lab that is part of the Center for Advanced Visualisation and Interaction (CAVI). Clemens has worked as a postdoc at Computer Science, Aarhus University and at Laboratoire de Recherche en Informatique, Université Paris-Sud. He has furthermore spent a year as a user interface specialist in the industry. Clemens received his PhD in Computer Science in 2009 from Aarhus University supervised by prof. Susanne Bødker. Clemens’ main interest is the fundamentals of interactive computing, particularly to support and understanding computing with multiple devices and multiple people. Many of his ideas are crystallised into the Webstrates platform (webstrates.net), which he leads the development of.
03/22/2017	No Brown Bag, Spring Break.
03/29/2018	Wei Bai University of Maryland, College Park	Expand Understanding User Tradeoffs for Search in Encrypted Communication Abstract: End-to-end message encryption is the only way to achieve absolute message privacy. However, searching over end-to-end encrypted messages is complicated. Several popular instant messaging tools (e.g., WhatsApp, iMessage) circumvent this inconvenience by storing the search index locally on the devices. Another approach, called searchable encryption, allows users to search encrypted messages without storing the search index locally. These approaches have inherent tradeoffs between usability and security properties, yet little is known about how general users value these tradeoffs, especially in the context of email rather than instant messaging. In this paper, we systematize these tradeoffs in order to identify key feature differences. We use these differences as the basis for a choice-based conjoint analysis experiment focused on email (n=160), in which participants make a series of choices between email services with competing features. The results allow us to quantify the relative importance of each feature. We find that users indicate high relative importance for increasing privacy and minimizing local storage requirements. While privacy is more important overall, local storage is more important than adding additional marginal privacy after an initial improvement. These results suggest that local indexing, which provides more privacy, may often be appropriate for encrypted email, but that searchable encryption, which limits local storage, may also hold promise for some users. Bio: Wei Bai is a PhD student in the Department of Electrical and Computer Engineering at the University of Maryland, advised by Prof. Michelle L. Mazurek. His research interests include network security and privacy with an emphasis on human factors, and his dissertation is about user perceptions of and attitudes toward encrypted communication. He obtained his MS in electrical and computer engineering from the University of Maryland. Contact him at wbai@umd.edu.
04/05/2018	Eun-Kyoung Choe University of Maryland, College Park	Expand Designing A Flexible Personal Data Tracking Tool Abstract: We now see an increasing number of self-tracking apps and wearable devices. Despite the vast number of available tools, however, it is still challenging for self-trackers to find apps that suit their unique tracking needs, preferences, and commitments. In this talk, I will present OmniTrack, a mobile self-tracking system, which enables self-trackers to construct their own trackers and customize tracking items to meet their individual tracking needs. OmniTrack leverages a semi-automated tracking approach that combines manual and automated tracking methods. From a deployment study, we showed how participants used OmniTrack to create, revise, and appropriate trackers—ranging from a simple mood tracker to a sophisticated daily activity tracker. I will discuss how to further improve OmniTrack by incorporating multimodal interactions, providing more appropriate visualizations on a mobile device, and supporting researchers' unique data collection needs. Bio: Eun Kyoung Choe (http://eunkyoungchoe.com) is an Assistant Professor in the College of Information Studies at University of Maryland, College Park. Her primary research areas are in the fields of Human-Computer Interaction and Health Informatics. She examines the design and evaluation of personal informatics tools to empower individuals—including patients, caregivers, clinicians, and those who wish to engage in self-tracking—to make positive behavior changes through fully leveraging their personal data. She explores this topic in various contexts, including sleep and productivity, patient-clinician communication and data sharing, and personal data insights and visualization. Her past and current research has been funded by the National Science Foundation, Microsoft Research, and the Google Anita Borg Scholarship. She received her PhD in Information Science from University of Washington, MS in Information Management and Systems from University of California, Berkeley, and BS in Industrial Design from KAIST, Korea.
04/12/2018	CHI practice talks	Expand Combining smartwatches with large displays for visual data exploration by Karthik Badam and Tom Horak TBD
04/19/2018	Hernisa Kacorri University of Maryland, College Park	Expand Accessibility and Assistive Technologies at the Intersection of Users and Data Abstract: Advances in artificial intelligence enable us to address key social issues. However, to see the benefit of this technology in many real-world applications, an integrative approach is necessary; effective solutions consist of a pipeline of processes or tasks involving both humans and machines. My research has integrated human computer interaction (HCI) techniques and data-driven methods applied to human data to steer technological innovations for people with visual impairments and for people who are deaf or hard-of-hearing. In this talk, I will provide an overview of my research program, and I will demonstrate the effectiveness of integrating machine learning and HCI methodologies with two concrete examples: i) teachable object recognizers trained by blind users, and ii) facial expression synthesis in sign language animations. Bio: Hernisa Kacorri is an Assistant Professor in the College of Information Studies and holds an affiliate appointment in the Computer Science and the Human-Computer Interaction Lab at University of Maryland, College Park. She received her Ph.D. in Computer Science in 2016 from The Graduate Center at City University of New York, and has conducted research at National and Kapodistrian University of Athens, IBM Research-Tokyo, Lawrence Berkeley National Lab, and Carnegie Mellon University. Her research focuses on data-driven technologies that address human challenges, faced due to health or disability, with an emphasis on rigorous, user-based experimental methodologies to assess impact. Hernisa is a recipient of a Mina Rees Dissertation Fellowship in the Sciences, an ACM ASSETS best paper finalist, and an CHI honorable mention award. She has been recognized by the Rising Stars in EECS program of CMU/MIT.
04/26/2018	Chi-Young Oh University of Maryland, College Park	Expand Small Worlds in a Distant Land: International Newcomer Students' Local Information Behavior in Unfamiliar Environments Abstract: International students are a rapidly growing sub-population of students, and the United States, as a top destination, has hosted students from 218 different countries. However, as with other international newcomers, these students face various types of challenges in a new country. Studies have reported the challenges this population faces in regard to cultures, academic systems, and general adjustments, but research is less clear about the challenges they face in terms of information behaviors during adjustment to a new country. This study addresses the information behaviors of international newcomer students in the context of adjustment to new local environments; that is, their local information behavior (LIB). Specifically, drawing on prior work and theories, this research conceptualizes the idea of "socio-national context," the degree to which there are individuals from the same country available in one's local environment, as a factor influencing international newcomer students’ information behavior. Through the findings from this longitudinal mixed-method study of international and U.S. graduate students in different socio-national contexts, it is argued that information behavior theories and models need to account for people's socio-national contexts if they are to inform research involving international newcomer students and provide insights on designing systems and services for all international newcomer students, especially those from countries that tend to be less well-represented among international students in a host country. Bio: Chi Young Oh is a doctoral candidate at the University of Maryland, College Park's College of Information Studies. His areas of research span information behavior, human-computer interaction, health informatics, and community informatics, and his dissertation research examines international newcomer students' information behaviors during adjustment to a host country. Chi Young holds an MS in Information Science (with a concentration in Human-Computer Interaction) from the University of North Carolina at Chapel Hill, as well as a BA in Psychology, a BA in Library and Information Science, and a BBA in Business Administration from Yonsei University, Seoul, Korea. Prior to joining University of Maryland, he was a user experience researcher in the UX Lab of internet search portal Daum in South Korea and a new product planner and assistant marketing manager at LG Electronics.
05/03/2018	Amanda Lazar University of Maryland, College Park	Expand Rethinking technology for dementia Abstract: As the population ages, research is increasingly focused on conditions associated with growing older, such as cognitive and physical impairment. Technology is often presented as a solution for managing or treating these changes. This framing can position health conditions as problems to address through design and can neglect the complexity and positive aspects of older adulthood. In this talk, I draw on critical perspectives from Human-Computer Interaction and Gerontology. I describe ways in which technology can help us understand and challenge stereotypes around aging as well as cognitive impairment, and my ongoing and future work in this area. I will argue for a view of aging that takes into account the ways that technologies position older individuals and, in turn, the way that this view can inform the design of new technologies to enrich the experience of growing older. Bio: Amanda Lazar is an Assistant Professor in the College of Information studies at the University of Maryland, College Park. Her research is in the areas of Human-Computer Interaction and Health Informatics. She studies how technologies designed for health and wellbeing position and support marginalized populations. She received her PhD from the University of Washington in the Biomedical and Health Informatics program and her undergraduate degree in Electrical Engineering at the University of California, San Diego.
05/10/2018	Joel Chan University of Maryland, College Park	Expand Back to the Future: How people construct new creative ideas from old knowledge, and how technology can help Abstract: Where do good ideas come from? One answer is that they come from prior knowledge: for example, Thomas Edison leveraged his knowledge of phonographs to “do for the eye what the phonograph does for the ear”. Yet, much research on human creativity demonstrates that prior knowledge often constrains creativity. How do people construct new creative ideas from old knowledge? And (how) can technology help? In the first part of my talk, I will summarize empirical work I have done that advances theories of the conditions under which people successfully construct new creative ideas from prior knowledge. This empirical work shows that prior knowledge can inspire creativity when it is analogically related to the current problem. This insight informs the ongoing work I will discuss in the second part of my talk: developing information technologies that combine human and machine intelligence to more effectively support analogical reasoning over prior knowledge. Bio: Joel Chan is an Assistant Professor in the University of Maryland’s College of Information Studies (iSchool), and Human-Computer Interaction Lab (HCIL). His research and teaching focus on the intersection of people, information, and creativity. He wants to know how they (can best) combine to enable us to design the future(s) we want to live in. His work has been recognized with a Best Paper Award at the ASME Design Theory and Methodology conference, the Design Studies Award 2015, and supported by an NSF Doctoral Dissertation Improvement Grant. Previously, he was a Postdoctoral Research Fellow and Project Scientist in the Human-Computer Interaction Institute at Carnegie Mellon University. He received his PhD in Cognitive Psychology at the University of Pittsburgh.
05/17/2018	Rachel Kramer World Wildlife Fund	Expand WILDLABS.NET: the conservation technology network Abstract: WILDLABS.NET: the conservation technology network is a collaboration across organizations that provides online infrastructure to connect wildlife conservationists directly to technologists to support the informed integration of technology tools in conservation practice. Since 2015, WILDLABS has evolved into a thriving online community of over 2,300 experts around the globe who crowd-source ideas and information, share case studies and co-develop solutions to pressing conservation and research challenges. WILDLABS community members range from academics to tech sector professionals, NGO staff, field-based practitioners and makers. On our platform, ideas are shared in over 25 technology and conservation challenge-specific groups with over 450 active discussion threads. The community is also a hub for posting grant and job opportunities to enhance the uptake of technical expertise into wildlife conservation initiatives. In this talk, we’ll explore the latest happenings on WILDLABS and empower those with engineering and related expertise to share their abilities to help save species. Bio: Rachel Kramer is a wildlife crime expert at World Wildlife Fund with a decade of experience in field-based conservation, wildlife and natural resource trade monitoring, policy and technology solutions. With TRAFFIC, the wildlife trade monitoring network that is a strategic alliance of WWF and IUCN, Rachel has overseen projects in Africa and Asia and manages wildlife trade assessments—including in the United States—to support enforcement action and policy change. Through WWF’s Wildlife Crime Technology Project supported by a Google Global Impact Award, Rachel joined United for Wildlife partners in 2015 in founding WILDLABS.NET: the conservation technology network. Rachel got her start in conservation serving in the Peace Corps in Madagascar from 2006-2009, leading community-based monitoring and conservation projects until her evacuation in the coup. Her graduate research at the Yale School of Forestry & Environmental Studies focused on surveying wild species consumption and natural resource dependence in Park-bordering communities in Madagascar’s northeastern rainforest. Rachel is committed to harnessing the power of communities and technology to advance the sustainable use of natural resources for future generations.

Past Brown Bags

View the Past Brown Bag Lunch Schedules to learn more about prior talks.