FW: Inviting summer research applicants

[Keith Vander Linden]

An REU opportunity forwarded by Ken Arnold, last week’s faculty candidate.

---------- Forwarded message ---------
From: Daskalova, Nediyana <nediyana_daskalova at brown.edu<mailto:nediyana_daskalova at brown.edu>>
Date: Tue, Feb 12, 2019 at 3:29 PM
Subject: Inviting summer research applicants
To: <chi-labs at lists.csail.mit.edu<mailto:chi-labs at lists.csail.mit.edu>>

Hi everyone,

Our lab at Brown is looking for a couple of REU students for the summer. Feel free to forward to your students or anyone you know who might be interested. Thanks!

Here’s a description of our summer student positions:

The Brown Human-Computer Interaction group [https://urldefense.proofpoint.com/v2/url?u=https-3A__hci.brown.edu_&d=DwIGaQ&c=4rZ6NPIETe-LE5i2KBR4rw&r=zzLZx5LZ1XGPH-v7tq_ZkstXU36EEkGjVBQ57KQGE1c&m=bs96h2kl87IMsC8KtSG8WJYR7iMs716wAFWkVO4Brbg&s=rRoSzC4sO00bXyOcPR6alcVcHBiK_EAm37gECE_G4iU&e=<https://urldefense.proofpoint.com/v2/url?u=https-3A__hci.brown.edu_&d=DwMFaQ&c=4rZ6NPIETe-LE5i2KBR4rw&r=JhDWCBnuRQzO1O3Wnrh_-5Tq_lbjhPfN9dvv-oAoHUw&m=eoYASya4G1Znqz9XUtan6UVIVpqoyWbUvdZn4pIvNGY&s=XR7svhW6_HKfqqUlo-mMYxku-qoGN_vNHZMrBh_lbg0&e=>] is looking for two summer students for research on self-experiments, specifically working as part of a team on designing, developing and analyzing results from Self-E, an automatically guiding self-experiment app (see the description below for more detail). We are looking for students with experience in some of the following topics: self-tracking, mobile app development, visualization or design, machine learning or other statistical methods, and experimental design.

The students will learn HCI research methods and work on a research project that we expect to lead to both a co-authorship on a paper submission and an app deployed to the Google Play Store. They will work with a faculty member (Jeff) and Ph.D. student (Nedi) for 12 weeks over the summer. Brown is located in Providence, Rhode Island and has an amazing summer, with festivals, beaches, history, world-class restaurants, a lively art and music scene.

The students will be funded either through an NSF REU (pending) or other grant mechanism. They will receive a stipend of $8,000, be invited to summer events, and be part of a lab with other Brown University students doing HCI research over the summer. Students who are U.S. Citizens or permanent residents will be given preference due to NSF funding restrictions. Applications submitted by March 31 will be given preference, but the application will be open until both positions are filled.

Our research group has had success with undergraduate students in the past, with over 50 students being involved in research in the past 5 years. 100% of our research papers have undergraduate student co-authors, and many have been accepted to Ph.D. programs in HCI afterwards. Women and students from underrepresented groups are strongly encouraged to apply.

Application form link:
https://urldefense.proofpoint.com/v2/url?u=https-3A__goo.gl_forms_Hvm0DU4UMgblemiC3&d=DwIGaQ&c=4rZ6NPIETe-LE5i2KBR4rw&r=zzLZx5LZ1XGPH-v7tq_ZkstXU36EEkGjVBQ57KQGE1c&m=bs96h2kl87IMsC8KtSG8WJYR7iMs716wAFWkVO4Brbg&s=CCHEX50xVS6BL9UlgUHuGJuzkPiUDGGClfyJNdvAkUs&e=<https://urldefense.proofpoint.com/v2/url?u=https-3A__goo.gl_forms_Hvm0DU4UMgblemiC3&d=DwMFaQ&c=4rZ6NPIETe-LE5i2KBR4rw&r=JhDWCBnuRQzO1O3Wnrh_-5Tq_lbjhPfN9dvv-oAoHUw&m=eoYASya4G1Znqz9XUtan6UVIVpqoyWbUvdZn4pIvNGY&s=E1TpK9BAAdyn3uYQtFFVqqXNEDdbDOnTJGnQ67rn0oc&e=>

PROJECT DESCRIPTION

We are developing a fully automated system that guides users in adapting health tracking and behavior improvement information technology systems to suit their personal needs. While the goal of empowering users to improve their own health and wellness with data is impactful, current methods which rely heavily on displaying charts and providing summary statistics about steps taken and heart rate, are not sufficiently motivating for most people in the long term. What is needed is a way to provide guided self experiments that offers a probabilistic interpretation of how likely a change is effective. The complete cycle includes generating personalized interventions through actionable behavior change suggestions, causal analysis to learn from outcomes, and then back to generating a new intervention.
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