Hi! I'm a 5th year Ph.D. student in the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University (CMU), advised by Niki Kittur and Bob Kraut. I received my Bachelor's from Princeton University in 2015 with Highest Honors in Psychology and minors in Neuroscience and Applications of Computing.

Broadly, I'm interested in applying social computing theory and mixed methods research to develop tech products/services for wellness and productivity. My current research develops and tests new strategies for improving participant engagement, collaboration, and innovation quality in online ideas competitions and communities.

I also organize CMU's Crowdsourcing Lunch Seminar, an informal discussion series that invites researchers from a broad range of perspectives in academia, industry, and entrpreneurship to meet and share their work with the community here. If you're interested in speaking at one of our lunches, email me at fng@cs.cmu.edu!

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Improving Online Innovation Competitions and Communities

I'm currently collaborating with Conservation X Labs, a non-profit organization devoted to solving global environmental conservation challenges, to better understand and improve participation engagement as well as innovation quality in online idea competitions and collaborative maker communities. Check out our first public blog post about our findings here, and stay tuned for more updates!


Understanding Member Experiences in Online Groups

During my summer 2018 internship as a UX Researcher at Facebook, I worked with a cross-functional product team to better understand member experiences in Facebook Groups and to collect user feedback on concept mocks of new product designs. Based on my empirical findings and my literature reviews on related social computing research, I developed new conceptual frameworks and design recommendations to drive the Facebook Groups product strategy.


Improving R&D Problem Solving Processes

From 2015-2016, I collaborated with the Innovation Research Interchange (IRI), a non-profit consortium of R&D managers from diverse industries across the world, to better understand their challenges during R&D collaboration and to test new strategies for improving R&D problem solving processes. I presented the results from this work to over 200 R&D practitioners during a plenary session at the annual IRI Summit Meeting.


Improving Crowd Innovation Processes

In between field studies with collaborating organizations, I've been runnning online studies on Amazon Mechanical Turk and lab studies at Carnegie Mellon University to develop and test new strategies for improving crowd innovation processes. Specifically, these new processes leverage the creative power of analogies and distribute the analogical thinking process across crowds to solve design and R&D problems.


Augmenting Designer Creativity through Computational Analogical Search

In addition to helping crowds find and apply analogies, I also collaborated with machine learning researchers from The Hebrew University of Jerusalem to help computers find analogies. The team developed a novel search engine for analogical inspirations to user-specified product design needs, and I conducted evaluation studies showing that it outperformed previous state-of-the-art approaches. I'm excited about this work's implications for developing tools to boost creative productivity in a broad range of design, research, and engineering fields.

Analogy Mining for Specific Design Needs. Karni Gilon, Joel Chan, Felicia Ng, Hila-Lifshitz-Assaf, Aniket Kittur, and Dafna Shahaf. CHI 2018.


Understanding Online Feedback Exchange

The summer before my PhD, I worked with CMU HCII researchers to understand socio-psychological factors in online feedback exchange. We conducted an online experiment to see how feedback language and source anonymity affect feedback reception and creative work quality. I'm excited about this work's implications for designing social platforms that support more productive feedback exchange between users.

Fruitful Feedback: Positive Affective Language and Source Anonymity Improve Critique Reception and Work Outcomes. Thi Thao Duyen T. Nguyen, Thomas Garncarz, Felicia Ng, Laura A. Dabbish, and Steven P. Dow. CSCW 2017.


Understanding Goal Progress Feedback

For my undergraduate senior thesis, I conducted a self-designed research project on the effects of goal progress feedback on cognitive motivation. Through a controlled lab experiment, I looked at how different valences and visualizations of progress feedback affect task performance and persistence at different stages of goal completion. I'm most excited about this work's implications for designing persuasive technologies to encourage productive behaviors.

Unpublished manuscript:
Am I There Yet?: Probing the Effects of Goal Progress Feedback on Cognitive Motivation. Felicia Ng. 2015.


Understanding Memory and Visual Prediction in the Brain

As an undergraduate research assistant, I worked with my mentors on fMRI experiments that led to the discovery of novel relationships between object representations in the hippocampus and predictive coding in the visual cortex.

Linking pattern completion in the hippocampus to predictive coding in visual cortex. Hindy, N. C., Ng, F. Y., and Turk-Browne, N. B. (2016). Nature neuroscience.


May 2019.

Moving to the greater Seattle area for a summer internship at Microsoft Research AI!

Mar 2019.

Our paper "Matching Open Innovation Projects for Analogical Feedback Exchange" got accepted to the ACM Collective Intelligence Conference!!

Feb 2019.

Just accepted an internship position at Microsoft Research AI! Looking forward to spending the summer around Seattle again.

Jan 2019.

Happy New Year! I'm working as a Teaching Assistant for the course Social Web this semester!

Oct 2018.

Our paper "Applications of Social Identity Theory to Research and Design in Computer-Supported Cooperative Work" won a Best Paper Award at CSCW 2018!