Information Science PhD Candidate at Cornell Tech.

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2 W Loop Rd

New York, NY 10044

United States

Alexandra Bremers is a PhD Candidate in Information Science at Cornell University, based at Cornell Tech (New York, NY). She works with Wendy Ju, Francois Guimbretiere and Steve Marschner on interaction design for multi-modal, physical tasks.

Alexandra holds an M.S. in Information Science from Cornell University, an M.S. in Artificial Intelligence from Utrecht University, and a B.S. in Industrial Design from Eindhoven University of Technology. Additionally, she studied automotive human-technology interaction at Warwick University. From 2017 to 2020, she worked as a Human-Machine Interface Researcher at Jaguar Land Rover, UK, on collaborative research with Cambridge University. While at Jaguar, she was selected to join the 2018 Oxford-Cambridge cohort of Rising Women in Science and Engineering (RisingWISE), and was recognized for innovation through the JLR & Tata Innovista competitions. She also spent time at Toyota Research Institute and Accenture Labs R&D in the Bay Area, and the NTU IoX Center at National Taiwan University.

In addition to her technical work, Alexandra has been involved in art and design projects with Next Nature Network and Dutch Design Week, and won awards in creative and print writing. In 2020, she received the Royal Commission of 1851 Industrial Fellowship to pursue a PhD in Engineering at the University of Cambridge.

Alexandra’s work has been published at top ACM/IEEE conferences IROS, CHI, HRI, TEI, AutoUI, SCF, CUI, and RO-MAN, as well as in the journals IEEE IV and Elsevier IJHCS.

Her cv can be found here, her resume here, and her papers on Google Scholar or ResearchGate.


news

Jul 23, 2024 Two works got accepted to the Halfway to the Future Symposium: my short paper together with Wendy Ju, and a full-length pictorial led by Natalie Friedman! The Symposium will be held in Santa Cruz in October 2024.
Jun 24, 2024 I am at the Ubiquitous Robots conference held at NYU. I will be at Conversational User Interfaces in Luxembourg from July 8 to 10. Excited!
Jun 12, 2024 We have a new paper coming out, led by Teresa Parreira, on Anticipatory Human Reactions for Outcome Prediction in HRI. It will be presented at RO-MAN 2024. Stay tuned!
Jun 3, 2024 Consultant, author, entrepreneur and designer Mike Kuniavsky wrote a research agenda on applied distributed cognition using foundation models and biosensing, and it features three projects that I’ve been involved in! I recommend reading the full article here.
May 21, 2024 Excited that two posters got accepted into ACM CUI (conversational user interfaces): our analysis of social discomfort in shared car trips, and a preliminary study on situated conversational interfaces for task guidance. I will present our work in Luxembourg in July!
Apr 3, 2024 While I won’t be attending CHI this year, Frank Bu will present our late-breaking report with field notes on deploying research robots in public spaces. We hope that this work can contribute to more in-the-wild human-robot interaction studies! Read our paper in the ACM Digital Library.
Mar 4, 2024 In a few weeks I will be attending HRI in Boulder, Colorado! I’m participating in the 1st International Workshop on Worker-Robot Relations. You can read my accepted position paper here.
Jan 22, 2024 Two new arXiv pre-prints are out: recent work led by Natalie Friedman and Daniel Zhou’s internship project.
Jan 12, 2024 Accenture’s 2024 TechVision report features our recent work on learning from facial reactions. “Similarly, a 2023 research paper from Accenture and Cornell University describes a way human-robot collaborations can benefit when robots can identify when they’ve made an error based on implicit reactions from humans they interact with – much like how people use social cues to recognize their own mistakes. The authors built a dataset of bystander responses to human and robot errors and used it as input to a deep-learning model to predict failures. By creating these systems that are sensitive to human social signals, they are efficiently using the expertise of human perception and action as a marker for mitigating robotic errors.”
Dec 13, 2023 Our IROS 2023 paper “The Bystander Affect Detection Dataset for Failure Detection in HRI” is now readable in IEEE Explore.
Dec 7, 2023 University of Cambridge published a story around our recent article in IEEE Intelligent Vehicles. Read it here: “Using machine learning to monitor driver ‘workload’ could help improve road safety”
Oct 5, 2023 Our newest work on collaborative creative machines will be showcased at the ACM Symposium on Computational Fabrication 2023 at Cornell Tech, NYC. Read the paper in the conference proceedings!
Aug 17, 2023 The collaborative work I was a part of during my time at Jaguar Land Rover has now resulted in another accepted paper! Together with our colleagues from Cambridge University, “Driver Profiling and Bayesian Workload Estimation Using Naturalistic Peripheral Detection Study Data” can now be found in IEEE Transactions on Intelligent Vehicles.
Aug 10, 2023 Just attended SIGGRAPH in Los Angeles, which was a blast!
Jun 25, 2023 Our paper “The Bystander Affect Detection (BAD) Dataset for Failure Detection in HRI” has been accepted to IROS 2023! I will be presenting the findings of our paper in Detroit, on the 4th of October. Find out more about the project on our website.
Jun 5, 2023 First day at Accenture Labs San Francisco, where I’ll spend the summer working as Associate Principal.
May 25, 2023 I passed my Admission to Candidacy (A-Exam) today! This milestone marks completion of the “master’s” part of the Cornell Information Science PhD, and means that I am done with all-but-dissertation.
Mar 1, 2023 Going to attend HRI in Stockholm to participate in the workshop “The Imperfectly Relatable Robot”.
Jun 20, 2022 Presenting my thesis topic “A computer that sketches along with you” at Creativity and Cognition in Venice!
May 15, 2022 Visiting Prof. Antti Oulasvirta at Aalto University, Helsinki to work on mixed-initiative HRI, funded by the Finnish Center for AI.