Media, Talks, Announcements
Recent Awards
Our paper won Data Mining Best Paper Award at INFORMS 2023 ! Congrats to my coauthors Yiyang, Zhi, Vittorio and Tong!
We are the second place winners of the prestigious 2023 Bell Labs Prize! This is for innovations that will lay the foundations of the next technology revolution and in the process, manifestly change the way we live, work and communicate. My teammates are Margo Seltzer, Chudi Zhong and Jiachang Liu. We won 50K!
The paper “The Mechanical Bard: An Interpretable Machine Learning Approach to Shakespearean Sonnet Generation” coauthored with current and former Duke students Edwin Agnew. Michelle Qiu, and Lily Zhu as well as collaborator Sam Wiseman won an Outstanding Paper Award at the Association for Computational Linguistics Conference in 2023! Great job Edwin, Michelle, and Lily!!
Congratulations to Eric Song, Harry Chen, Allan Guo and Gaurav Parikh from the Duke Data Science Team who won the American Statistical Association's 2023 Data Challenge Expo in the Student Category!! Amazing job!
Totally thrilled to win the grand prize in the A-Mu-Sing contest on music for statistics education for my bluegrass songs about machine learning! Thank you to accompaniment by talented scientists Ed Browne on bass and Dargan Frierson on mandolin.
I'm happy to be named one of the Top 10 Women in AI in 2023 by AIo.
I'm proud to be the 2022 winner of the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI). This is the most prestigious award in the field of artificial intelligence. This award, similar only to world-renowned recognitions, such as the Nobel Prize and the Turing Award, carries a monetary reward at the million-dollar level. Duke Announcement | AAAI Announcement | Wall Street Journal AI Section feature article by John McCormick, October 14, 2021
I am proud to be named a 2022 Guggenheim Fellow! (press release)
Our team, led by student Srikar Katta, won the 2023 International Workshop on Health Intelligence (W3PHIAI 2023) at AAAI-23 Hackathon. This hackathon challenged the AI community to design an optimal age predictor. There was no restriction on the type of data used for this challenge, and we used sleep EEG to predict biological “brain” age. Congrats on your $1K award, Srikar! (announcement)
Our PaCMAP software package for dimension reduction was the winner of the 2023 John M. Chambers Statistical Software Award from the American Statistical Association. Congratulations Haiyang and Yingfan!
The FLAME/DAME software package from the Almost Matching Exactly Lab was the honorable mention for the 2022 John M. Chambers Statistical Software Award from the American Statistical Association. Congratulations Vittorio and Neha!
The paper “How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning” won the 2022 SPES+Q&P Student Paper Competition of the American Statistical Association. Congratulations Zhi!
Congratulations to Jenny Huang, Gaurav Parikh, and Albert Sun from the Duke Data Science Team who won the American Statistical Associations 2022 Data Challenge Expo in the Student Category!! Nice work all!
Gah-Yi Ban and I won the 2021 Best OM Paper in OR Award from the Manufacturing and Service Operations Management Society of INFORMS. This award is given to the best operations management paper published in the journal Operations Research.
Aaron Struck, Brandon Westover, Berk Ustun and I won the INFORMS Innovative Applications in Analytics Award in 2019 for our work on interpretable models for ICU seizure prediction. Thank you to our amazing coach Leo Guadalupe. (Duke News) (Analytics News Announcement) (INFORMS ORMS Resoundingly Human Podcast)
Students from the lab have won major awards! Rui Xin was awarded Finalist of the Computing Research Association's (CRA) Outstanding Undergraduate Researcher Award for 2023. Jerry Liu was awarded NSF Graduate Research Fellowship in 2022 and Honorable Mention of the Computing Research Association's (CRA) Outstanding Undergraduate Researcher Award for 2022. Caroline Wang and Sachit Menon were awarded Finalist of the Computing Research Association's (CRA) Outstanding Undergraduate Researcher Award for 2020. They join our very own Oscar Li, who won this award in 2019. Caroline Wang and Quinn Lanners were finalists for the NSF Graduate Research Fellowship in 2022.
Chaofan Chen, Kangcheng Lin, Yaron Shaposhnik, Sijia Wang, Tong Wang and I won the FICO Recognition Prize for the Explainable Machine Learning Challenge. We did not follow the instructions - rather than explaining a black box we provided a globally interpretable model. (Announcement of the winners)
Congratulations to the Duke Data Science Team! After our first semester, we are winners of the CVPR-NTIRE 2018 Single Image Super-Resolution Competition (Track 1) , and winners of the PoetiX Creative Turing Test 2018! It's been a pleasure coaching you guys!
Opinions
How good are AI health technologies? We have no idea, with Zhicheng Guo, Cheng Ding and Xiao Hu, STAT, October 11, 2023
What the Supreme Court Doesn’t Understand About AI, with Brandon Garrett, The Messenger, June 3, 2023
A Reasonable Right to Biometric Privacy (They retitled it to this unfortunate title: “That selfie you posted on Instagram? Companies are using it in unethical ways”) with Lance Browne (Charlotte Observer link) | (Raleigh News&Observer link), March 27, 2023
Talks and Interviews
Interview on CNBC International on AI Regulation May 30, 2023.
WNAR (Western North American Region of The International Biometric Society) Webinar on Understanding How Dimension Reduction Tools Work, describing joint work with Yingfan Wang, Haiyang Huang, Yaron Shaposknik and Ed Browne. May 12, 2023.
Schwartz Reisman Institute, University of Toronto. “Do Simpler Machine Learning Models Exist and How Can We Find Them?” January 24, 2023.
Giving a plenary at INFORMS was such an amazing honor. This article doesn't use my ML terminology but I think it gets the point across. October 16, 2022.
Interview on BBC Digital Planet about our work on interpretable neural networks | Interview on BBC Digital Planet Podcast - start at 22:33.
NSF Statistics at a Crossroads Webinar, featuring Jianqing Fan, Michael Jordan and I, my talk at 17:30 in the video, called “Please stop doing explainable ML”
Data Science at Home Podcast by Francesco Gadaleta, called “How can deep neural networks reason” about our work on interpretable networks for computer vision
FAT-ML invited talk 2016, on interpretable models
Raymond and Beverly Sacker USA-UK Scientific Forum 2017, on interpretable models
INFORMS IAAA Award semi-final presentation INFORMS 2013, on power grid reliability
PAPIs random interview, 2016
Media
This list contains only articles that are still live on the Internet. Past aired TV, Radio, or Magazine articles that are not archived are not included.
AI Regulation
Duke professor – a critic of ‘runaway train’ AI development – is named one of the field’s top women: WRAL TechWire, April 6, 2023
Interpretability / Computer Vision
The First AI Breast Cancer Sleuth That Shows Its Work New AI for mammography scans aims to aid rather than replace human decision-making. January 14, 2022 - Based on work of Alina Barnett and our AI Mammography team, written by Ken Kingery
Accurate Neural Network Computer Vision Without the 'Black Box’: Duke team disentangles neural networks to understand how they see the world, December 15, 2020 - A new media article about the work of Zhi Chen, with help from Webster Bei, written by Robin Smith
What Do Conspiracy Theories And AI Explainability Have In Common? by Kareem Saleh, Forbes, May 4, 2021
New Deep Neural Network Enables Better Artificial Intelligence Transparency by Cami Rosso, June 8, 2021
A framework to assess the importance of variables for different predictive models by Ingrid Fadelli, Tech Xplore, January 12, 2021
Accurate Neural Network Computer Vision Without the 'Black Box’: Duke team disentangles neural networks to understand how they see the world by Robin Smith, December 15, 2020
“Rise of Robot Radiologists,”: by Sara Reardon, Nature, Innovations In, December 18, 2019
“Machine vision that sees things more the way we do is easier for us to understand”: MIT Technology Review, Artificial Intelligence, December 6 2019
Computer Vision
“Artificial Intelligence Makes Blurry Faces Look More Than 60 Times Sharper: This AI turns even the blurriest photo into realistic computer-generated faces in HD”: by Robin A. Smith, Duke Today, June 12, 2020. This article was covered by many new venues in several countries, including Newsweek, Independent.co.uk, and IEEE Spectrum
Duke Team Attempts a Real-Life Version Of CSI 'Zoom and Enhance’, written by Robin A. Smith
Crime Data Mining
“Possible to predict recidivism? Here's how…”: The Docket, MSNBC (TV), Tuesday May 19, 2015
“Crime-Fighting Computer Code from Cambridge Police and MIT”: Interview on WBUR (NPR) Radio Boston, August 2013
“Cambridge police look at math to solve crimes”: Boston Globe, Metro Section, front page (also link to article from Boston Globe front page), Sunday August 4 2013
“Statistician enlisted to fight crime by numbers”: The Times of London, US & Americas section, Tuesday August 6 2013
“Mapping the Future: The Power of Algorithms”: Documentary by Java Films, 2015
“Can Cops Predict Crime?”: Discovery News, December 12, 2014. (Slightly misquoted - we do consider time and space.)
Health
Do You Zone Out? Procrastinate? Might Be Adult ADHD: NPR 2017 (article about Berk Ustun's JAMA Psychiatry paper on ADHD)
How Big Data Can Be Used to Improve Early Detection of Cognitive Disease: The Health Care Blog 2015
Could a digital pen change how we diagnose brain function?: Phys.org 2015
Data-driven tool enables patients to balance recovery expectations: FierceHealthIT, July 2, 2014
Meeting Analysis
Some of the media coverage of our meetings analysis paper was pretty funny.
“At Work: Just Say 'Yeah’”: Wall Street Journal, Business Section, on page B8 in the U.S. edition, June 19, 2013
“How to sound like a boss at your next work meeting,”: Interview on Fox & Friends, Fox News, national television, 6:45AM July 3 2013
"How to be effective at meetings? Say 'yeah’: Toronto Star, Business section, June 28, 2013
'Yeah’ is the most persuasive word to use in a meeting: study says,": NY Daily News, living section, June 26, 2013
Most Persuasive Four-Letter-Word in Meetings (It's Not What You Think): Yahoo! Shine, work-money section, June 25, 2013
5 Words That Get Results Business Meetings: Yahoo! News, (also LiveScience and Business News Daily), June 21, 2013
Researchers discover the key to persuasion: ABC News, consumer report blog / business, June 24, 2013
MIT Sloan Professor's Research Identifies Top Persuasive Words in Meetings : Reuters, Businesswire
5 Important words to say in every business meeting: Business News Daily, June 20, 2013
“How To Win Over Co-Workers And Influence Meetings: Use These 3 Words”: Forbes.com, Pharma & healthcare section, June 23, 2013
“The most effective words to use at a meeting”: Fox Nation, foxnews.com, June 20, 2013
“Five words that can persuade your boss to give you a raise”: NDTV (India) June 25, 2013
Computational Poetry
Bard or Bot? Duke team wins prize for most human-like sonnet written by A.I., written by Robin A. Smith
Product Rankings
“How to Improve Product Rankings”: Businessweek, March 09, 2012
Power Grid Reliability
“New York's Exploding Manhole Covers Pose Unexpected Winter Hazard”: Reuters, Yahoo! News, NY Times
“Machine vs. Manhole”: U.S. News and World Report, Science News, WIRED Science, Slashdot, Discovery News
“21st-Century Data Miners Meet 19th-Century Electrical Cables”: IEEE Computer Magazine (one of three articles featured on the cover), 2011 (publisher's site)
Other Media
Top 10 Women in the World of AI, by AIo, 2023. Covered here by WRAL TechWire
Top 40 Under 40: Poets & Quants, 2015
12 of the most impressive professors at MIT: Business Insider, 2015
Slides
Slides from JSM Introductory Overview Lecture on Interpretable Machine Learning, with Alina Barnett, August 7, 2023
Cool Stuff
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This beautiful poster was done by Sita Magnuson from Dpict during my plenary talk at CODE. |
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from The Docket on MSNBC |