July 2024: Paper acceptance at ACM TMIS reviewing and benchmarking the use of LLMs for online depression detection |
June 2024: Paper acceptance at ISR for our discussion on preparedness and response in the "Century of Disasters" |
May 2024: Our ISR editorial on pathways for design research on Artificial Intelligence" has been downloaded nearly 5,000 times in the first 3 months! |
January 2024: Paper acceptance at MIS Quarterly for our work examining digital experimentation platforms. |
December 2023: Call for papers: MISQ special issue on "The Institutional Press in the Digital Age." Submission deadline is December 1, 2024. |
November 2023: See our article on "Data Science for Social Good" in the JAIS special issue. |
October 2023: Paper acceptance at JMIR Mental Health for our work exploring the efficacy of mental health analysis using machine learning/NLP applied to virtual interviews. |
September 2023: Paper acceptance at MIS Quarterly for our work on designing NLP and graph analytics-based social listening platforms for public health 3.0. |
December 2022: Excited to win the 2021 INFORMS ISR best paper award for our paper on predicting user susceptibility to phishing attacks. |
October 2022: Paper acceptance at EMNLP 2022 on background-aware representation learning for detecting background shifts. |
March 2022: Paper acceptance at NAACL 2022 for our work on quantifying multi-dimensional language model bias in downstream user-generated text-based modeling tasks: "Benchmarking Intersectional Biases in NLP" |
February 2022: Excited to give an invited talk to eBay's Data Science team on our collaborative research related to "Examining User Heterogeneity in Digital Experiments" |
February 2022: Paper acceptance at ACL 2022 for our work on auto-debiasing language models without relying on pre-defined lists of de-biasing terms and keywords: "Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts" |
January 2022: Paper acceptance at Information Systems Research for our work on NLP methods for text-based measurement of personality. |
December 2021: Paper acceptance at IEEE BIBM 2021 for our work related to adverse event detection. |
November 2021: Paper acceptance and presentation at EMNLP 2021 related to our work on constructing psychometric testbeds for fair NLP. |
November 2021: Paper presentation at MIT CODE for our work examining user and session heterogeneity in online controlled experiments. This work is a joint collaboration between our human-centered analytics lab (HAL) and eBay's Digital Experimentation Data Science team. |
September 2021: Thrilled to be featured in ND Research for my work on human-centered AI. |
June 2021: We're looking for smart, motivated students for our PhD in Analytics program offered through the ITAO department. |
April 2021: Honored that our paper examining online user journeys was a finalist for the American Marketing Association's 2020 Hunt/Maynard Award. |
March 2021: Inviting submissions to our Information Systems Research special issue on "Disaster Response." The call for papers can be found on the ISR website. |
January 2021: Work related to our NSF-funded research on user behavior modeling was recently published or is forthcoming. One paper focuses on predicting user behavior in real-time field environments. Another explores the importance of trust calibration for understanding user behavior in AI-augmented settings. |
December 2020: Really enjoyed being a mentor for the AMCIS 2020 and ICIS 2020 doctoral consortiums. The doctoral students demonstrated an amazing level of grit, intellect, and intestinal fortitude. |
November 2020: Greatly appreciative of my fellow co-organizers for IEEE ISI 2020 and INFORMS Workshop on Data Science. Pulling off conferences and workshops during COVID is never easy! |
October 2020: Our student-led paper on Deep Generative models for forecasting was accepted at IEEE ICDM Workshops. |
October 2020: Two paper acceptances at IEEE ISI 2020. One was based on an undergraduate thesis led by two excellent students. |
September 2020: Honored to have given a keynote at the AI Symposium hosted by the Memorial University of Newfoundland. Canada is doing amazing things in the AI space! |
September 2020: Inviting submissions to our Journal of AIS special issue on "Data Science for Social Good." The call for papers can be found on the JAIS website. |
September 2020: Our 2019 article related to detecting adverse events was the most downloaded article in Information Systems Research over the past 12 months. |
August 2020: Honored to be part of the INFORMS ISS DSR Award selection committee. These awards are a fantastic way to recognize impactful design research. For more details about the award, visit the website. |
August 2020: Thrilled that our paper examining adverse event detection using web search queries was accepted at IEEE TKDE. The preprint can be viewed in the IEEE Digital Library. |
August 2020: Our 2020 article related to psychometric NLP was the most downloaded article in ACM TOIS over the past 12 months. |
July 2020: Very excited that our paper related to predicting user susceptibility to phishing attacks was accepted at Information Systems Research. The open access version can be viewed in INFORMS Online. |
June 2020: Our "NLP for Social Good" project is being sponsored by Oracle for Research. |
May 2020: Congratulations to my student, Faizan Ahmad, for successfully defending his thesis. He will be joining Facebook next month. |
May 2020: Our paper on NLP to derive behavioral constructs from text is forthcoming in MIS Quarterly. |
April 2020: Excited that our "path to purpose" paper examining omni-channel customer journeys is forthcoming in the Journal of Marketing |
January 2020: Very happy to be part of the NSF-funded "Stroke Belt Project" examining patient empowered health platforms: AJKD Paper JCA Paper HBR Article |
December 2019: Honored that my collaborators and I were awarded the 2019 INFORMS Design Science Award for our work at the intersection of design and machine learning in the context of natural language processing |
September 2019: Our HBR digital article on the risks of AutoML just appeared on the HBR website |