Yi Zhu

Yi Zhu

PhD Candidate
Information & Decision Sciences

Education:

  • PhD, 2024 (expected)
    Information and Decision Sciences, University of Minnesota
  • MS, 2019
    Business Analytics, Drexel University
  • MS, 2015
    Journalism, University of Illinois at Urbana-Champaign
  • BA, 2014
    English, Communication University of China

Expertise:

  • Health IT and Analytics
  • Network Science and Economics
  • Innovation and Entrepreneurship
  • Econometrics, Causal Inference
  • Network Analysis
  • Machine Learning, Deep Learning, Natural Language Processing

Biography

I am on the 2023 to 2024 academia job market, actively seeking a tenure-track faculty position in management information systems and related fields. 

I am a fifth-year Ph.D. candidate in the Department of Information and Decision Sciences at Carlson School of Management, University of Minnesota. My research interests lie in health IT, design science, network science and economics, and innovation and entrepreneurship. My recent research centers on employing data-driven empirical methodologies to unravel new IT-induced adverse outcomes in healthcare (e.g., medical device recall, human sedentary behavior) and developing theory-driven algorithmic approaches for their predictions. My work has been published in leading academic journals, including Journal of the American Medical Association (JAMA), Journal of General Internal Medicine, and Medical Care Research and Review. I also have presented my work at top information system conferences, including International Conference on Information Systems (ICIS), Conference on Information Systems and Technology (CIST), Workshop on Information Technologies and Systems (WITS), and Hawaii International Conference on System Sciences (HICSS). I am the recipient of NSF Innovation Corps (I-Corps) program grant for technology commercialization and customer discovery, INFORMS ISS Design Science Award, Carlson Ph.D. Student Teaching Award, University of Minnesota Early Innovation Fund, and University of Minnesota BOLD IDEAS grant.

 

Scheduled Talk

1. 2023 INFORMS Workshop on Data Science. Phoenix, AZ. Time: 11 a.m. local time, Oct 14, 2023. Location: Phoenix Convention Center, room 126A. Paper: Zhu Y, Bi X, Adomavicious G, Curley S. Forecasting Goal-Oriented Activities: A Deep Learning Approach Leveraging Cross-Activity Relationships.

 

Journal Publications 

1. Everhart A, Sen S, Stern A, Zhu Y, Karaca-Mandic P (2023) Association Between Regulatory Submission Characteristics and Recalls of Medical Devices Receiving 510(k) Clearance. Journal of the American Medical Association (JAMA) 329(2):144-156.
2. Zhu Y, Carroll C, Vu K, Sen S, Georgiou A, Karaca-Mandic P (2022) COVID-19 Hospitalization Trends in Rural Versus Urban Areas in the United States. Medical Care Research and Review 80(2):236-244.
3. Karaca-Mandic P, Sen S, Georgiou A, Zhu Y, Basu A (2020) Association of COVID-19-Related Hospital Use and Overall COVID-19 Mortality in the USA. Journal of General Internal Medicine. 

 

Work in Progress (full manuscripts are available upon request)

1. Zhu Y, Sen S, Everhart A, Karaca-Mandic P. Predicting Medical Device Recalls: An Evidence-Informed Deep Learning Approach Leveraging Regulatory Submission Characteristics. In preparation for submission to Information Systems Research. (JOB MARKET PAPER)
Abstract: Medical devices in the US entering the market through the FDA’s predominant 510(k) clearance pathway have garnered significant safety concerns. The medical industry worries that devices approved under this pathway, primarily based on new devices’ equivalency to previously approved devices (referred to as predicate devices), may be more likely to encounter recalls. These recalls could impose substantial financial strains on the healthcare system. In response, this work proposes a data-driven approach for predicting 510(k) device recalls, aiming to alleviate such safety concerns. Following the design science paradigm and informed by the empirical findings from prior research, our approach leverages the predictive power of the characteristics in the network formed by predicate device citing relationships. It incorporates natural language processing and deep learning techniques to tackle three design challenges, including creating the predicate database, learning the spatial dependencies of predicate network features, and capturing the temporal patterns of those features. Rigorous tests based on 45,236 510(k) devices approved from 2003 to 2020 show that our approach significantly outperforms standard prediction models and the performance varies by device subgroups and key attributes applied. The improved medical device recall prediction performance and the analysis insights into the performance variations provide actionable implications for timely response to recalls and improving the current 510(k) pathway requirements to reduce device safety issues.

2. Zhu Y, Bi X, Adomavicious G, Curley S. Forecasting Goal-Oriented Activities: A Deep Learning Approach Leveraging Cross-Activity Relationships. In preparation for submission to INFORMS Journal on Computing. (received 2023 INFORMS Annual Meeting and Workshop on Data Science Student Scholarship)
Abstract: Many individuals struggle to maintain consistent efforts toward their goals, such as maintaining a desired physique or mastering a second language. Although online platforms have introduced various goal-oriented programs to help enhance motivation and adherence, these programs often suffer from high dropout rates, diminishing their effectiveness. To intervene in early dropouts and recommend programs with suitable goals, we propose an approach to accurately forecast individuals’ program goal completion and their actual performance toward completing the goal. Following the design science paradigm, the proposed approach leverages a combination of convolutional neural networks and gated recurrent neural networks, surpassing traditional methods by capturing the latent interactions among different activity types (e.g., running, cycling) and measures (e.g., distance, duration) recorded in sequential format and temporal dependencies between daily activities. Its applicability extends beyond goal-oriented programs, as it can be utilized in forecasting contexts involving multiple sequences and benefiting from cross-sequence interrelationships. We test the effectiveness of the proposed approach using simulated and real-world datasets, demonstrating its advantages over canonical machine learning models with both datasets. This performance enhancement positions the approach as a promising tool for improving adherence in goal-oriented programs and goal attainment. It also provides valuable insights for goal-oriented program intervention and personalization.

3. Zhu Y, Mani A. Investigating Churn in Online Wellness Programs: Evidence from a US Online Social Network. In preparation for submission to Proceedings of the National Academy of Sciences
Abstract: Online wellness and fitness platforms are increasingly utilizing social support in their wellness programs to motivate healthy activities and improve user engagement. However, many wellness programs suffer from high churn rates that discount their expected efficacy. This introduces negative social influence that may lead to a churn contagion and amplify churn speed and scale. Hence, a need arises to understand why users churn wellness programs and how social contagion contributes to the churns. Leveraging the exercise challenge setting, exercise field data, and a large social network on a renowned U.S. online fitness platform, we investigate the effect of peers' tendency to churn exercise challenges on ego's churn likelihood. To achieve the research goal, we employ an instrumental variable framework, using the exogenous variation of peers' weather in locations that differ from the ego's location as instruments. The framework untangles the endogeneity of the estimated effect using variations created by peers' weather as a shock to the ego's churn. We measure churn as a decision the ego makes after being inactive for one to two weeks and define peers as the ones the ego follows on the platform. We find that exercise challenge churn is socially contagious and demonstrates a complex contagion effect. Interestingly, our analyses reveal that the social contagion of churn diffuses from the sub-central or peripheral egos who have fewer friends in the social network to central egos who have more friends in the social network. Such churn contagion is mostly confined to low-density network communities with members who are poorly connected with one another. Our findings have important implications for designing intervention plans to stop wellness program churn based on social contagion.

4. Zhu Y, Chan J, Bi X, Guo Y, Wu J. Consumer Responses to Puffery: Empirical Evidence from a Cellular Network Upgrade Advertising. In preparation for submission to Journal of Marketing.
Abstract: Firms often use puffery to attract consumer attention, but doing so can backfire and negatively impact the consumer experience, resulting in a boomerang effect. Despite the potential risks, there is limited empirical evidence on the boomerang effect of puffery, which has led to extensive discussion among researchers. To fill this gap, we conducted an empirical study to assess and quantify the impact of advertising puffery on consumer response to a cellular network upgrade advertising campaign using a large proprietary field dataset of consumer service calls about the same cellular network. To achieve our research objective, we relied on a continuous difference-in-differences causal identification strategy to estimate the impact of advertising puffery. This strategy leverages the varied advertisement intensities across different locations and the comparison of consumer response during pre- and post-period of the cellular network upgrade. We measured consumer response by analyzing their service call sentiment and found that the use of puffery had a negative effect on the sentiment. Interestingly, the negative sentiment was mainly driven by the advertised attributes related to the upgraded cellular network's most significant and highly-weighted strength. Moreover, the effect varied with location-based socioeconomic and demographic characteristics. Our findings have important implications for managers in terms of the appropriate use of puffery for different product attributes and its consequent response from various consumer subgroups.

 

Selected Works & Activities

  • Journal Articles
    Everhart AO, Sen S, Stern AD, Zhu Y, Karaca-Mandic P (2023) Association Between Regulatory Submission Characteristics and Recalls of Medical Devices Receiving 510(k) Clearance. Journal of the American Medical Association (JAMA) 329(2):144–156.
  • Journal Articles
    Zhu Y, Carroll C, Vu K, Sen S, Georgiou A, Karaca-Mandic P (2022) COVID-19 Hospitalization Trends in Rural Versus Urban Areas in the United States. Medical Care Research and Review.
  • Journal Articles
    Karaca-Mandic P, Sen S, Georgiou A, Zhu Y, Basu A (2020) Association of COVID-19-Related Hospital Use and Overall COVID-19 Mortality in the USA. Journal of General Internal Medicine.
  • Journal Articles
    Zhou J, Everhart A, Smith L, Qiu Y, Zhu Y (2020) The Economic Burden of Extended—Release Pharmaceuticals in Minnesota. Public Health Review, 3(2).
  • Conference Proceedings
    Zhu Y, Mani A (2023) Investigating Churn in Physical Activity Challenges: Evidence from a US Online Social Network. Hawaii International Conference on System Sciences (HICSS). Lahaina, HI.
  • Conference Proceedings
    Zhu Y, Everhart AO, Karaca-Mandic P, Sen S (2020) Using NLP to Extract Predicate History from Medical Device Approvals. International Conference on Information Systems (ICIS). Virtual.
  • Other
    Sen S, Karaca-Mandic P, Georgiou A, Zhu Y (2021) An Information System for COVID-19 Hospitalization Tracking and Analysis. INFORMS ISS Design Science Award.
  • Research Diary

    · 8/17/2023: Our paper titled “Forecasting Goal-Oriented Activities: A Deep Learning Approach Leveraging Cross-Activity Relationships” was accepted for full presentation with student scholarship at the 2023 INFORMS Workshop on Data Science, October 14, 2023, Pheonix, AZ (Coauthored with Xuan Bi, Gedas Adomavicius, Shawn Curley). 

    · 7/29/2023: I got accepted by the 2023 Doctoral Consortium at the International Conference on Information Systems (ICIS). 

    · 3/30/2023: I got accepted by the 2023 Doctoral Consortium at the Conference on Health IT and Analytics (CHITA) with a $600 travel grant. 

    · 3/23/2023: Our paper titled "Investigating Churn in Physical Activity Challenges: Evidence from a US Online Social Network" was accepted for presentation at the 2023 International School and Conference on Network Science (NetSci). July 10-14, Vienna, Austria. (Coauthored with Ankur Mani).

    · 3/17/2023: Our paper titled "Predicting Medical Device Recalls Leveraging Regulatory Submission Characteristics" was accepted for presentation at the 2023 Conference on Health IT and Analytics (CHITA). May 5-6, 2023, Washington, DC.  (Coauthored with Soumya Sen, Alexander Everhart, Pinar Karaca-Mandic).

    · 2/21/2023: Our paper titled "Consumer Responses to Puffery: Empirical Evidence from a Cellular Network Upgrade Advertising" was accepted for presentation at the 2023 INFORMS Society for Marketing Science (ISMS) Annual Conference. June 8-10,  2023, Miami, FL. (Coauthored with Jason Chan, Xuan Bi, Yue Guo, Jun Wu).

    · 2/9/2023: I received the 2023-2024 Carlson School Doctoral Dissertation Fellowship and was nominated by Carlson School for the 2023-2024 UMN Graduate School Doctoral Dissertation Fellowship (there were three nominations). My dissertation was titled "Understanding Adverse Events in Healthcare and Wellness: Medical Device Recall, COVID-19 Hospitalization, and Exercise Program Dropout". 

    · 1/18/2023: Our paper titled "Consumer Responses to Puffery: Empirical Evidence from a Cellular Network Upgrade Advertising" was accepted for presentation at the 2023 Production and Operations Management Society (POMS) Annual Conference. May 21-25,  2023, Orlando, FL. (Coauthored with Jason Chan, Xuan Bi, Yue Guo, Jun Wu).

    · 1/13/2023: Our paper titled "Predicting Medical Device Recalls Leveraging Regulatory Submission Characteristics" was accepted for presentation at the 2023 INFORMS Healthcare Conference. July 26-28, 2023, Toronto, ON Canada.  (Coauthored with Soumya Sen, Alexander Everhart, Pinar Karaca-Mandic).

    · 1/9/2023: Our project "ML-based decision support system for analyzing medical device history and recalls from FDA’s 510k filings" was awarded an Early Innovation Fund from University of Minnesota Technology Commercialization.  (joint project with Soumya Sen and Pinar Mandic-Karaca) ($10,000). 

    · 12/23/2022: Our project "ML-based decision support system for analyzing medical device history and recalls from FDA’s 510k filings" was awarded an MVP Challenge grant from Minnesota Innovation Corps. This grant will provide seed funding and mentorship for further prototyping and product development (joint project with Soumya Sen and Pinar Mandic-Karaca) ($5000). 

    · 11/25/2022: Our paper titled "Consumer Responses to Puffery: Empirical Evidence from a Cellular Network Upgrade Advertising" was accepted for presentation at the 2023 Winter AMA Marketing for Higher Education Special Interest Group (SIG) Special Session, February 10-12, 2023, Nashville, TN (Coauthored with Jason Chan, Xuan Bi, Yue Guo, Jun Wu).

    · 11/11/2022: Our paper titled "Consumer Responses to Puffery: Empirical Evidence from a Cellular Network Upgrade Advertising" was accepted for presentation at the 2023 American Marketing Association (AMA) Winter Conference, February 10-12, 2023, Nashville, TN (Coauthored with Jason Chan, Xuan Bi, Yue Guo, Jun Wu).

    · 10/21/2022: I received the 2022-2023 Carlson School of Management PhD Student Conference/Travel Fellowship ($750).

    · 8/24/2022: I received the 2021-2022 Carlson School of Management PhD Student Teaching Award.

    · 8/18/2022: Our paper titled "Investigating Churn in Physical Activity Challenges: Evidence from a US Online Social Network" was accepted for presentation at the 2023 Hawaii International Conference on System Sciences (HICSS), January 3-6, 2023, Lahaina, HI (Coauthored with Ankur Mani).

    · 8/7/2022: Our paper titled "Investigating Churn in Physical Activity Challenges: Evidence from a US Online Social Network" was accepted for presentation at the 2022 Conference on Information Systems and Technology (CIST), October 15-16, 2022, Indianapolis, IN (Coauthored with Ankur Mani).

    · 4/20/2022: I received the 2021-2022 Carlson School of Management PhD Student Conference/Travel Fellowship ($750).

    · 4/20/2022: Our University of Minnesota COVID-19 Hospitalization Tracking Project received Honorable Mentions in the 2022 Innovation Impact Case Award, sponsored by Office of the Vice President for Research, University of Minnesota.

    · 4/7/2022: Our research team won the Second Place of the Third University of Minnesota Interdisciplinary Health Data Competition ($2000). Project topic: Demographic (In)equities Revealed by HCAHPS Ratings.  

    · 3/10/2022: Our work titled "Predicate Characteristics and Recalls of 510(k) Medical Devices" was accepted for presentation at the 2022 AcademyHealth Annual Research Meeting, June 4-7, 2022, Washington, DC (Coauthored with Alexander Everhart, Pinar Karaca-Mandic, Soumya Sen, Ariel Stern).

    · 12/17/2021: Our work titled "An Information System for COVID-19 Hospitalization Tracking and Analysis" won the 2021 INFORMS Information Systems Society (ISS) Design Science Award ($1000). (project summary) (news feature 1, news feature 2)

    · 10/25/2021: I gave an invited talk at the 2021 INFORMS Annual Meeting with the paper titled "Investigating The Willingness To Pay For Enhanced Mobile Internet Services: Evidence From A Mobile Network Upgrade" (Coauthored with Jason Chan, Xuan Bi, Yue Guo, Jun Wu).

    · 10/25/2021: Our paper titled “Forecasting Goal-Oriented Activities: A Deep Learning Approach Leveraging Cross-Activity Relationships” was accepted for poster presentation at the 2021 Workshop on Information Technology and Systems (WITS), December 15-17, 2021, Austin, TX (Coauthored with Xuan Bi, Gedas Adomavicius, Shawn Curley). 

    · 6/3/2021: Our paper titled "Consumer Reactions Toward IT Infrastructure Upgrade: Evidence From A Nation-wide Mobile Network Upgrade" was accepted for presentation at the 2021 Statistical Conference in E-Commerce Research (SCECR), June 17-18, 2021 (Coauthored with Jason Chan, Xuan Bi, Jun Wu).

    · 5/3/2021: Our paper titled "Consumer Reactions Toward IT Infrastructure Upgrade: Evidence From A Nation-wide Mobile Network Upgrade" has been accepted for presentation at the 2021 American Marketing Association (AMA) Summer Conference, August 4-6, 2021 (Coauthored with Jason Chan, Xuan Bi, Jun Wu).

    · 4/29/2021: Our University of Minnesota COVID-19 Hospitalization Tracking Project won two Silver Stevie Awards for "Most Valuable Non-Profit Response" and "Most Valuable Service" at the 2021 Annual American Business Awards (COVID-19 Response Category).

    · 4/22/2021: I received the 2020-2021 Carlson School of Management PhD Student Conference/Travel Fellowship ($355).

    · 4/7/2021: Our paper titled "Consumer Reactions Toward IT Infrastructure Upgrade: Evidence From A Nation-wide Mobile Network Upgrade" was accepted for presentation at 2021 INFORMS Society for Marketing Science (ISMS) Annual Conference, June 3-5, 2021 (Coauthored with Jason Chan, Xuan Bi, Jun Wu).

    · 3/30/2021: I was featured in the news report "COVID-19 Hospitalization Tracking Project Wins Innovations that Inspire Award".

    · 3/30/2021: Our University of Minnesota COVID-19 Hospitalization Tracking Project won 2021 AACSB Innovations That Inspire.

    · 3/16/2021: Our paper titled "Consumer Reactions Toward IT Infrastructure Upgrade: Evidence From A Nation-wide Mobile Network Upgrade" was accepted for presentation at the 2021 Industry Studies Association (ISA) Annual Conference, June 2-4, 2021 (Coauthored with Jason Chan, Xuan Bi, Jun Wu).

    · 3/10/2021: Our University of Minnesota COVID-19 Hospitalization Tracking Project won 2021 NIHCM Awards in Journalism and Research, Digital Media Track ($15,000).

    · 8/20/2020: I was featured in the news report "New research finds association between COVID-19 hospital use and mortality".

    · 4/24/2020: Our research team won the Champion of the First University of Minnesota Interdisciplinary Health Data Competition ($4000). Project topic: The Economic Burden of Extended-Release Pharmaceuticals in Minnesota.

    · 3/6/2020: Our research team  won the BOLD IDEAS Grant, Office of Academic Clinical Affairs, University of Minnesota ($30,000). Project topic: Using Natural Language Processing to Extract Predictors of Medical Device Adverse Events.

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