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Danielle Song wins best graduate student poster award at the Northeast Decision Sciences Institute conference.

DSLab research assistants attended the NEDSI conference (April 2022). Pictured (left-to-right): Adrian Perez, Grace Niu, Danielle Song, Claire Ding, David Kuo, Jingran Xu, Caroline Tan, and Pennart Klanwari.

DSLab researcher Danielle Song won the best graduate student poster award at the 52nd Northeast Decision Sciences Institute (NEDSI) conference in Newark, New Jersey, on April 8, 2022.  Danielle’s poster, entitled “MBTA Winter Storm Planning: Slick Road Prediction Model,” focused on her application of machine learning methods to assist the Massachusetts Bay Transportation Authority (MBTA) by creating a more timely and accurate decision support system for allocating labor and equipment resources in preparation for inclement weather.   Seven other DSLab researchers accompanied Danielle and DSLab co-director John Maleyeff to the conference, with DSLab researchers delivering two other presentations.  Pennart Klanwari presented a paper entitled “Climate Change Impacts on Boston Hospitals,” which was co-authored by Jiayi Pan, along with Dr. Canan Corlu and Prof. Dave Weidman. Claire Ding presented a paper entitled “Severity Prediction Models to Support MBTA Winter Storm Planning,” which gave a more comprehensive overview of the MBTA project.  This paper was co-authored by Ruojia Peng, along with Danielle Song and John Maleyeff.  MBTA risk management director Frans Valk and MBTA emergency management director Mark Munroe collaborated on this project. 

DSLab researchers to present three papers at NEDSI Conference in Newark NJ

Five DSLab researchers have co-authored two articles and one poster to be presented at the 52nd Northeast Decision Sciences Institute (NEDSI) meeting on April 7-9 in Newark, New Jersey. The first paper, “Severity Prediction Models to Support MBTA Winter Storm Planning,” was co-authored by Yiwei (Danielle) Song, Ruojia Peng, and Claire Ding, and will be presented by Claire at the meeting. Prof. John Maleyeff supervised this project, with collaboration from Frans Valk and Mark Munroe at the MBTA. The second paper, “Climate Change Impacts on Boston Hospitals,” was co-authored by Pennart Klanwari and Jiayi Pan, and will be presented by Pennart at the meeting.  Profs. Canan Corlu and Dave Weidman supervised this project. The poster, called “MBTA Winter Storm Planning: Slick Road Prediction Model,” was prepared by Danielle Song. It will be entered in a master’s student competition to be held at the conference.

Nine of the 10 current DSLab researchers are expected to attend the conference, along with John Maleyeff and Canan Corlu.

DSLab Welcomes New Researchers

The DSLab welcomes six new research team members for the Spring 2022 semester.  They are all M.S. students at Metropolitan College: Adrian Perez (Supply Chain Management), Ching-Wei (David) Kuo (Supply Chain Management), Jingran Xu (Applied Business Analytics), Xiaomeng (Grace) Niu (Enterprise Risk Management), Valeria Kaffaty (Supply Chain Management), and Yuxin (Alex) Yang (Applied Business Analytics). They will work on projects that include MBTA winter storm planning, mitigating climate change impacts on Boston hospital supply chains, long tail demand inventory modeling, and MBTA repair parts inventory control.

MET Decision Sciences Lab (DSLab) researchers visit the new MBTA Green Line extension project.

Danielle Song, Chloe Peng, and Claire Ding (pictured, with MBTA project contact Frans Valk), along with Professor John Maleyeff (co-director of the DSLab) visited the Somerville headquarters of the MBTA Green Line extension project on December 6. This project will enable 80% of Somerville residents to live within walking distance of a “T” stop (up from the current 20% of residents).  The researchers learned about new and existing issues that affect their DSLab project. This project uses analytical modeling to help the MBTA allocate resources in an efficient and timely manner during winter storms. Danielle, Chloe, and Claire are MET administrative sciences master’s students. More information about this and other DSLab projects can be found here: https://sites.bu.edu/met-dslab/

DSLab Research Presented at Annual DSI Meeting

Three DSLab projects were presented at the annual Decision Sciences Institute (DSI) meeting in November 2021. Yujue (Caroline) Tan (ERM student) made a presentation entitled “Post-Pandemic Business Continuity Planning for Biotechnology & Pharmaceutical Startups: Analysis & Recommendations.” The DSLab researchers who co-authored the article were Yueyi (Queena) Ma (ERM graduate), Yuanfei (Fibby) Zang (ERM graduate), and Zhenyan Yin (ABA student).  Yuzhen Liang (ABA student) made a presentation entitled “Queue Modeling for Decision Support at a Henkel Call Center.”  The DSLab researchers who co-authored this article were David (Da Wei) Cadreact (SCM graduate) and Mingxuan (Bella) Zhang (SCM graduate). Alexandra Malaspina from Henkel was also a co-author. The third presentation was delivered by co-director John Maleyeff, entitled “Knee Optimization for Queuing Systems: A Customized Approach.” DSLab researcher Danqi Lu (ABA graduate) was the first DSLab researcher to be designated as first author of a published work.

All three articles were published in the conference proceedings, found here:  

https://decisionsciences.org/wp-content/uploads/2021/11/Dsi-annualconference2021.pdf

Danielle Song presented the MBTA winter storm planning project at the INFORMS Annual Meeting.

On October 26, the DSLab MBTA winter storm planning project was presented by Danielle Song at the 2021 annual conference of INFORMS (The Institute for Operations Research and the Management Sciences). The session, Decision Analysis in Practice, showcased four projects that effectively applied analytical approaches to solve problems in business and industry. Danielle presented her team’s work on the winter storm planning decision support system that will be tested this winter. Other contributors to this project include DSLab researchers Jennifer Li, Tracy Ning, Claire Ding, and Chloe Peng.

DSLab Welcomes New Researchers

The DSLab welcomes five new research team members.  Four of them are M.S. students at Metropolitan College: Jiayi Pan (Supply Chain Management), Pennart Klanwari (Supply Chain Management), Ruojia Peng (Applied Business Analytics), and Xiaotong Ding (Applied Business Analytics). The fifth is Cas Rosman, a visiting researcher who is completing his M.Eng. degree in Manufacturing Systems Engineering at Eindhoven University of Technology in the Netherlands.

Three DSLab articles accepted for DSI conference presentations

DSLab researchers had three papers accepted for presentation at the 2021 Decision Sciences Institute conference, to be held virtually in November 2021.  The three papers are:

  1. Post-Pandemic Business Continuity Planning for Biotechnology & Pharmaceutical Startups: Analysis & Recommendations (researchers Caroline Tan, Queena Ma, Fibby Zang, and Evan Yin).
  2. Queue Modeling for Decision Support at a Henkel Call Center (researchers Yuzhen Liang, Dave Cadreact, and Bella Zhang, with Henkel Corporation collaborator Ally Malaspina).
  3. Knee Optimization for Queuing Systems: A Customized Approach (researcher Danqi Lu).

DSLab Summer 2021 Symposium was held on June 15; click here to see the presentations.

Using Analytics and Visualizations for MBTA Winter Storm Planning (researchers Danielle Song, Tracy Ning, and Jennifer Li – with MBTA collaborators Jesse Biroscak & Frans Valk). This project was presented at the City Innovate STIR Labs Summit on June 8, 2021.

 

Queue Modeling for Decision Support at a Henkel Call Center (researchers Yuzhen Liang, Bella Zhang, and Dave Cadreact – with Henkel collaborator Alexandra Malaspina). This project was presented at the Northeast Decision Sciences Institute (NEDSI) conference on March 26, 2021.

 

Post-Pandemic Business Continuity Planning for Biotechnology & Pharmaceutical Startups: Analysis & Recommendations (researchers Queena Ma, Caroline Tan, Evan Yin, and Fibby Zang). This project has been submitted for presentation at the Decision Sciences Institute (DSI) conference to be held in November 2021.

 

Machine Learning Approach to Fast-Paced Priority Dispatching of Nurses – a collaborative project with the Grand Valley State University College of Nursing (researchers Kaming Yip & Yuzhen Liang – with Grand Valley State University School of Nursing collaborator Marie Vanderkooi). This project was awarded a BU Institute for Health Systems Innovation & Policy (IHSIP) summer 2021 research grant.

 

Knee Optimization for Queuing Systems: A Customized Approach (researcher Danqi Lu). This project was presented at the Production & Operations Management (POMS) conference on May 3, 2021.