INFORMS Open Forum

INFORMS Boston Chapter Talk on Wednesday, 13 December 2023 - "Model Thinking for Everyday Life" by MIT Professor Richard Larson, 6:30 PM with refreshments and talk at 7:00 PM at MITRE Corporation, 202 Burlington Road, Bedford, MA. Room 1C103 (C building)

  • 1.  INFORMS Boston Chapter Talk on Wednesday, 13 December 2023 - "Model Thinking for Everyday Life" by MIT Professor Richard Larson, 6:30 PM with refreshments and talk at 7:00 PM at MITRE Corporation, 202 Burlington Road, Bedford, MA. Room 1C103 (C building)

    Posted 11 days ago
      |   view attached

    Please join the INFORMS Boston Chapter for a meeting and talk by MIT Professor Richard Larson!  Details below and a map of MITRE is attached to this announcement. Please is at MITRE in Bedford, MA and RSVP/registration required.



    Date: Wednesday, 13 December 2023<o:p></o:p>


    Time: Meet at 6:30 pm with refreshments, Talk: 7 – 8 pm<o:p></o:p>


    Title:  Discussion of a new book: Model Thinking for Everyday Life<o:p></o:p>


    Speaker: Professor Richard Larson, Mitsui Professor, Institute for Data, Systems, and Society, Massachusetts Institute of Technology<o:p></o:p>


    Location:  The MITRE Corporation, 202 Burlington Road, Bedford, MA.  Room 1C103 (C Building).  Attached is a map<o:p></o:p>


    Logistics: <o:p></o:p>

    ·        All attendees must register provide their name, email, phone number, company affiliation, country of citizenship. The due date is 7 Dec for US citizens and 29 Nov for non-US citizens.    Email RSVP to with subject Boston INFORMS meeting. <o:p></o:p>

    ·        Cost: $0.<o:p></o:p>

     Abstract <o:p></o:p>


    This active-learning book, published by INFORMS, is designed to be engaging, interactive, instructive, and fun! The reader will use a sharpened pencil and a Blank Sheet of Paper to move forward on many topics. A key motivation is our perception that much "learning" these days takes place on the computer. People often confuse a Google search with learning. They confuse dropping data into a "plug and chug" algorithm with learning. With reliance on technology, they have lost track of orders of magnitude, losing ability to guestimate the approximate answer to a problem. Faced with a new problem, people often lack the ability to frame and formulate it using basic principles.  So, we move ahead with all computers off, our only technology being a sharpened pencil and a Blank Sheet of Paper. <o:p></o:p>


    Model thinking has two equally important and related interpretations: (1) thinking aided by conceptual and/or mathematical models and (2) exemplary thinking-a type of thinking to be emulated. Just like there are "model citizens," we can have, "model thinkers!" In many problems, both interpretations of model thinking can help to get us to where we want to go-to full problem comprehension. For instance, a model thinker will often utilize mathematical or conceptual models as part of her analysis of a problem. And we would hope that those who primarily use such formal models in their work are also model thinkers more broadly!<o:p></o:p>

    Model thinking goes hand in hand with "discovery learning."  By applying methods of model thinking to a previously unanalyzed (by you) process, you yourself discover and then understand the full operation of the process.  This is much better than simply seeking "an answer" via a search engine, writing it down and soon forgetting it.  Discovery learning tends to be remembered learning.  Benjamin Franklin summarized it well:  "Tell me and I forget. Teach me and I remember. Involve me and I learn."<o:p></o:p>



    Prof. Richard Larson's career has focused on operations research as applied to services industries. He is author, co-author or editor of six books and author of over 75 scientific articles, primarily in the fields of technology-enabled education, urban service systems (esp. emergency response systems), queueing, logistics and workforce planning.  His latest book, published this year by INFORMS, is "Model Thinking for Everyday Life, How to make smarter decisions." (available on Amazon).<o:p></o:p>

    Dr. Larson is inventor of the Hypercube Queueing Model - for deploying urban emergency services - and the Queue Inference Engine, using 'big data' to determine the performance of technology-enabled queues such as automatic teller machines. Known as "Dr. Queue", Dr. Larson has appeared extensively in national and international media. He is a Founding Fellow of The Institute for Operations Research and the Management Sciences (INFORMS), past president of the Operations Research Society of America (ORSA), past president of INFORMS, and a member of the U.S. National Academy of Engineering.<o:p></o:p>

    Dr. Larson is principal investigator of the MIT BLOSSOMS Initiative, which offers a series of freely available interactive video lessons for classrooms; he is founder and director of MIT LINC (Learning International Networks Consortium), which promotes digital learning technologies to advance quality education worldwide.<o:p></o:p>

    Daniel Rice


    Map Bedford Campus.docx   456 KB 1 version