BCASA Annual Winter Party
Join us this January for the Boston Chapter of the American Statistical Association's Annual Winter Social Gathering, now coming to you virtually via Zoom. In this beloved BCASA tradition, let's reconnect, share stories, and uplift each other as we look forward to a brighter 2024. Don't miss this evening of laughter, conversation, and community as we toast resilience and the promise of better times ahead. See you there!
Date: Thursday, January 11, 2024
Time: 6-7:30pm EST
Cost: Free
Registration:
Annual BCASA Winter Social
A Zoom link will be sent in advance to all who sign up.
Interested in knowing what the previous Winter Party looked like? Check out the details from the BCASA newsletter:
2023 Winter Party
Happy Holidays and Look forward to seeing you at the party!
Boston Chapter of American Statistical Association: 2023 Outstanding Teaching Award Presentation
The Boston Chapter of the ASA is delighted to recognize Dr. Kylie Bemis with the 2023 Outstanding Teaching Award. A reception honoring Dr. Bemis for the award will be held. This reception is a collaboration between the Boston Chapter and Khoury College of Computer Sciences at Northeastern University. The event will include Kylie’s presentation “Outliers, Life in the Tails, and the Statistics We Don’t Plot” followed by light appetizers and refreshments.
Date: 6:00 – 8:00pm (ET), January 31, 2024
Location: Northeastern University 102 lab, West Village Residence Complex H, 440 Huntington Ave, Boston, MA 02115
Registration
Honoree and Speaker: Dr. Kylie Bemis, Assistant Teaching Professor at Northeastern University
Presentation Title: Outliers, Life in the Tails, and the Statistics We Don’t Plot
Abstract: At the end of 2016, to the best of my knowledge, I became the first Native American to earn a PhD in Statistics. In that same year, I came out as a trans woman. Statisticians have long understood that how we handle outliers, missing values, and sampling bias can have a dramatic impact on outcomes. The same is true in teaching and society at large. As we train the next generation of statisticians and data scientists, it is vital that our students see themselves reflected in their work, and that they understand the social responsibility of analyzing and interpreting data for a diverse world. I will share what I have learned about teaching as a statistician who has rarely seen herself reflected as a category in a bar plot, and what it means to be a statistic.
Bio: Kylie Bemis is an Assistant Teaching Professor in the Khoury College of Computer Sciences at Northeastern University. She holds a B.S. degree in Statistics and Mathematics, a M.S. degree in Applied Statistics, and a Ph.D. in Statistics from Purdue University. In 2013, she interned at the Canary Center at Stanford for Cancer Early Detection, where she developed the Cardinal software package for statistical analysis of mass spectrometry imaging experiments. In 2015, she was awarded the John M. Chambers Statistical Software Award by the American Statistical Association for her work on Cardinal. In 2016, she joined the Olga Vitek lab for Statistical Methods for Studies of Biomolecular Systems at Northeastern University as a postdoctoral fellow. In 2019, she joined Northeastern as faculty, where she now teaches data science and develops curriculum for the M.S. in Data Science program. Her research interests include machine learning and large-scale statistical computing for bioinformatics.
While at Purdue University, Kylie Bemis served as president of the Purdue chapter of the American Indian Science and Engineering Society (AISES) and secretary of the Native American Student Association (NASA). She is active in outreach to the Native American and LGBTQ communities. She is an enrolled member of the Zuni tribe, and she is a writer of fiction and poetry. Her short fiction has appeared in the anthologies Nameless Woman: An Anthology of Fiction by Trans Women of Color (2018), Maiden Mother Crone: Fantastical Trans Femmes (2019), and Transcendent 4: The Year’s Best Transgender Themed Speculative Fiction (2019).
About the Award: the Boston Chapter presents the Boston Chapter’s Outstanding Teaching Award to acknowledge a distinguished faculty member who has made exceptional accomplishments in statistics and data science education.
Introduction to Data Science Workshop for High School Students
The Boston Chapter of the American Statistical Association and the Harvard T.H. Chan School of Public Health are delighted to host an engaging one-day workshop for high school students. This event serves as an introduction to the exciting fields of statistics and data science, specifically tailored for participants with no prior coursework or experience in these areas. Attendees can anticipate an interactive and informative session designed to ignite interest and curiosity in the dynamic world of statistics and data science.
Throughout the workshop, students will gain hands-on experience in visualizing and summarizing data using R. Don't forget to bring your laptop computer for an enriched learning experience!
Registration
DETAILS:
Date: Saturday, February 10, 2024
Venue: Dept. of Biostatistics, Harvard T.H Chan School of Public Health
Time: 10 am - 4 pm LUNCH WILL BE PROVIDED
AGENDA (tentative):
10am: Introduction to data science with Dr. John Quackenbush
11am: Session 1(Introduction to R) with Dr. Kathryn Schaber
12:30pm: Lunch
1:30pm: Session 2 (Modeling) with Dr. Nestor Hernandez
Hurry Up! The registration deadline is Feb 3rd.
Boston Chapter Webinar: Statistical Thinking in the Age of AI for Drug Development: A Regulatory Perspective, with Dr. Zhiheng Xu
Join the Boston Chapter of the ASA for a webinar with Dr. Zhiheng Xu, as he talks from a regulatory perspective about the potential of AI in drug development and the statistical challenges it presents. Below is the detail about the event.
Time/Date: 12:00 – 1:00pm (ET), Feb 23, Friday, 2024
Location: online (Zoom link will be provided to attendees one day before the event)
Cost: Free
Registration
Speaker: Dr. Zhiheng Xu, Lead Mathematical Statistician in the hematology division (DBIX) at FDA/CDER Office of Biostatistics, US Food and Drug Administration and the President for the FDA Statistical Association in 2023
Presentation Title: Statistical Thinking in the Age of AI for Drug Development: A Regulatory Perspective
Abstract: Artificial Intelligence (AI) has shown great potentials in advancing drug development, particularly in areas such as drug discovery, disease diagnostics, clinical research, real-world data (RWD) and digital health technologies (DHTs). This development is fueled by the exponential growth in computer power and data accessibility. However, there are concerns related to explainability, reliability, privacy, safety, security, and bias mitigation. For example, the complexity of AI algorithms, the data-driven nature in which they are trained, and the unique characteristics of clinical data create challenges in developing robust evaluation methods for AI algorithm. In this talk, I will delve into the statistical hurdles associated with the use of AI in drug development and explore how a vigorous statistical thinking can ensure that data-driven conclusions are not only accurate but also robust and reproducible.
Bio: Zhiheng Xu has over a decade of experience in regulating drugs and medical devices at the FDA. He is the lead mathematical statistician in the hematology division (DBIX) at FDA/CDER Office of Biostatistics. Before that, he was a mathematical statistician with FDA/CDRH since 2012. He was the president for the FDA Statistical Association (FDASA) in 2023 and currently serves as the program co-chair for 2024 American Statistical Association (ASA) Biopharmaceutical Section Regulatory Industry Statistical Workshop (RISW). Zhiheng received his Ph.D. in Biostatistics from Emory University in 2011. His research interests include real-world data, innovative trial design, dose finding, biomarker evaluation and digital health. In his spare time, he likes reading, gardening, running, and swimming. He is also a content creator on LinkedIn.
The 7th Analytics Without Borders Conference
The 7th Analytics Without Borders Conference is organized Organized by Bryant University’s Tom Dougherty, Executive in Residence, Information Systems and Analytics and Assistant Professor Tingting Zhao, Ph.D., the 7th annual Analytics Without Borders Conference will be held on March 22, 2024.
The conference is an intercollegiate endeavor which is co-sponsored by Bryant University, Tufts University, Bentley University and Nichols College. This program attracts approximately 150 attendees from the four institutions including undergraduate and graduate students and faculty members. This year, we will also be joined by students from UMass Lowell and Babson College.
The 2024 conference features keynote presentations from leaders in the field including Todd Gustafson, President of HP Federal LLC and Head of Public Sector HP, Inc. (confirmed) and Michael Jabbour, Chief Innovation Officer of Microsoft (invited). A career panel as well as student research presentations showcasing some of the best data science and analytics students in the region complement the day. The breakout of student presentations by school includes: UMass Lowell (12), Bryant University (6), Bentley University (3), Babson College (2), and University of Montenegro (1). It will be the first in person convening of this program since 2020 and the Covid-19 pandemic.
You are cordially invited to submit your presentation for the 7th Analytics Without Borders conference. This conference marks our return to in-person gatherings following the COVID pandemic.
The conference serves as a platform for individuals involved in various aspects of analytics to present and discuss their work, whether they come from corporate institutions, academia, or government organizations. This event aims to foster collaboration and bridge-building among diverse analytics communities.
The conference covers a wide range of topics in analytics, including applied statistics, optimization, data science, and more. We welcome anyone who works with data to share their insights. The conference sessions will feature a blend of corporate, academic, and government researchers and practitioners.
We strongly encourage both undergraduate and graduate students to submit their research or side projects. Moreover, we are excited to announce a student research competition during the conference, open to participating graduate and undergraduate students. The top five students in each group will receive the prestigious Excellent Student Research Award for AWB 2024.
The deadline for submissions is March 1, 2024. Please visit our online submission page for details.
For additional information, please see the Analytics Without Borders Conference Flyer and explore our conference website at the 7th Analytics Without Borders Conference.
ASA Boston Chapter is a proud sponsor of this conference.
New England Student Research Symposium on Statistics and Data Science
Join the Boston Chapter of the ASA and student chapters from Bentley, Boston University, Holy Cross, and Tufts for a day of insightful presentations by undergraduate and graduate students from across New England. This symposium offers a unique opportunity to connect with peers, receive feedback, and network with industry professionals.
Online Registration
Date/Time: April 20, 2024, Saturday, 10:00 AM - 4:00 PM EST
Location: Boston University, Center for Computing and Data Sciences (CDS)
Keynote Speaker: Olga Vitek, Raymond Bradford Bradstreet Professor
Keynote Talk Description: "Proteomic Investigations of Biomolecular Systems: Importance of a Statistical Mindset and Lessons Learned" - The talk will delve into the significance of statistical approaches in proteomic research and the insights gained from such investigations.
Registration and Abstract Submission Guide:
- Register now using the QR code provided in the flyer.
- Abstract submission closes on April 6, 2024.
- Students interested in presenting a talk (either a 15-20 minute talk or a 3-5 minute lightning talk) or an ePoster can submit their title and abstract while registering using the appropriate "ticket" category on Eventbrite.
- Space is limited, and priority is given to early submissions.
For more details, please refer to the flyer.
2024 Mosteller Statistician of the Year Award Reception
The Boston Chapter of the American Statistical Association is thrilled to announce that Dr. Susan A. Murphy, Mallinckrodt Professor of Statistics and of Computer Science and Associate Faculty at the Kempner Institute of Harvard University, is the esteemed recipient of the 2024 Mosteller Statistician of the Year Award.
This reception is organized by the Boston Chapter. The event will include Susan's presentation "Online Reinforcement Learning in Digital Health Interventions". Light appetizers and refreshments will be served.
Honoree and Speaker: Dr. Susan A. Murphy, Mallinckrodt Professor of Statistics and of Computer Science and Associate Faculty at the Kempner Institute of Harvard University
Date: April 12, 6:00 - 8:00 PM (ET)
Location: The West Atrium of the Science and Engineering Complex, 150 Western Avenue, Allston, MA 02134
Registration
Presentation Title:
Online Reinforcement Learning in Digital Health Interventions
Abstract:
In this talk I discuss first solutions to some of the challenges we face in developing online RL algorithms for use in digital health interventions targeting patients struggling with health problems such as substance misuse, hypertension and bone marrow transplantation. Digital health raises a number of challenges to the statistical RL community including different sets of actions, each set intended to impact patients over a different time scale; the need to learn both within an implementation and between implementations of the RL algorithm; noisy environments and a lack of mechanistic models. In all of these settings the online line algorithm must be stable and autonomous. Despite these challenges, RL, with careful initialization, with careful management of bias/variance tradeoff and by close collaboration with health scientists can be successful. We can make an impact!
About the Awardee: Dr. Murphy's groundbreaking research focuses on improving sequential decision making in health, currently online, real-time learning algorithms for developing personalized digital health interventions. She is a member of the US National Academy of Sciences and of the US National Academy of Medicine. In 2013 she was awarded a MacArthur Fellowship for her work on experimental designs to inform sequential decision making. She has had a remarkable impact on the real-world practice of clinical trials in medical and behavior science through her research as well as efforts to promote adaptive intervention. She is a Fellow of the College on Problems in Drug Dependence.
Dr. Murphy's services to the professional community are equally outstanding. Her leadership as the former President of both IMS and Bernoulli Society, the former Editor of Annals of Statistics, and the former Chair of the Interest Group on Health and Technology of the National Academy of Medicine highlight her long-time dedication to the field. She has served on a large number of committees of professional societies and on many NIH and NSF review panels. She has trained many students and postdocs, many of whom have achieved faculty positions in leading statistics departments and received student paper awards.
The Boston Chapter of the ASA is proud to recognize Susan for her seminal achievements and contributions. An award reception is planned to occur on an evening of the second week in April 2024 at Harvard University. Details about this reception and the presentation will be announced soon.
About the Award: Every year the Boston Chapter presents the Mosteller Statistician of the Year award to a distinguished statistician who has made exceptional contributions to the field of statistics and has shown outstanding service to the statistical community, including the Boston Chapter. The award was originally established in 1990 as the Statistician of the Year Award. In 1997, this award was renamed the Mosteller Statistician of the Year award in honor of the 80th birthday of its first recipient, Fred Mosteller.
For a historical perspective on the award and its past recipients, please visit Boston Chapter's Mosteller Statistician of the Year Award.
BCASA FALL SOCIAL
Enjoy gathering with fellow chapter members to enjoy Art and Music at the
Out of the Blue Community Arts Gallery Performance Space
Date: Saturday, September 28, 2024 (rescheduled time)
Time: 1:00 pm -4:00 pm, (Rain or Shine)
Location: Out of the Blue Community Arts Gallery
Performance Space
191 Highland Ave Ground Floor, B6 Suite.
Somerville, MA 02134
Reservations are Going Fast! Limited to the First 40.
Directions:
Accessible by public transport (Fitchburg commuter line, Green Line B, C, D, Red Line) or by car (parking details provided upon registration)
Handicap Accessible (elevator)
Contact Info: Available upon event registration.
What to Bring: Your favorite story. The dress is casual.
Menu: Salads, Sandwiches, Seltzers, Soda, Beer, Wine, Coffee, Cookies & Pastries
Host: This event is hosted by the Boston Chapter of the American Statistical Association.
The Eventbrite Reservation Site: BCASA Fall Social
Expresso Your Professional Future: A Coffee Chat with Academic Statisticians hosted by the BCASA
Join us for a virtual coffee chat organized by the Boston Chapter of the ASA.
📅 Date: September 18
⏰ Time: 4:00 PM – 6:00 PM (EST)
📍 Location: Zoom
🔗: https://lnkd.in/eTspsZND
The first session is a one-hour panel discussion, focusing on the statisticians in academia, and is your gateway to insights on:
Finding full-time positions: What to look for and where to start.
Resume Crafting: How to make your resume stand out.
Preparing for Interviews: Tips and expected questions for interviews.
Becoming a Full-Time Employee as an academic statistician: Skills needed and transition guidance.
Featured Panelists:
Kristin Baltrusaitis, Research Scientist at CBAR, Harvard T.H. Chan School of Public Health.
Marie-Abèle Bind, Assistant Professor of Medicine at Harvard Medical School and Assistant Investigator at MGH Biostatistics.
Zeyuan Song, Senior Statistician, Tufts Medical Center.
After the panel discussion with live Q&A, there will be an opportunity for attendees to participate in 1-1 coffee chats in breakout Zoom rooms. Whether you're starting to think about a future career or seeking guidance for full-time employment, this coffee chat is tailored to your needs.
ASA Traveling Course: Fundamentals of Causal Inference: With R
Registration: Eventbrite_ASA_traveling_course
Instructor:
Dr. Babette Brumback, Professor Emerita, University of Florida Department of Biostatistics
Date and time: Saturday, Oct 5, 8:30 - 4:00
Format: Virtual
Description:
One of the primary motivations for clinical trials and observational studies of humans is to infer cause and effect. Disentangling causation from confounding is of utmost importance. Fundamentals of Causal Inference: With R explains and relates different methods of confounding adjustment in terms of potential outcomes and graphical models, including standardization, doubly robust estimation, difference-in-differences estimation, front-door estimation, and instrumental variables estimation. These methods are compared in terms of estimating the average effect of treatment on the treated (ATT). The fundamentals of mediation analysis and adjusting for time-dependent confounding are also presented. Several real data examples, simulation studies, and analyses using R motivate and illustrate the methods throughout.
The course assumes familiarity with basic statistics and probability, regression, and R. The course will be taught with a blend of lecture and worked examples.
Detailed program for an eight-hour course with four modules:
Module 1 (8:30 - 10 AM): Introduction
a) Definitions and Datasets
b) Potential Outcomes Framework
c) Directed Acyclic Graphs
15 mins - break
Module 2 (10:15 - 11:45 AM): Adjusting for Confounding Part One
a) Standardization
b) Difference-in-Differences Estimation
60 mins – break
Module 3 (12:45 - 2:15 PM): Adjusting for Confounding Part Two
a) Front-Door Estimation
b) Instrumental Variables Estimation
c) Comparison of the Four Methods (in terms of estimating the average effect of treatment on the treated, or ATT)
15 mins - break
Module 4 (2:30 - 4:00 PM): More Advanced Topics
a) Mediation
b) Time-Dependent Confounding
About the instructor
Dr. Babette Brumback is known for her work on causal inference. She is the author of the recently published textbook, Fundamentals of Causal Inference: With R. Babette is Professor Emerita of Biostatistics at the University of Florida, and she is an elected member of Delta Omega and a Fellow of the American Statistical Association. Babette’s statistical research has concentrated on methods for longitudinal data analysis, causal modeling, bias adjustment, and analysis of data from complex sampling designs. She has also collaborated extensively on public health and medical studies concerning a broad array of research areas.
Boston Chapter Webinar: Development of Gene Therapies: Open Questions on Design, Analysis, and Statistical Strategy, with Dr. Avery McIntosh and Dr. Oleksandr Sverdlov
Join the Boston Chapter of the ASA for a webinar with Dr. Avery McIntosh and Dr. Oleksandr Sverdlov, as they talk about the history and future of gene therapies from a statistical perspective. Below is the detail about the event.
Time/Date: 11:00 – 12:00pm (ET), Dec 6, Friday, 2024
Location: online (Zoom link will be provided to attendees one day before the event)
Cost: Free
Registration
Presentation Title: Development of Gene Therapies: Open Questions on Design, Analysis, and Statistical Strategy
Abstract: One of the recent advances in 21st-century medicine is the emergence of gene therapies, drugs that affect the basic biology of genetic disease. The field has seen some notable setbacks in the past, but in recent years has exploded as decades of basic science have been successfully translated into the most complex biologics ever constructed, leading to regulatory approval of several gene therapy products in oncology, hematology, neurology, and ophthalmology indications. These drugs are at the apex of biological manufacturing complexity, and have the potential to be disease modifying or even curative. Evidence-based and innovative quantitative clinical development and lifecycle management strategies will be required as fixtures in the development for these unique drugs in order to reach patients in need. In this webinar we provide an overview of the history and future of gene therapies, and discuss the crucial role of the statistician in the drug development process of these drugs, with a focus on innovative trial design and analysis techniques.
About the Speakers:
Avery McIntosh, PhD is a drug developer working in internal medicine and rare disease at Pfizer. He received his MSc and PhD in biostatistics from Boston University with a dissertation on Bayesian methods to model household tuberculosis transmission. He has managed teams of statisticians across study phases and in a variety of drug types and disease areas, including neurology, ophthalmology, infectious disease/global health, hematology, and oncology. He has published peer-reviewed articles on various topics in drug development and biostatistics, including development of cell and gene therapies and qualification of digital endpoints in neurological diseases.
Oleksandr Sverdlov, PhD is a Neuroscience Disease Area Statistical Lead at Novartis. He earned his BSc in Applied Mathematics from V.N. Karazin Kharkiv National University, Ukraine, MSc in Statistics from University of Maryland, Baltimore County (UMBC), and PhD in Information Technology with Concentration in Statistical Science from George Mason University. He has been actively involved in methodological research and applications of innovative statistical approaches in drug development. He has co-authored over forty refereed articles, edited two monographs, and co-authored a book “Mathematical and Statistical Skills in the Biopharmaceutical Industry: A Pragmatic Approach” (CRC Press/Chapman & Hall, 2019). His most recent work involves design and analysis of clinical trials evaluating novel digital technologies.
Avery and Alex have a book published recently "Development of Gene Therapies: Strategic, Scientific, Regulatory, and Access Considerations."
25th Annual New England Isolated Statisticians Meeting
We are pleased to invite you to the 25th Annual New England Isolated Statisticians Meeting (NEISM25) which will be held on Saturday, November 9th, 2024, from 9:00 am – 4:30 pm at Stonehill College. This event is a wonderful opportunity for isolated statisticians (usually, but not always, in mathematics departments) to network with other statisticians, learn best practices, discuss current trends, and have a little fun!
At this, our 25th meeting, we are honored to welcome our keynote speaker, Dr. Richard De Veaux from Williams College, who will present on the timely and critical topic of data ethics, ensuring that we not only teach our students how to handle data but also how to do so responsibly.
Our theme, "The Past, Present, and Future of Statistics in Higher Education," invites us to explore the evolving landscape of statistics education. We’ll begin by examining how students are introduced to statistical concepts in K-12 settings and discuss how prepared they are for college-level courses. In the present, we'll dive into what a modern college statistics course looks like, exploring innovative teaching methods and technologies that are shaping the way students engage with data. Finally, we'll look ahead to the future, focusing on how we can equip our students to become data-minded thinkers, prepared to meet the demands of their future careers in an increasingly data-driven world.
Join us for a day of insightful discussions, collaborations, and forward-thinking ideas as we chart the course for the future of statistics education.
The registration fee for the event is $20 and is non-refundable. Please click on the link to register.
Please contact anyone on the planning committee if you have any questions.
The NEISM 25 Planning Committee
This meeting is sponsored by NEISM with support from the Boston Chapter.
************************Regional Events**************************************************************************************************
Women in Data science (WiDS) Cambridge Conference
This conference is taking place Friday, March 8th, 2024 from 8:00am - 4:30pm ET at Microsoft New England (NERD Center) in Cambridge, MA. Registration closes Friday March 1st, at 2pm EST.
For the eighth year, MIT, Harvard, and Microsoft New England are proud to collaborate with Women in Data Science (WiDS) Worldwide to bring the WiDS regional conference to Cambridge, Massachusetts.
This one-day conference will feature an all-female lineup of speakers and panelists from academia and industry to talk about the latest data science-related research in several domains, to learn how leading-edge researchers and companies are leveraging data science for success.
Click here to register!
The program will include:
- Keynote speaker: Fotini Christia, Ford International Professor of the Social Sciences
Director, MIT Sociotechnical Systems Research Center (SSRC), MIT
- Plenary Speakers/technical talks:
Danisha Baker, Data Scientist, Statistician
Elizabeth Lingg, Principal Software Engineering Manager at Microsoft
- Morning Panel: Data Science for Humanitarian Work in Conflict Zones
Moderator: Natalie Ayers, Panelists: Rana Hussein, Aarathi Krishnan, and Erica Nelson,
- Afternoon Panel: Responsible AI: Democratization of AI Tools & AI for Sustainability
Moderator: Nishtha Sardana, Panelists: Lindsey Batteast, Priya L. Donti, and Minsoo Thigpen
- Poster sessions with students and researchers
- Lightning talks
- Career development and networking opportunities
For additional information, see the conference website.
Registration for the conference closes on Friday March 1st, at 2pm EST. Be sure to get your ticket before then!
Email wids-cambridge@mit.edu with any questions regarding the conference.
Data Analytics Pre-College Program for Teens
Bentley University is currently accepting applications for Analytics Academy, one of Bentley’s premier pre-college summer programs. If you know a high school student who is interested in analyzing data to answer complex questions, then you should check out Bentley University’s Analytics Academy!
Analytics Academy has a cutting-edge curriculum that offers rising high school juniors and seniors a unique opportunity to discover the vast power of data and analytics. Additionally, Bentley University will be offering 10 students who are referred to the program by an ASA Boston Chapter member a 50% discount scholarship!
Through hands-on lessons, students will develop practical skills and knowledge needed to perform modern data analysis. The program is taught by Bentley professors and industry professionals who will give insight into how data impacts our world and day-to-day lives. The week will culminate with a capstone project, where students apply their newfound skills in a real-world setting.
Bentley's pre-college programs offer unique opportunities for high school students to experience residential college life. Students stay in a college dorm, eat in the dining halls, and build meaningful friendships both inside and outside the classroom. Students can gain valuable insights into their academic interests and career aspirations by immersing themselves in a rigorous and supporting learning environment.
Two one-week sessions will be offered this summer:
June 24th to June 28th
July 22nd to July 26th
If your student is interested in data analytics, or looking for something interesting to do this summer, join us for an exciting week!
The application is now available. To refer a student and make them eligible for a 50% discount scholarship, the student should apply using waiver code “AnalyticsAcademy2024”. Applications are due by June 1st.
Bentley University Pre-College Programs
precollege@bentley.edu
781-891-2545