Bentley University, Bryant University, Tufts University, Nichols College present:

 Join us in-person on April 4th (Friday), 2025 hosted by Bentley University in partnership with Bryant University, Tufts University, and Nichols College.  You are cordially invited to submit your presentation for the 8th Analytics Without Borders conference. The abstract submission is open now, until Mar 22, 2025. Please click this link to submit your abstract for either oral presentation or student competition.

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. Please join to share your project, experience, and opinion, by submitting your abstract.

We welcome co-sponsors to support this annual conference. If you are interested in participating as a sponsor for our conference, please contact Mingfei Li (MLI@bentley.edu) directly. Detailed sponsorship levels and their awards can be notified later.  

Student research competition

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 three student projects in each level will receive the prestigious Excellent Student Research Award for AWB 2025. 

Student competition teams ( each team has no more than THREE students), please submit your abstract, team, and major contact person in the abstract submission form and indicate student competition presentation in the presentation preference. All students' competition presentations will be held in parallel tracks and judged by the competition committee. The winners will be announced before the closing of the conference. 

For more details, please contact the chair of the student competition committee below.

Conference Organizing Committee

Mingfei Li (Chair) (Bentley University, mli@bentley.edu)
Moinak Bhaduri (Bentley University, mbhaduri@bentley.edu)
Luke Cherveny (Bentley University, lcherveny@bentley.edu)
Kristine Cirino (Bentley University, kcirino@bentley.edu)
Mengyan Li (Bentley University, mengyangli@bentley.edu)
Tony Ng (Bentley University, tng@bentley.edu)
Jiaying Weng (Chair) (Bentley University, jweng@bentley.edu)

 

Student Competition Committee

Jiaying Weng (Chair) (Bentley University, jweng@bentley.edu)
Mengyan Li (Bentley University, mengyangli@bentley.edu)
Chandrakant Maheshwari (FVP, Lead Model Validator, Flagstar Bank)

Keynote 1: Sheamus McGovern, Founder - ODSC, Venture Partner and Head of AI - Cortical Ventures

Bio: Sheamus McGovern founded ODSC (The Open Data Science Conference), one of the world’s leading AI conferences and communities. He also serves as a Venture Partner and Head of AI at Cortical Ventures, a venture fund focused on advancing AI  and machine learning innovation. Prior to founding ODSC, Sheamus had a diverse career as a data engineer, software architect,, and AI expert. His professional journey began in finance, where he worked for leading financial institutions and quantitative hedge funds. Over the years, he has consulted with startups and enterprises in finance, healthcare, and eCommerce, helping develop cutting-edge, data-driven applications and AI solutions. Sheamus holds degrees from Northeastern University, Boston University, and Harvard University, as well as a Certificate in Quantitative Finance (CQF).

Keynote Title: coming soon
Abstract: coming soon

Keynote 2 John Chan, Ph.D., Head of ShinrAI Center for AI and Machine Learning, Takeda

Bio: John Chan is a technology executive, trained as a scientist and engineer, with over 25 years of industry experience in computational sciences and informatics. He has led computational teams, built informatics capabilities, and translated ideas into products for global biopharma and biotech start-ups. He is currently the head of the ShinrAI Center for AI and Machine Learning at Takeda. Prior to joining Takeda, John built a neuroscience AI company, Syllable Life Sciences, and as its CEO, led its acquisition by Neumora. Before Syllable, John held several contributor and management roles in computational biology, bioinformatics, and enterprise IT. This includes tenure as a visiting scientist at the Broad Institute, an Executive Director and Head of Informatics and Technology at Novartis, and the Head of computational biology at Millennium Pharmaceuticals, where he led the innovative team that fueled Millennium's drug discovery partnerships. John earned a B.Sc. in population genetics from Marlboro College and a Ph.D. in genetics and molecular biology from the University of Pennsylvania.

Keynote Title: coming soon
Abstract: coming soon

Major Talk: Victor S.Y. Lo, SVP, Data Science & AI, Fidelity Investments

Bio: Victor S.Y. Lo is a Big Data, Analytics, Marketing, and Finance leader with over three decades of extensive consulting and corporate experience employing data-driven solutions in a wide variety of business areas, including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, Healthcare, Operations Management, and Human Resources. He is a pioneer of uplift modeling, a subfield of data science.

Victor has led data science and analytics teams in multiple business units at Fidelity Investments for over two decades, and is currently SVP, Data Science & AI in Workplace Investing at Fidelity. He has pioneered many analytics practices such as marketing mix, uplift modeling, causal inference, quantitative risk analytics, healthcare analytics, and AI ethics. Prior to Fidelity, he was VP of Modeling and Analysis at FleetBoston Financial (now Bank of America) and Senior Associate at Mercer Management Consulting (now Oliver Wyman). Victor earned a master’s degree in Operational Research and a PhD in Statistics, and was a Postdoctoral Fellow in Management Science. For academic services, he has been serving on the board of the National Institute of Statistical Sciences (NISS) and the Steering Committee of the Boston Chapter of INFORMS (Institute for Operations Research and the Management Sciences), and also on the editorial boards of three academic journals including Harvard Data Science Review (HDSR) and Frontiers in AI. Additionally, he is publishing a graduate level textbook on causal inference in business (Cause-and-Effect Business Analytics and Data Science) with co-authors and has been active in research on AI ethics, causal inference, design of experiments, and prescriptive analytics.  

Major Talk Title coming soon

Abstract: coming soon

Morning Career Discussion Panel

Afternoon Career Discussion Panel

Tutorial Session