Information about NISS hosted or sponsored events that are set up in a series that support a common purpose or topic.
To review the recordings of all previous events, visit the Meet-Up Recordings page.
NISS Hosted Webinar Series
Forums honoring the memory of Professor Ingram Olkin focus on a current societal issue that could benefit from attention from the statistical community.
Ingram Olkin Forum: The Opioid Crisis (May 4, 2021)
Ingram Olkin Forum: Algorithmic Fairness and Social Justice (September, 2020)
Ingram Olkin Forum Series: Unplanned Clinical Trial Disruptions (Summer / Fall 2020)
Inaugural Ingram Olkin S3 Forum: Gun Violence - The Statistical Issues (June 2019)
NISS / Merck Meet-ups
Topics and issues of interest to biostatisticians, statisticians and epidemiologists related to the pharmaceutical industry.
"NISS/Merck Meetup Reviews the Challenges and Potential in Vaccine Development" (September 16, 2020)
"Bayesian Statistics the Focus of Popular NISS/Merck Meetup" (April 27, 2020)
"Recent Approaches to Adaptive Trials for Drug Development the Focus of NISS/Merck Meet-Up" (January 15, 2020)
"Subgroup Analysis" (Septermber 10, 2019)
"Applications of Real World Data" (April 1, 2019)
"Statistical Challenges in Immuno-Oncology" (January 22, 2019)
"Real World Data and its Applications in the Pharmaceutical Industry" (October 4, 2018)
"Applications of Machine Learning in the Pharmaceutical Industry" (April 25, 2018)
"Estimands and Sensitivity Analysis in Clinical Trials" (January 23, 2018)
"Multiple Endpoints in Clinical Trials" (September 12, 2017)
Data Science Essentials for Business
Tutorials that focus on the Top 10 analytics approaches for the key topics that are used in the business.
July 29, 2020: Overview: "Victor Lo Sets the Stage for a New Series of Tutorials: Essentials of Data Science for Business" - Victor Lo (Fidelity Investments)
October 7, 2020 - James Harner: "Data Science Workflows" (see event page)
October 21, 2020 - Lee Wilkinson: "Descriptive Analytics, Exploratory Data Analysis, and Data Visualization" (see event page)
November 4, 2020 - Yanling Zuo: "Predictive Analytics and Machine Learning" (see event page)
November 18, 2020 - Victor Lo & Dominique / Jonathan Haughton: "Causal Inference and Uplift Modeling" (see event page)
December 2, 2020 - Ming Li: "Deep Learning" (see event page)
Winter 2021 /Instructor TBA: "Prescriptive Analytics and Optimization"
Winter 2021 /Instructor TBA: "Unstructured Data Analysis"
Winter 2021 /Instructor TBA: "Social Sciences and Data Science Ethics"
Winter 2021 /Instructor TBA: "Domain Knowledge and Case Studies"
Winter 2021 / Sam Woolford: "Analytical Consulting, Communication and Soft Skills"
NISS Affiliate Virtual Career Fairs
NISS Sponsored webinars where experienced statisticians from industry, government and academia talk about and provide advice for individuals interested in pursuing a career as a statistician.
"Successful Career Fair Series Finishes with Insights into BioPharm Industries" (June 3, 2020)
"3rd NISS Government Career Fair" (May 22, 2020)
"Academic Career Paths Explored During NISS Career Fair" (April 23, 2020)
"Career Paths Highlighted in Three Health Related Government Agencies" (March 11, 2020)
"Advice and Insights Offered During Third NISS Industry Career Fair!" (February 19, 2020)
"NISS Government Career Fair Outlines Opportunities for Statisticians!" (January 8, 2020)
"Opportunities in Banking & Marketing Sectors Highlighted in Virtual Career Fair" (December 6, 2019)
"NISS Virtual Career Fair for NISS Affiliates" (September 26, 2019)
Recent/Upcoming NISS Sponsored Webinar Series
A weekly online seminar on random topics on mathematical foundations of machine learning, statistics and optimization
September 1, 2020: "On Nearly Assumption-Free Tests of Nominal Confidence Interval Coverage for Causal Parameters Estimated by Machine Learning", James Robins (Harvard University)
September 29, 2020: TBA, Amir Ali Ahmadi (Princeton University)
October 6, 2020: TBA, Susan Murphy (Harvard University)
October 13, 2020: TBA, e: TBA, Maryam Fazel (University of Washington, Seattle)
Deep Learning Methods and Theory (Purdue website)
Timely and important research topics for the statistical audience via both introductory overview and in-depth research talks from leading researchers.
August 28, Friday: "On Demystifying Adversarial Learning", Lawrence Carin (Duke University).
September 4, Friday: "Distributed Machine Learning", Heng Huang, (University of Pittsburgh).
September 11, Friday: "A Representational Model of Grid Cells Based on Matrix Lie Algebras", Ying Nian Wu (UCLA).
September 18, Friday: "Integrating Domain-Knowledge into Deep Learning", Ruslan Salakhutdinov (Carnegie Mellon University).