data & science with glen wright colopy by Glen Wright Colopy
Keith O'Rourke | The Logic of Statistics
Jack Fitzsimons | Evil Models: Hiding Malware in Neural Networks
Scott Cunningham | Causal Inference (The Mixtape) Scott Cunningham (Baylor University) discusses the ideas of his book "Causal Inference: The Mixtape". Topics include trusting inference in the absence of counterfactuals and the challenges of apply scientific methods to social phenomena.
Eric Daza | Important Ideas in Causal Inference
Wenting and Weidong discuss how the statistical challenges in the biopharm industry have proliferated with the unique demands of biotech and related life science industries.
Ruda Zhang | Gaussian Process Subspace Regression
Ruda Zhang | Math-Science Duality
Simon Mak | Integrating Science into Stats Models #statistics #science #ai
Martin Goodson | Practical Data Science & The UK's AI Roadmap
Dr. Jack Fitzsimons (Oblivious AI) gives a high-level introduction to the technologies that can either exploit or protect your data privacy. If you'd like to survey the landscape of data privacy-preserving technologies (from someone who's building the tech) this is a good place to start!
The piranha problem (too many large, independent effect sizes influence the same outcome) has received some attention on Andrew Gelman’s blog. But now it’s a paper! Chris Tosh (Memorial Sloan Kettering) talks about multiple views of the piranha problem and detecting the implausible scientific claims that are published. The butterfly effect makes an appearance.
Chris Holmes is Professor of Biostatistics at the University of Oxford and Programme Director for Health and Medical Sciences at The Alan Turing Institute. Chris’ research interests include Bayesian nonparametrics (which is the right kind of nonparametrics), statistical machine learning, genomics, and genetic epidemiology.
Philosophy of Data Science Series Keynote with Deborah Mayo Episode 1: Revolutions, Reforms, and Severe Testing in Statistical Thinking
Charlotte Deane | Bioinformatics, Deepmind's AlphaFold 2, and Llamas #datascience #ai
Charlotte Deane | Proteomics, AlphaFold 2, and Llamas #datascience #ai
The philosophical community continuously aims to reconcile differing views on first person data and the consciousness of the mind. Is it possible to live without consciousness? Can one conceive thoughts without matching images to them? In this episode, Eric Schwitzgebel of the University of California tries to dissect such topics and questions to help us better understand the philosophical world.
Starting a Statistics Consultancy | Janet Wittes
Jingyi Jessica Li | Advancing Statistical Genomics
Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education #datascience #statistics #education
Jingyi Jessica Li | Statistical Hypothesis Testing versus Machine Learning Binary Classification
Gualtiero Piccinini | What Are First-Person Data?
David Dunson | Advancing Statistical Science | Philosophy of Data Science Series
Note: This conversation was recorded June 25, 2021.
Interested in Data Science? Learn Data Science and Statistics from experts as they cover key topics in the field. The Data & Science podcast focusses on teaching data scientists how to think critically in order to solve data analysis problems across various scientific domains.
Interesting in Data Science? Learn Data Science and Statistics from experts as they cover key topics in the field. The Data & Science podcast focusses on teaching data scientists how to think critically in order to solve data analysis problems across various scientific domains.
#datascience #statistics
#datascience #jobs #career #jobsearch #statistics
Mike Evans | Statistical Reasoning & Evidence | Philosophy of Data Science Series
Deborah Mayo | Statistics & Severe Testing vs Pseudoscience
Description: In the world of biomechanics, engineers continuously aim to innovate and create new models for better understanding of their research. In this episode, Kristin Morgan (University of Connecticut) returns to the show as she explains how they use gait as a form of diagnostic tool in maximizing human performance. Having experiences on sports herself, Morgan presents how they use gait to measure recovery from physical impairment, specifically for ACL-related injuries. Aside from this, however, she also explains how they use the same tool to measure recovery from cognitive impairment. An insightful episode for all!
Michael McRoberts | Football Analytics and Data-Driven Decisions
Andrew Gelman & Megan Higgs | Statistics' Role in Science and Pseudoscience
Irina Gaynanova (Texas A&M) describes why she thinks that replicability is a prerequisite for reproducibility in science and how scientists can (personally) start improving the replicability of research. We also discuss how the concepts of replicability/reproducibility can differ according to the domain-specific context and the methods used.
#datascience #science #pseudoscience #criticalthinking #reasoning
We have a new series that centers on the discussion of science vs. pseudoscience. Guests of different backgrounds share their insights on what really constitutes science and the highly-contested pseudoscience. In today’s episode, we talk to Professor Dien Ho, PhD, a Professor of Philosophy and Healthcare Ethics, of the Massachusetts College of Pharmacy & Health Science University. Discover how philosophical ideas and theories are applied in hopes of understanding what really counts as science and what pseudoscience really is.
We're launching a series on "Science vs Pseudoscience" tomorrow! Also we've rebranded to better reflect the focus of the podcast. The focus of the podcast isn't changing - it's still data science, critical scientistic reasoning, and figuring out how to figure stuff out!
We've received a lot of questions from early career data scientists interested in starting a career in environmental science and climate science. Elizabeth Mannshardt (EPA), Grant Weller (Optum Labs), and Megan Higgs (Critical Inference LLC) sit down to give you your answers!
#datascience #career #job
Philosophy of Data Science Series
Philosophy of Data Science Series Session 3: Data Science Highlight Reel Episode 1: Adler Perotte on NeuralNets, GANs, Causality, and Medicine
Career Q&A: 10 Questions From a Beginner Data Scientist
Philosophy of Data Science | Keynote 1 Presentation | Philosophy of Science & Statistics
Philosophy of Data Science Series
Philosophy of Data Science Series Session 2: Essential Reasoning Skills for Data Science Episode 4: Intro to Abductive Reasoning for Data Scientists
Philosophy of Data Science Series Session 2: Essential Reasoning Skills for Data Science Episode 3: Intro to Inductive Reasoning for Data Scientists
Philosophy of Data Science Series Session 2: Essential Reasoning Skills for Data Science Episode 2: Intro to Deductive Reasoning for Data Scientists
Philosophy of Data Science Series
Philosophy of Data Science Series
Philosophy of Data Science Series Session 1: Scientific Reasoning for Practical Data Science Episode 2: Scientific Reasoning for Practical Data Science
Philosophy of Data Science Series
The Philosophy of Data Science Series
Lisa LaVange (Gillings School of Global Public Health at the University of North Carolina at Chapel Hill) was the 2018 American Statistical Association (ASA) president and the director of the Office of Biostatistics in the Center for Drug Evaluation and Research (CDER) at the FDA.
Amy Shi (SAS), Emily Griffith (North Carolina State University), and Elizabeth Mannshardt (EPA) discuss the many activities of the North Carolina Chapter of the American Statistical Association, including a lot of online activities that can be enjoyed even if you aren't in NC. The recording was made on the cusp of COVID...so updated information is posted below. NC ASA Activities NC ASA YouTube Channel: https://www.youtube.com/channel/UCPMPV3vCOY2dZka5ELPBWpA NC ASA Website: https://community.amstat.org/northcarolina/home
Molham Aref and Nathan Daly describe their experience using Julia to build a next-generation knowledge graph database that combines reasoning and learning to solve problems that have historically been intractable. They explain how Julia's unique features enabled them to build a high-performance database with less time and effort. Both Nathan and Molham with be speaking at JuliaCon 2020 at the end of July. It's free and online, so there's no reason not to attend. You can register for JuliaCon 2020 here: https://juliacon.org/2020/
Working with brain imaging data, Xinyi has a lot of cool figures to show off in her technical presentation. She walks us through the image-on-scalar regression model and how it is used to infer a personalized “baseline” brain image along with the effects of different cognitive diagnoses.
Xinyi continues the conversation on precision medicine research at SAMSI. Xinyi describes the challenges of combining genomic data with imaging data for modelling Alzheimer’s with the goal to supplement subjective diagnosis criteria with the more objective biomarkers.
John is back to show the how machine learning can vastly speed up the selection of mathematical models. His presentation provides great visual intuition on how machine learning methods can help select mathematical models, even as measurement noise increases. It’s a huge improvement over selecting models by hand!
John discusses his work in the precision medicine program at the Statistical and Applied Mathematical Sciences Institute (SAMSI) to model wound healing. He describes the physiological mechanisms of wound healing and how to select a applications that are appropriate for mathematical modelling.
Rita Hendricusdottir (Department of Engineering Science, University of Oxford) show cases a new tool to help innovators quickly assess the regulatory buden of their medical devices. From answering the simple question of “Is my invention a medical device?” to the complex considerations for “which classification is my device?” the Oxford Global Guidance tool is designed to facilitate this initial evaluation.
Mike McArdle, co-founder and Chief Product Officer at Lucid Dream VR, is back to walk us through applications of VR that helps clinicians train for rare events and better understand the patient’s experience.
Mike McArdle, co-founder and Chief Product Officer at Lucid Dream VR, breaks down the key technological factors that have led to the rapid increase in VR and AR solutions for the life sciences. He then walks us through two products helping companies and hospitals to accelerate training and talent development on their staff.
Hear about new episodes as they come out by joining our mail list: https://www.podofasclepius.com/mail-list
A mini-epsidoe with (fellow data science podcaster) Stephanie Hicks. Stephanie highlights the keynote speakers at SDSS 2020 along with the conference themes.
It’s not everyday that medical researchers give the world access to 13+ years of dense, high-quality critical care data. Intensivist Paul Elbers describes the data set along with the clinical priorities in collecting the data. Paul covers a range of topics including protecting the patients’ interests and anonymity, a clinician’s priorities when selecting clinical performance metrics, and the stages of validating predictive algorithms up to the stage of an RTC. The work done to create AmsterdamUMCdb is an incredible feat and a huge boon to the medical science profession.
Dave Hunter highlight a variety of cool life science collaborations he has worked on, including the network models used to describe AIDS transmissions and mixture modelling to describe pediatric cognitive tests. We then talk about the upcoming SDSS 2020 conference, and its newest additions to benefit early career researchers.
There are many places in which ML/AI methods can be of benefit to pharmaceutical research (several have already been covered on the show). David and Demissie explain where AI can fit in to in vivo studies, which carries it’s own benefits, but also with heightened risk to to human test subjects. They go on to cover several other areas of interest including AI for observation studies and real world evidence. It’s a “big tent” conversation as we lead up to the Pfizer/ASA/Columbia University Symposium on Risks and Opportunities of AI in Clinical Drug Development.
Dana al Sulaimen’s (MIT) work runs the gamut of biomedical engineering areas. She gives a great presentation on the clinical motivation for her work, engineering sensing platforms, and data analysis. Definitely watch the video for this one for some excellent visual material.
The episode of milk and honey.
Rob Scott, Chief Medical Officer at AbbVie, discusses the importance of a clinician’s perspective for keeping clinical trial development focussed on the patients. Rob talks about how the role of a Chief Medical Officer changes between a large pharma company and small biotechs. He then covers the key areas in which new developments in healthcare technology can help us better understand a patient’s response to therapies and interventions.
Gajanan Bhat and Xinping Cui discuss the major themes of data science in clinical drug and device development.
Eric Stephens, Chief Analytics Officer at Nashville General Hospital, talks about building analytics capacities in the hospital setting and how hospitals select their priorities for new analytics projects. Then he discusses the cool events coming up at CSP 2020 and how applied data scientists have more options than ever for career advancement.
Neurosurgeon and entrepreneur Nick de Pennington talks about the importance of automating clinical tasks to help doctors focus on the most challenging cases.
Niven Narain, CEO of Berg Health, discusses creating value through data platforms and AI in the pharmaceutical industry.
Originally developed in the Stanford biodesign ecosystem, the “needs-led” approach to healthtech innovation has rapidly become a key philosophy for those wanting to develop a viable healthcare solution.
We’ve got a great lineup of speakers on deck.
This is Part 2 of a two-part episode in which Allison treats the audience to a technical deep-dive into optimizing bespoke clinical models.
S00 Ep04 Pt01 with Allison Meisner: Predictive Models in Kidney Injury
Part 3 of a three part episode with Martin Ho and Greg Maislin, talking about the ASA Section on Medical Devices and Diagnostics (MDD).
Part 2 of a three part episode with Martin Ho and Greg Maislin, talking about the ASA Section on Medical Devices and Diagnostics (MDD).
Part 1 of a three part episode with Martin Ho and Greg Maislin, talking about the ASA Section on Medical Devices and Diagnostics (MDD).
Emma Hughes discusses how to find and cultivate technical entrepreneurial talent. She then talks about the critical challenge of making technical solutions sufficiently robust for clinical implementation.
This episode is Part 2 of a two part episode with yours truly, discussing personalized probabilistic patient monitoring.
Part 1 of a two part episode with yours truly, discussing personalized probabilistic patient monitoring.
Glen introduces the podcast, himself, and what’s going on!
