PODCAST · science
Data & Science with Glen Wright Colopy
by Glen Wright Colopy
The Pod of Asclepius is a healthcare technology podcast for the technical crowd. No fluff, no sales pitches, just important health tech ideas (described well!) to help everyone keep learning and becoming more of an expert in the field.Our guests are top researchers (from academia and industry), entrepreneurs, and regulatory experts. They will talk about cool technology, from data science to engineering, but also share insights on practical concerns of bridging the gap between technical innovation and a clinical solution.
Episodes
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Keith O’Rourke | The Logic of Statistics
Keith O'Rourke | The Logic of Statistics Dr. Keith O'Rourke talks about the logical reasoning behind statistical modeling. Topics include mathematical vs scientific reasoning, whether science has become too stats focused, and vice versa. Watch it on... Youtube: https://youtu.be/FqE4ROHBKpY…
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Jack Fitzsimons | Evil Models: Hiding Malware in Neural Networks
Jack Fitzsimons | Evil Models: Hiding Malware in Neural Networks Did you know that it's possible to hide malware in neural networks? Actually, you can hide malware in many statistical models. This is the subject of two recently-published papers (aptly titled "EvilModel" & "EvilModel 2.0"). Dr.…
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Scott Cunningham | Causal Inference (The Mixtape)
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. Watch it...
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Eric Daza | Important Ideas in Causal Inference
Eric Daza | Important Ideas in Causal Inference YouTube: https://youtu.be/K5nsSMJVIT0 Andrew Gelman and Aki Vehtari wrote a paper titled, "What are the most important statistical ideas of the past 50 years?". The first idea in the list is "counterfactual causal inference". Eric Daza (Evidation...
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Wenting Cheng & Weidong Zhang | Advances in Biotech/Biopharma
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.
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Ruda Zhang | Gaussian Process Subspace Regression
Ruda Zhang | Gaussian Process Subspace Regression Ruda Zhang (Duke University) walks us through "Gaussian Process Subspace Regression for Model Reduction" by Zhang, Mak, and Dunson. To keep the topic interesting for both the early career & advanced audience we recap key points at a high level so...
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Ruda Zhang | Math-Science Duality
Ruda Zhang | Math-Science Duality Watch it on... Youtube: https://youtu.be/GoDwen-RGZg Podbean: https://dataandsciencepodcast.podbean.com/e/ruda-zhang-math-science-duality/ Statistics is thought to reside at the interface of science and mathematics. Ruda Zhang (Duke University) discusses the...
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Simon Mak | Integrating Science into Stats Models
Simon Mak | Integrating Science into Stats Models #statistics #science #ai It’s a common dictum that statisticians need to incorporate domain knowledge into their modeling and the interpretation of their results. But how deeply can scientific principles be embedded into statistical models? Prof....
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Martin Goodson | Practical Data Science & The UK’s AI Roadmap
Martin Goodson | Practical Data Science & The UK's AI Roadmap #ai #datascience #startups Martin Goodson (Evolution AI) describes the key aspects of the UK's AI Roadmap & responses to the document by members of the Royal Statistical Society. In particular, Martin describes the disconnect between…
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Jack Fitzsimons | Data Security, Privacy, & Artificial Intelligence
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!...
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Chris Tosh | The piranha problem in statistics
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...
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Chris Holmes | AI, Digital Health, & The Alan Turing Institute
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…
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Philosophy of Data Science | Deborah Mayo | Revolutions, Reforms, and Severe Testing in Statistical Thinking
Philosophy of Data Science Series Keynote with Deborah Mayo Episode 1: Revolutions, Reforms, and Severe Testing in Statistical Thinking In the first keynote of the Philosophy of Data Science Series we have a 2-part interview with Deborah Mayo (Virginia Tech). In the first part of our keynote with...
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Charlotte Deane | Bioinformatics, Deepmind’s AlphaFold 2, and Llamas
Charlotte Deane | Bioinformatics, Deepmind's AlphaFold 2, and Llamas #datascience #ai Charlotte Deane (Oxford University) talks about statistical approaches to bioinformatics, the evolution of Google Deepmind's AlphaFold 2 & its place in protein informatics deep learning landscape. She also...
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Eric Schwitzgebel | Consciousness, Zombies, & First Person Data | Philosophy of Data Science
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...
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Starting a Statistics Consultancy | Janet Wittes
Starting a Statistics Consultancy | Janet Wittes The following interview was a keynote fireside chat with Janet Wittes (Statistics Collaborative, Inc.) titled "Statisticians as Entrepreneurs". It was recorded for the BBSW 2021 Conference (Nov 3 - 5 in Foster City, CA). References: BBSW 2021...
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Philosophy of Data Science | Jingyi Jessica Li | Advancing Statistical Genomics
Jingyi Jessica Li | Advancing Statistical Genomics Watch it on…. YouTube Podbean Jingyi Jessica Li (UCLA) describes common statistical pitfalls in genomic data analysis & the statistical reasoning required to correct these mistakes. Common themes throughout include: Hypothesis-driven science &...
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Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education
Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education #datascience #statistics #education Mine Çetinkaya-Rundel (Duke University) describes the current and future states of statistics and data science education. Then she discusses the process of building open access learning...
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Jingyi Jessica Li | Statistical Hypothesis Testing vs Machine Learning Binary Classification
Jingyi Jessica Li | Statistical Hypothesis Testing versus Machine Learning Binary Classification Jingyi Jessica Li (UCLA) discusses her paper "Statistical Hypothesis Testing versus Machine Learning Binary Classification". Jingyi noticed several high-impact cancer research papers using multiple...
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Gualtiero Piccinini | What Are First-Person Data? | Philosophy of Data Science
Gualtiero Piccinini | What Are First-Person Data? First-person methods (and its associated data) have been scientifically and philosophically contentious. Are they pseudoscientific? Or simply pushing the bounds of scientific methodology? Obviously, I have no idea… so Prof. Gualtiero Piccinini...
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David Dunson | Advancing Statistical Science | Philosophy of Data Science
David Dunson | Advancing Statistical Science | Philosophy of Data Science Series A fundamental question in the philosophy of science is "what does it mean to make scientific progress?" We will have a series of episodes centered around this question for statistics and data science. In our first...
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Martin Kuldorff | Spatiotemporal Models of Disease Outbreaks
Note: This conversation was recorded June 25, 2021. Martin Kuldorff | Spatiotemporal Models of Outbreaks Martin Kuldorff (Harvard Medical School) talks about the integration of biological & demographic information (and general reality) in the spatiotemporal models used to detect disease…
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Jason Costello | Data Science vs Software, Academia vs Industry
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. Jason Costello |…
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Eric Daza | N-of-1 Science & Causal Inference | Philosophy of Data Science
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. Eric Daza | N-of-1...
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Edward McFowland III | Anomalous Pattern Detection & Model Building
#datascience #statistics Edward McFowland III | Anomalous Pattern Detection & Model Building Edward McFowland III (Harvard Business School) describes the differences between "anomalies" and "anomalous patterns". Edward describes how this informs modeling strategies, in particular, when to use an...
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Data Science Job Search | Advice + Q&A
#datascience #jobs #career #jobsearch #statistics The Statistical Consulting Section of the ASA invited me to give a presentation on the data science job search followed by a Q&A. They were kind enough to let me post it here (with minor edits). My drawing of "cumulative cost" is wrong. It should...
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Mike Evans | Statistical Reasoning & Evidence | Philosophy of Data Science Series
Mike Evans | Statistical Reasoning & Evidence | Philosophy of Data Science Series Mike Evans (University of Toronto) describes his approach to statistical reasoning. Mike outlines how to recognize and address problems that are statistical in nature and why these approaches should be grounded in…
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Deborah Mayo | Statistics & Severe Testing vs Pseudoscience
Deborah Mayo | Statistics & Severe Testing vs Pseudoscience Watch it on… YouTube Podbean In our fourth episode of the “science vs pseudoscience” mini-series, Deborah Mayo (Virginia Tech) specifies several necessary criteria to be scientifically rigorous. She gives several examples of how...
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Kristin Morgan | The Data Science of Sports Injury
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...
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Michael McRoberts | Football Analytics and Data-Driven Decisions
Michael McRoberts | Football Analytics and Data-Driven Decisions Michael McRoberts (Championship Analytics Inc.) uses Monte Carlo simulations to provide strategy analytics to college and NFL football teams. Topics include communicating data-driven recommendations, the need to create…
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Andrew Gelman & Megan Higgs | Statistics’ Role in Science and Pseudoscience
Andrew Gelman & Megan Higgs | Statistics' Role in Science and Pseudoscience #datascience #statistics #science #pseudoscience Our science vs pseudoscience discussion continues with Andrew Gelman (Columbia) and Megan Higgs (Critical Inference LLC). Andrew and Megan describe two critical roles that...
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Irina Gaynanova | Replicability, Reproducibility, Responsibility, and Optimism for the Future of Science
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...
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Science vs Pseudoscience | Neil Manson | Philosophy of Data Science
#datascience #science #pseudoscience #criticalthinking #reasoning We each like to think of ourself as scientific. I'm yet to meet someone who would embrace being called "pseudoscientific". But what makes the difference? In this episode, Neil Manson talks about the fallout from Thomas Kuhn's 1962...
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Science vs Pseudoscience | Dien Ho | Philosophy of Data Science
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...
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New Science vs Pseudoscience Series (+ Renaming the Podcast)
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! Some fun reading on...
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Environmental Data Science | Career Q&A
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! Thinking about a...
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Data Science Career Q&A for Undergrads
#datascience #career #job Data Science Career Q&A for Undergrads with Mallory LaRusso We continue to answer data science career questions. We've heard back from a lot of different groups about the world of data science. In this episode, we're talking about undergraduate DS job prospects. Mallory...
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Philosophy of Data Science | Step-change and Anomaly Detection | Alex Bolton
#datascience #ai #earlycareer Philosophy of Data Science Series Session 3: Data Science Highlight Reel Episode 4: Alex Bolton on Step-change and Anomaly Detection Who makes it into the highlight reel of data science? Alex Bolton for doing the hard work of analyzing data to figure out exactly...
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Irina Gaynanova | Replicating Clinical Metrics & Innovating New Methods
Philosophy of Data Science Series Session 3: Data Science Highlight Reel Episode 2: Irina Gaynanova on Replicating Clinical Metrics & Innovating New Methods Who makes it into the highlight reel of data science? Irina Gaynanova for her work on replicating clinical metrics for deployment. She then...
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Karel Moons | Validating Medical Predictive Models | Philosophy of Data Science
Philosophy of Data Science Series Session 3: Data Science Highlight Reel Episode 2: Karel Moons on Validating Medical Predictive Models Watch it on... YouTube: https://www.youtube.com/watch?v=Y6Qik_5hZog Podbean: Who makes it into the highlight reel of data science? Karel Moons and the classic…
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Philosophy of Data Science | S3 E1 | NeuralNets, GANs, Causality, and Medicine
Philosophy of Data Science Series Session 3: Data Science Highlight Reel Episode 1: Adler Perotte on NeuralNets, GANs, Causality, and Medicine Watch it on... YouTube: https://www.youtube.com/watch?v=DOf2lVHzZS4 Podbean:...
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Career Q&A: 10 Questions From a Beginner Data Scientist
Career Q&A: 10 Questions From a Beginner Data Scientist Watch it on... YouTube: https://youtu.be/ftikMj7MoYM Podbean: https://podofasclepius.podbean.com/e/career-qa-10-questions-from-a-beginner-data-scientist/ This week's episode is likely of interest to early career data scientists or those...
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Philosophy of Data Science | Deborah Mayo | Philosophy of Science & Statistics
Philosophy of Data Science | Keynote 1 Presentation | Philosophy of Science & Statistics Philosophy of Data Science Series Keynote with Deborah Mayo Episode 2: The Philosophy of Science & Statistics In the first keynote of the Philosophy of Data Science Series we have a 2-part interview with...
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Philosophy of Data Science | S01 E04 | Values and Subjectivity in Data Science
Philosophy of Data Science Series Session 1: Scientific Reasoning for Practical Data Science Episode 4: Values and Subjectivity in Data Science The Value-Free Ideal is a central tenant of objective science. But how do values, value judgements, and subjectivity leak into the practice of data…
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Philosophy of Data Science | S02 E04 | Intro to Abductive Reasoning for Data Scientists
Philosophy of Data Science Series Session 2: Essential Reasoning Skills for Data Science Episode 4: Intro to Abductive Reasoning for Data Scientists Watch it on... YouTube: https://youtu.be/SzQn9SPVhRU Podbean:...
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Philosophy of Data Science | S02 E03 | Intro to Inductive 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 Watch it on... YouTube: https://youtu.be/lNOUvOUE_KE Podbean:...
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Philosophy of Data Science | S02 E02 | Intro to Deductive 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 Watch it on... YouTube: https://youtu.be/y93D-55wgX8 Podbean: Deductive reasoning pervades statistics and data science...but how far can it get us…
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Philosophy of Data Science | S02 E01 | Round Table on Essential Reasoning Skills for Data Science
Philosophy of Data Science Series Session 2: Essential Reasoning Skills for Data Science Episode 1: Round Table on Essential Reasoning Skills for Data Science Session 2 "Essential Reasoning Skills for Data Scientists" is kicking off with a roundtable discussion with Elina Vessonen (Finnish...
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Philosophy of Data Science | S01 E03 | Communicating the Science in Data Science
Philosophy of Data Science Series Session 1: Scientific Reasoning for Practical Data Science Episode 3: Communicating the Science in Data Science One of the biggest challenges in data scientists is to communicate why your work matters. Kathy Ensor (ASA 2022 President and Rice University’s Noah...
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Philosophy of Data Science | S01 E02 | Scientific Reasoning for Practical Data Science
Philosophy of Data Science Series Session 1: Scientific Reasoning for Practical Data Science Episode 2: Scientific Reasoning for Practical Data Science Scientific reasoning plays an essential role in data science and statistics, both for developing new methods and applying our methods to…
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ABOUT THIS SHOW
The Pod of Asclepius is a healthcare technology podcast for the technical crowd. No fluff, no sales pitches, just important health tech ideas (described well!) to help everyone keep learning and becoming more of an expert in the field.Our guests are top researchers (from academia and industry), entrepreneurs, and regulatory experts. They will talk about cool technology, from data science to engineering, but also share insights on practical concerns of bridging the gap between technical innovation and a clinical solution.
HOSTED BY
Glen Wright Colopy
CATEGORIES
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How many episodes does Data & Science with Glen Wright Colopy have?
Data & Science with Glen Wright Colopy currently has 89 episodes available on PodParley. New episodes are automatically indexed when they're published to the podcast feed.
What is Data & Science with Glen Wright Colopy about?
The Pod of Asclepius is a healthcare technology podcast for the technical crowd. No fluff, no sales pitches, just important health tech ideas (described well!) to help everyone keep learning and becoming more of an expert in the field.Our guests are top researchers (from academia and industry),...
How often does Data & Science with Glen Wright Colopy release new episodes?
Data & Science with Glen Wright Colopy has 89 episodes. Check the episode list to see recent publication dates and frequency.
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You can listen to Data & Science with Glen Wright Colopy on PodParley by clicking any episode. We provide an embedded audio player for direct listening, and you can also subscribe via your preferred podcast app using the RSS feed.
Who hosts Data & Science with Glen Wright Colopy?
Data & Science with Glen Wright Colopy is created and hosted by Glen Wright Colopy.
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