Michael R. Schwob

@UT_Stats PhD Student and @NSF Graduate Research Fellow developing models for applications in #ecology, #epidemiology and #genetics | musician | sci-fi fan

[Michael R. Schwob @mrschwob]

My first textbook is officially available for pre-order today. Grab a copy if you're interested in developing a (statistical) research-oriented mindset. The book is designed as a stepping stone from statistical coursework to novel statistical research.
https://t.co/SO6rIb0d03

[Stat.ML Papers @StatMLPapers]

I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers https://t.co/Yu1zuBaXUp

[Michael R. Schwob @mrschwob]

Relevant tags: #landscape-genetics #landscapegenomics
#landscapeecology #ancientDNA
#spatiotemporal
#dyadic
#Bayesian
#advectiondiffusion
#BronzeAgeEurope
#ecologicalstatistics
(5/5)

[Michael R. Schwob @mrschwob]

In my latest paper (with M. Hooten and @vagheesh), we developed a dyadic model that accounts for the flow of biological processes in space-time. We applied our method to ancient human DNA data to study human movement in Bronze Age Europe. (1/5)

https://t.co/RVuEEmgpUo

[Michael R. Schwob @mrschwob]

We construct a fully connected network comprising spatio-temporal data for the dyadic model and use normalized composite likelihoods to account for the dependence structure in space and time. (4/5)

[Vagheesh Narasimhan @vagheesh]

New paper led by star PhD student @mrschwob (who is currently on the statistics job market) building a bayesian hierarchical model to understand gene flow across space and time in ancient DNA datasets.

https://t.co/K8Hreo0cuB

[Michael R. Schwob @mrschwob]

🎉 Published🎉

"Dynamic Population Models with Temporal Preferential Sampling to Infer Phenology" w/ Mevin Hooten and @tmcdevittgalles

- Mechanistic Bayesian models for phenometrics
- Simple preferential sampling component
- NEON mosquito case study

https://t.co/HePUBYydEt

[Michael R. Schwob @mrschwob]

🎉 Publication Alert 🎉

"Multistage hierarchical capture-recapture models"
w/ Mevin Hooten, @drdevijo , and Jacob Ivan
We fit CR models in stages and leverage parallel computing resources for large data sets.

https://t.co/YWBnib3HfQ

[Michael R. Schwob @mrschwob]

🎊arXiv Alert🎊
My latest paper explores population dynamics for species that are preferentially sampled and infers phenology in an embedded mechanistic process. Co-authors: Mevin Hooten and @tmcdevittgalles

https://t.co/m5wkwIHGU2

[Michael R. Schwob @mrschwob]

Just gave my first JSM talk - and I promise there was more than one person in attendance #JSM2022

[Anders Bergström @andersbrgstrm]

Our wolf paper is out! https://t.co/y3KQnxRlYz Analysing 72 ancient 🐺 genomes from the last 100,000 years, we: #1 chart wolf natural history through the Ice Age, #2 directly detect natural selection, #3 reveal that dogs have dual ancestry. A 🧵 (11), illustrations by @jessrpeto

[Michael R. Schwob @mrschwob]

@leoNitrogen Glad to see that the Bayesian conversion has begun! Thank you for teaching me about agronomy. Let's get some more Bayesian work in there 😎🌾

[Michael R. Schwob @mrschwob]

Over the last two weeks, I had the opportunity to help with the NSF Bayesian Short Course, hosted at CSU. It has been a pleasure meeting such wonderful and curious ecologists, agronomists, and environmental scientists. Based on the smiles below, I think it went well!

[Michael R. Schwob @mrschwob]

@GenesLuisa It was a pleasure! Thank you for the ecology textbook recommendations 😁

[Arjun Gopalaswamy @ArjunGswamy]

How “science” can facilitate the politicization of charismatic megafauna counts | Proceedings of the National Academy of Sciences https://t.co/fX6RH5MorL @PNASNews @Femke_Broekhuis @alexbraczkowski @TurgwePete

[Michael R. Schwob @mrschwob]

Several years ago, my dad decided to quit his job and return to college. Today, he received his PhD in Mechanical Engineering at 54 years old! Very proud of him 🎓🎉🎉

[Michael R. Schwob @mrschwob]

🎉Live on arXiv🎉
"Bayesian Capture-Recapture Models that Facilitate Recursive Computing "
w/ Mevin Hooten, @drdevijo , and Jacob Ivan
We fit CR models in stages and leverage parallel computing resources for large data sets.
https://t.co/0mTxPEMeT8

[Michael R. Schwob @mrschwob]

@NISS_DataSci event: "How to Write a Successful Grant Proposal" on Nov. 4, featuring seminars from experts in NSF, NIH, and academia. Who doesn't want more money for more research? #NISS
https://t.co/JdRZTZzAEt