Mojtaba Barzegari Profile picture
Jan 31 8 tweets 3 min read
(1/7)
One year has passed since I uploaded the first video to start my beloved personal project, #TuxRiders. And now, after one year, the project is where it should be. I love it more than before, and the feedback I receive now and then motivates me even more to keep it going.
(2/7)
I received many emails and comments during the past year on the topics discussed in the videos as well as suggestions to improve and expand the contents. I have always enjoyed replying to these emails to start a conversation, from which I learn new things a lot too.
(3/7)
I am very grateful to the people giving me their valuable feedback. It helps me improve the quality of the videos, make better plans for upcoming content, spread the message on the awesomeness of open-source philosophy, and make TuxRiders more useful for potential viewers.
(4/7)
I aimed to prepare and upload a video per week and kept the pace of doing this for the whole year. It means that there are already 50+ videos belonging to various series including scientific visualization, setup your environment, and applied numerical computing.
(5/7)
Having most of the fundamental concepts and topics already discussed, I will start demonstrating the true power of these open-source tools in scientific research in the upcoming year by elaborating on a set of real-world projects I’ve done recently.
(6/7)
The forthcoming series are planned, but I hope I find enough time to prepare them the way I want since the last year of my PhD has already started, implying that the tremendous amount of work needed to wrap up the PhD is already out there 🙃
(7/7)
And last but definitely not least, I highly appreciate the incredible support and limitless help I got from my beloved ones, close friends, and great colleagues, without which it was/is impossible to go on ❤️
youtube.com/TuxRiders

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More from @MojBarz

Oct 13, 2021
(1/8)
Are you interested in reaction-diffusion systems? Also want to know more about coupling them with moving interface problems? Especially if it’s related to #HighPerformanceComputing and elaborated on it? Then, don't miss our recent publication😉👇
doi.org/10.1177/109434…
(2/8)
Reaction-diffusion systems coupled with moving interface problems (in which the boundary of the domain is part of the solution 🙂) have great importance in various real-world scenarios in chemistry and chemical engineering as well as environmental and life sciences.
(3/8)
As an example of such systems, we developed an #InSilico model of the #biomaterials degradation phenomena, in which the loss of material due to #corrosion (#biodegradation) leads to movement of the material-medium interface.
Read 9 tweets
Jul 14, 2021
(1/8)
I'm glad to say that our latest paper in the Corrosion Science is now available online.🙂

"Computational modeling of degradation process of biodegradable magnesium biomaterials"
doi.org/10.1016/j.cors…
(2/8)
Biodegradable materials find important applications in designing supportive medical implants, but despite the advantages, assessing the uncontrolled degradation and release remain a challenge in practical use-cases.
(3/8)
Combining the insights obtained through several years of experimental research with computational (in silico) modeling approaches enables us to save lots of resources by studying the biodegradation of medical devices virtually prior to conducting any in vitro/vivo tests.💪
Read 9 tweets
Jul 13, 2021
(1/6)
I'm very happy that we (finally) got an acceptance for our submitted paper in the Journal of Open Source Education, JOSE🙂.

"An open source crash course on parameter estimation of computational models using a Bayesian optimization approach"
doi.org/10.21105/jose.…
(2/6)
Parameter estimation is a crucial aspect of model development in science and engineering. In the proposed educational module, we have a look at the #Bayesian optimization processes in general and model calibration (parameter estimation) in particular.
(3/6)
For demonstration purposes, we implement a model parameter estimation process for a fitting problem step by step in Python such that the readers can adapt it to their own models and use-cases.

Codes are available in this repo: github.com/mbarzegary/edu…
Read 7 tweets

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