Does github have a mechanism for flagging suspicious accounts? Reporting doesn't seem like the right idea without any actual wrong-doing.
277 karma · joined March 18, 2019
Does github have a mechanism for flagging suspicious accounts? Reporting doesn't seem like the right idea without any actual wrong-doing.
Remote: Yes
Willing to relocate: No
Technologies: Python (Django, FastAPI), Typescript (NestJs, Angular, Vue), C# (Asp.Net), Terraform (AWS, Azure), Postgres (PostGIS, Timescale), Dart (Flutter)
Resume: https://docs.google.com/document/d/10xFKmRFgv0J0lUv1QB6Fjcge...
Email: See resume
Former geophysicist with a PhD. After 10+ years of full-stack engineering experience, I'm looking for something where I can combine it with my scientific expertise. I have academic/industrial experience with energy systems and EVs, GHG emission calculations, time-series and geospatial data handling and analysis.
Looking for opportunities to make positive impact on the environment and society.
Currently I'm waiting to hear from Whatsapp support and/or the 7 day waiting time to be over to reset my account. It is bizarre that I am not able to recover my account when I still own my phone number (I can still receive SMS on it).
I would consider myself very cautious about clicking suspicious links, of course one can never be 100% sure. This was very disconcerting.
As a reminder for all Whatsapp users, please set up your 2FA PINs and recovery emails.
Remote: Yes
Willing to relocate: Not at this moment
Tech: Python, C, C++, Matlab, R, Django, FastAPI, Docker, Jenkins, GCP, AWS, Tensorflow, Vue, Angular, PostGres (+PostGIS), Arduino+Raspi stuff
github: https://github.com/maratumba/
homepage: https://gulyamani.com/
CV: https://www.dropbox.com/s/2pa1b8zqszd21xl/Yaman%20Ozakin%20-...
Email: dandik & gmail.com
PhD Scientist/Fullstack Developer. 3 years in the industry after 8 years of PhD and PostDoc in Geophysics/Physics. Strong mathematical and analytical background, proficient in ML methods. Self-motivated problem solver and a fast learner. Used to remote work w/ Agile methods.
Developed and maintained/maintaining many projects written mainly in Vue, Angular, Django and hosted on DO, Netlify, AWS, GCP. My strongest skill is to understand the basics and apply them as code, like creating a performant magnetic lasso tool based on Dijkstra's algorithm in TypeScript.
I am especially interested in helping environmental/climate causes but anything that requires strong problem solving skills interests me. Feel free to send an email even just to chat.
Remote: Yes
Willing to relocate: Not at this moment
Tech: Python, C, C++, Matlab, R, Django, FastAPI, Docker, Jenkins, GCP, AWS, Tensorflow, Vue, Angular, PostGres (+PostGIS), Arduino+Raspi stuff
github: https://github.com/maratumba/
homepage: https://gulyamani.com/
CV: https://www.dropbox.com/s/2pa1b8zqszd21xl/Yaman%20Ozakin%20-...
Email: dandik & gmail.com
PhD Scientist/Fullstack Developer. 3 years in the industry after 8 years of PhD and PostDoc in Geophysics/Physics. Strong mathematical and analytical background, proficient in ML methods. Self-motivated problem solver and a fast learner. Used to remote work w/ Agile methods.
Developed and maintained/maintaining many projects written mainly in Vue, Angular, Django and hosted on DO, Netlify, AWS, GCP. My strongest skill is to understand the basics and apply them as code, like creating a performant magnetic lasso tool based on Dijkstra's algorithm in TypeScript.
I am especially interested in helping environmental/climate causes but anything that requires strong problem solving skills interests me. Feel free to send an email even just to chat.
Most of the EM based earthquake prediction is based on really loose reasoning. In summary, it goes like this: "earthquakes can generate EM fields through piezo-electric effect, therefore small movements before big earthquakes should generate small EM fields we can measure". But there is almost never no such thing as "small movements before big earthquakes", which is why reliably predicting them has been impossible so far.
Most likely, this will turn out to be an example of confirmation bias. In the unlikely event that it is not, people will be all over this.
There have been all kinds of tests with animals but so far, all animal behaviour that looks like predicting earthquakes is only their sensitivity to low amplitude-high speed P (pressure) waves, which humans usually don't feel.