Alessandro (Alex) Filazzola

Come work with me!

Excited to hear how it comes out! If you try it with ecoclassify, would love to hear more.
Enjoy your weekend!

The package is open source though! We're always looking for improvements if you find anything!

The package created a framework to build your own model by providing the best data. We've found some pretty good success classifying wetlands, green infrastructure, alpine snow, invasive trees, etc. Needs someone familiar with the target to train

Array of wildlife species found in Sask. cities. Climate change could bring more - The Weather Network Urban wildlife project caught photos, audio recordings of 143 bird species and 15 mammal species

No specific data for Sask. cities, but @afilazzola.bsky.social's study suggested even under low-emission scenario, #ClimateChange could drive more than 150 more species into Winnipeg, while only about 30 species would leave it. @westernu.ca @usask.ca www.theweathernetwork.com/en/news/natu...

🧪 AI is coming to SyncroSim!

We're working on ecoClassify — a new #SyncroSim package led by our team members, Hannah Adams and @afilazzola.bsky.social, that brings image classification into your workflows 🌎

Proud of all this work! And glad to have started working with this project back in 2019 as a postdoc

Thanks for making this Stephanie!

I created a Winter #Limnology starter pack - please let me know if you'd like to be added (or removed)!
go.bsky.app/UnKfRfA

Thank you!

Thanks for organizing these!

Can I be added please?

Happy to have been back at UTSC to present our classifier work for this project!

We recently welcomed Hannah Adams as our newest quantitative ecologist at ApexRMS!

If the Toronto Eglinton LRT takes any longer it's going to get decommissioned before it even gets used.
Just like it's sidewalks

toronto.citynews.ca/2024/02/27/e...

#transit

Spain potentially banning short haul flights when trains are available is a fantastic way to combat emissions.

How I wish Canada had a similar train network

#urbanism

fortune-com.cdn.ampproject.org/v/s/fortune....

Distilling information into the most important elements can be powerful for data storytelling.

It is certainly a delicate balancing act between providing data reduction and data distillation. The former can at times be a lot harder than the latter.

Right now, I’m on a journey to implement analytics on our web application/ Just because I can implement hundreds of analytics doesn’t mean I should, and delivering a massive report of niche analytics is generally not helpful for decision-making.

We live in a world where there are unbelieve amounts of data available. Being a data scientist involves digesting that information into meaningful insights. Sometimes though, the most powerful thing we can do when trying to understand data is to ignore some of it.

Death by data – can there be too much of a good thing?

I’ve heard it said before for famous musicians, it is not about the notes that they do play, but the notes that they don’t. The same is true about data.

😂

New authentication feature - hardcore mode.
If you enter your password incorrectly, your account gets deleted

Also true!

This mind shift can be jarring. It's not about corporate glorification or academia bashing. Both worlds offer unique rewards.

My advice? Be flexible, adapt, & hold onto your values. This isn't about efficiency wars. Academia can be great, although more compensation would be nice

Corporate world? Time is a very much money. Automating tasks & outsourcing are strategic investments. "Can I learn this?" becomes "Is my time worth more elsewhere?"

In academia, grants reign but your time? Free-range! Need a graphic? Learn design & DIY with free software. Efficiency? Not a priority.

Time Warp: Academia vs. Corporate Hustle

My biggest shift switching from #academia to a company? The value of time. Same hustle, but undefined hours to billable ones changed how I think about time.

Taking the leap can certainly be challenging. I talked to some people who went through this process who helped me bust these myths and many others. If you’re thinking about making the change, reach out to others to see if your myths are false too!
#Academia #CareerTransition #datascience

🦄 Myth 3: “You’re working for the ‘man’”.
❌ False: While in a company, it's not black and white. Universities also have constraints like grant objectives. Corporate jobs offer flexibility in growth, research, and creativity.

🦄 Myth 2: “You’ll be disconnected from the research world.”
❌ False: You can still do research outside of academia. You can write papers or teach. For me, I joined Western University as an Adjunct faculty to enjoy academia without a lot of the stress.

🦄 Myth 1: “You will stop learning.”
❌ False: You'll learn differently. I shifted from expertise in a few areas to broad knowledge. Your mileage may vary. In any job, you can keep learning and pushing yourself.