About the Series
Introducing the second season of WILDLABS Tech Tutors, our series that focuses on answering the "how do I do that?" questions of conservation tech. Launched with the support of Microsoft AI for Earth, this series will give you the bite-sized, easy-to-understand building blocks you'll need to broaden your conservation technology horizons, enhance your research, or launch a new collaborative project.
Taking place every Thursday, each Tech Tutor will present a 30 minute tutorial guiding you through an aspect of conservation tech, followed by a 30 minute live Q&A session with the audience.
Tech Tutors is made for conservation tech beginners of all knowledge levels (and yes, even experts can still be beginners when it comes to tackling a new aspect of conservation tech or starting a new project!), and because we know that there's always more to learn in the #tech4wildlife world, that's why we're so excited to bring you a brand-new season of WILDLABS Tech Tutors! With presentations that will take you even deeper into those tricky "how do I do that?" questions of conservation tech, we hope you'll discover new perspectives and ideas to bring to your own #tech4wildlife work.
For participants, the outcome will be an increased sense of confidence in their technological skills, the ability to actively build off of the skills discussed in these tutorials, and an opportunity to learn and collaborate with other members of the WILDLABS community. Read about the first season's community highlights here.
Our goal is to customize these tutorials to fit the needs of the community and address your needs, so let us know what you want to see in this season and beyond.
Can't make it? You can find every tutorial after it airs on our Youtube channel.
Meet your Tutor: Elizabeth Bondi, Harvard University
Elizabeth is a PhD candidate in Computer Science at Harvard University. Her research interests include computer vision and deep learning, remote sensing, and multi-agent systems, especially applied to conservation and sustainability. Specifically, she has developed SPOT, GUARDSS, and the BIRDSAI dataset in collaboration with many wonderful people from many fantastic places, including Air Shepherd and Microsoft AI for Earth.
We asked Elizabeth...
What will I learn in this episode?
Techniques for allocating drones (e.g., game theory)
How you can use real-time information from drones (e.g., computer vision, more game theory, etc.)
- Examples of the above!
How can I learn more about this subject?
This is still active research, so a good place to start might be academic papers, or conference/workshop proceedings. I will point out some additional references in the episode.
If I want to take the next step, where should I start?
- AirSim is a great way to try out new ideas before going into the field.
- This is a short beginners Python tutorial I made to illustrate some of the ideas we've discussed.
- Feel free to reach out to me!
What advice do you have for a complete beginner in this subject?
Your first question might be whether this is useful at all. If you are dealing with limited resources, these techniques could be helpful to look into. We will talk about more specifics during the episode, but if all sounds promising for your context at that point, jump in, and bring a friend! Feel free to reach out if you'd like a computer science friend in particular!
Additional resources from the episode
- Hahn, Nathan, et al. "Unmanned aerial vehicles mitigate human–elephant conflict on the borders of Tanzanian Parks: a case study." Oryx 51.3 (2017): 513-516.
- Learn game theory on Coursera
- Elizabeth's website
- Making AI more inclusive: Try AI
Find out what the audience members are working on and look for collaborations! View the participant check in here.
Learn more about our upcoming Tech Tutorials
Visit the series page on WILDLABS to find the full list of WILDLABS Tech Tutors.