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Kandungan disediakan oleh Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
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Jessica Bohórquez | Using AI for leak detection in water pipelines (Spanish)

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Manage episode 341268714 series 2706384
Kandungan disediakan oleh Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

A Colombian engineer, Jessica is fascinated by the processes and complexity of water supply systems in urban areas.In her post doc research in Australia, she brings together her expertise on the water hammer and transient flow waves to create an AI model that is able to identify where pipeline defects are faster and more accurately than existing techniques.

She explains that in data science, the most important stage is understanding the problem. You need to bring in basic knowledge of the problem and expertise from other disciplines that are involved in a problem and combine that with artificial intelligence. AI is an important tool but just part of the solution. It’s critical to maintain all the legacy of knowledge and understanding of a problem. AI can make it simpler to apply, but you can’t leave behind the physics or knowledge of the hydraulic part of water movement.

Working in industry, she has found that it’s important to first understand how the system works. In these large companies in charge of delivering water, each person has different objectives, so you need to understand how the company works, who is in charge, what are their objectives, and how they measure their success. If your research project aims at those things, they will be more receptive and a better chance of success.

Jessica has learned in both research and industry consulting that nothing works the first time and it’s important to not to let those little defeats build up in your head. You need to trust yourself. There are many moments in life when you are criticizing yourself, and you realize that the biggest enemy you have is yourself. She just breaks down the problem into small parts and then solves each part one by one. She is passionate about teaching and inspiring young engineers about the importance of water and the future of this invaluable resource.

RELATED LINKS
Connect with Jessica on LinkedIN
Find out more about the University of Adelaide
Connect with Cindy Orozco Bohorquez on LinkedIN

  continue reading

53 episod

Artwork
iconKongsi
 
Manage episode 341268714 series 2706384
Kandungan disediakan oleh Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

A Colombian engineer, Jessica is fascinated by the processes and complexity of water supply systems in urban areas.In her post doc research in Australia, she brings together her expertise on the water hammer and transient flow waves to create an AI model that is able to identify where pipeline defects are faster and more accurately than existing techniques.

She explains that in data science, the most important stage is understanding the problem. You need to bring in basic knowledge of the problem and expertise from other disciplines that are involved in a problem and combine that with artificial intelligence. AI is an important tool but just part of the solution. It’s critical to maintain all the legacy of knowledge and understanding of a problem. AI can make it simpler to apply, but you can’t leave behind the physics or knowledge of the hydraulic part of water movement.

Working in industry, she has found that it’s important to first understand how the system works. In these large companies in charge of delivering water, each person has different objectives, so you need to understand how the company works, who is in charge, what are their objectives, and how they measure their success. If your research project aims at those things, they will be more receptive and a better chance of success.

Jessica has learned in both research and industry consulting that nothing works the first time and it’s important to not to let those little defeats build up in your head. You need to trust yourself. There are many moments in life when you are criticizing yourself, and you realize that the biggest enemy you have is yourself. She just breaks down the problem into small parts and then solves each part one by one. She is passionate about teaching and inspiring young engineers about the importance of water and the future of this invaluable resource.

RELATED LINKS
Connect with Jessica on LinkedIN
Find out more about the University of Adelaide
Connect with Cindy Orozco Bohorquez on LinkedIN

  continue reading

53 episod

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