
Sign up to save your podcasts
Or
In this interview, Alexa shares her journey, thoughts on AI, application of various ML models in Architecture alongwith advice to students and young professionals. She is currently Computer Vision and Robotics PhD student at University of Michigan. Alexa attended the University of Chicago, where she studied computational neuroscience and physics. Her current research focuses on robust computer vision for autonomous vehicles, specifically on realistic noise modeling in images. Journey 0:30 Can you tell us about your current projects and research interest? 1:19 Can you share your journey to pursue PhD in this topic? What are some aspects which inspired you to pursue this path? 4:01 Cross-disciplinary application in your current work 5:24 What are some challenges you faced when you started your PhD? Professional Work 6:37 Can you walk us through one of your project? What was your approach, challenges faced and the final output? 11:50 How did you generate those data sets? Was there any image scraping technique? 13:30 What is the strategy you adopted to ensure that the data is not biased? 15:47 Based on your experience of working with architects, what do you think are some roadblocks in AEC industry? 19:04 How would you categorize good AI versus bad AI design? 21:38 Can you share some examples how AI can be applied in architecture? 23:58 What is the question you are addressing through AI? 24:29 What are some upcoming projects you're working on? 27:16 What are some emerging trends in the field of AI which an architect should keep an eye on? Advice to students and young professionals 29:09 What will be your advice to students and professionals who are interested to apply a AI in their design projects? 32:04 What are some books or artists or courses you would recommend to people who are just starting out? 34:59 What was the realization moment in which you thought AI can be game changer? 37:16 How can our listeners follow you and your work? Resources Stanford course : http://cs231n.stanford.edu/Text : Deep learning by Goodfellow, Courville and Bengio Github : https://github.com/alexacarlson/DeepDesign_DigitalFutures #aiinarchitecture
In this interview, Alexa shares her journey, thoughts on AI, application of various ML models in Architecture alongwith advice to students and young professionals. She is currently Computer Vision and Robotics PhD student at University of Michigan. Alexa attended the University of Chicago, where she studied computational neuroscience and physics. Her current research focuses on robust computer vision for autonomous vehicles, specifically on realistic noise modeling in images. Journey 0:30 Can you tell us about your current projects and research interest? 1:19 Can you share your journey to pursue PhD in this topic? What are some aspects which inspired you to pursue this path? 4:01 Cross-disciplinary application in your current work 5:24 What are some challenges you faced when you started your PhD? Professional Work 6:37 Can you walk us through one of your project? What was your approach, challenges faced and the final output? 11:50 How did you generate those data sets? Was there any image scraping technique? 13:30 What is the strategy you adopted to ensure that the data is not biased? 15:47 Based on your experience of working with architects, what do you think are some roadblocks in AEC industry? 19:04 How would you categorize good AI versus bad AI design? 21:38 Can you share some examples how AI can be applied in architecture? 23:58 What is the question you are addressing through AI? 24:29 What are some upcoming projects you're working on? 27:16 What are some emerging trends in the field of AI which an architect should keep an eye on? Advice to students and young professionals 29:09 What will be your advice to students and professionals who are interested to apply a AI in their design projects? 32:04 What are some books or artists or courses you would recommend to people who are just starting out? 34:59 What was the realization moment in which you thought AI can be game changer? 37:16 How can our listeners follow you and your work? Resources Stanford course : http://cs231n.stanford.edu/Text : Deep learning by Goodfellow, Courville and Bengio Github : https://github.com/alexacarlson/DeepDesign_DigitalFutures #aiinarchitecture
31 Listeners
4 Listeners