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+---
+speaker: Student Speaker 1 -- Somrita Banerjee
+affiliation: Stanford
+website: "https://stanfordasl.github.io//people/somrita-banerjee/"
+date: 2024-05-03T12:30:00-0000
+location: Skilling Auditorium
+location-url: "https://campus-map.stanford.edu/?srch=Skillaud"
+title: "Learning-enabled Adaptation to Evolving Conditions for Robotics"
+abstract: "With advancements in machine learning and artificial intelligence, a new generation of “learning-enabled” robots is emerging, which are better suited to operating autonomously in unstructured, uncertain, and unforgiving environments. To achieve these goals, robots must be able to adapt to evolving conditions that are different from those seen during training or expected during deployment. In this talk I will first talk about adapting to novel instantiations, i.e., different task instances with shared structure, through parameter adaptation. Such adaptation is done passively, by augmenting physics-based models with learned models, with our key contribution being that the interpretability of physical parameters is retained, allowing us to monitor adaptation. Second, I will talk about a framework for active adaptation where the model monitors its own performance and curates a diverse subset of uncertain inputs to be used for periodic fine-tuning of the model, improving performance over the full data lifecycle."
+youtube-code: "TBD"
+---
diff --git a/_talks/student2sp_24.md b/_talks/student2sp_24.md
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+---
+speaker: Student Speaker 2 -- Elliot Weiss
+affiliation: Stanford
+website: "https://ddl.stanford.edu/people/elliot-weiss"
+date: 2024-05-03T12:30:00-0000
+location: Skilling Auditorium
+location-url: "https://campus-map.stanford.edu/?srch=Skillaud"
+title: "Wearing a VR Headset While Driving to Improve Vehicle Safety"
+abstract: "Driver assistance systems hold the promise of improving safety on the road. We are particularly interested in developing new assistance systems that smoothly share control with the driver and testing them in a wide range of driving conditions. Given the central role of the driver in a shared control system, it is critical to elicit natural driving behavior during tests. This talk discusses the development of a flexible driving simulation platform that can be used for safe and immersive shared control testing. Our platform, known as "Vehicle-in-the-Loop", enables experiments on a real vehicle within a simulated traffic scenario viewed by the driver in a virtual reality headset. By implementing this platform around a four-wheel steer-by-wire vehicle, the driver can interact with shared control systems in a variety of test conditions – including low friction and highway speed driving – all on one vehicle platform and at one proving ground. "
+youtube-code: "TBD"
+---
diff --git a/_talks/students_sp24.md b/_talks/students_sp24.md
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----
-speaker: Student Speakers (TBD)
-affiliation: Stanford
-website: "TBD"
-date: 2024-05-03T12:30:00-0000
-location: Skilling Auditorium
-location-url: "https://campus-map.stanford.edu/?srch=Skillaud"
-title: "TBD"
-abstract: "TBD"
-youtube-code: "TBD"
----