Upenn seas gaussian software
Additionally created various materials for objects such as reflective, refractive, and diffused surfaces.
#UPENN SEAS GAUSSIAN SOFTWARE FREE#
I love to talk about my work to anyone who wants to know more, so please feel free to ask me about anything you see here! TECHNICAL PROJECTSĬUDA Path Tracer and Denoiser (C++, CUDA) Implemented a basic path tracing algorithm in which rays are bounced between objects for multiple iterations to average each pixel's color in the scene. I am currently working on various personal projects involving Blender, Maya, and some painting and drawing. In my free time, I enjoy cooking, painting, and dancing. I love exploring the space where technology intersects art, and I hope to pursue a career that allows me to fulfill my love for both.
In addition, I developed my own eCommerce shop, and have served as the Creative Director for my dance company.
#UPENN SEAS GAUSSIAN SOFTWARE SOFTWARE#
I have experience working as a software engineering intern, a social media marketing intern, and a teaching assistant for electrical engineering and computer science courses at Penn. I am passionate about computer graphics, animation, and all types of art and design. At Penn, I am a developer for Penn Creative Labs, a member of Hexagon Engineering Senior Society, and the current director of Strictly Funk Dance Company. Next school year I will be a Master's student studying Computer Graphics and Game Technology (Class of 2023). At UMBC, he was a member of the Multi-Agent Planning and LEarning (MAPLE) research group and also a part-time instructor.Hi, I'm Lindsay! I am currently a senior at the University of Pennsylvania studying Computer Engineering and Design. His dissertation developed methods for selective knowledge transfer between learning tasks and was advised by in computer science from the University of Maryland, Baltimore County (UMBC), focusing on artificial intelligence and machine learning. While at Lockheed Martin, he was also part-time faculty in computer science atĮric received his Ph.D. At Lockheed Martin ATL, he led a number of machine learning research projects in the Artificial Intelligence Lab with a focus on their application for a variety of DoD organizations. Lockheed Martin Advanced Technology Laboratories This research is funded by grants from the Office of Naval Research, the National Science Foundation, and Lockheed Martin.īefore moving into academia, Eric spent two years as a senior research scientist at In particular, his research focuses on developing versatile AI systems that can learn multiple tasks over a lifetime of experience in complex environments, transfer learned knowledge to rapidly acquire new abilities, and collaborate effectively with humans and other agents through interaction. His primary research interests lie in the fields of machine learning, artificial intelligence, and data mining with applications to robotics, search & rescue, environmental sustainability, and medicine. Prior to joining Penn, he was a Visiting Assistant Professor in the GRASP (General Robotics Automation, Sensing, Perception) lab. University of Pennsylvania, and a member of the
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Presented papers on this project at AAAI'12 and Computational Sustainability 2012.ĭepartment of Computer and Information Science This book is intended to supplement an AI course with assignments related to sustainability. Past courses taught at Bryn Mawr, Swarthmore, and UMBCĭoug Fisher, Bistra Dilkina, Carla Gomes, and I started the online textbook Artificial Intelligence for Computational Sustainability: A Lab Companion as an experiment in crowd-sourced textbook creation. Spring 2013: CMSC 246 - Programming Paradigmsįall 2012: CMSC 110 - Introduction to Computing Spring 2013: CMSC 380 - Relational Network Analysis Spring 2014: CIS 110 - Introduction to Computer Scienceįall 2013: CIS 110 - Introduction to Computer Science Spring 2015: CIS 110 - Introduction to Computer Scienceįall 2014: CIS 419/519 - Introduction to Machine Learning Spring 2016: CIS 110 - Introduction to Computer Scienceįall 2015: CIS 700 - Integrated Intelligence for Roboticsįall 2015: CIS 419/519 - Introduction to Machine Learning Fall 2016: CIS 700 - Integrated Intelligence for Roboticsįall 2016: CIS 419/519 - Introduction to Machine Learning