Daniel Seita

Fostering growth in knowledge systems for the next generation of robotics, Daniel Seita is an Assistant Professor of Computer Science at the University of Southern California (USC). His research is at the forefront of computer vision and machine learning, with a particular focus on enhancing robot manipulation capabilities. Daniel is especially interested in developing innovative methods to improve the manipulation of challenging deformable objects, a critical area in advancing robotic applications in real-world scenarios. Before his tenure at USC, Daniel honed his expertise as a postdoctoral researcher at Carnegie Mellon University's prestigious Robotics Institute. His work there contributed significantly to the field, laying the groundwork for his current research endeavors. Daniel's academic journey is marked by a PhD in computer science from the University of California, Berkeley, where he developed a strong foundation in machine learning and robotics. Daniel's contributions to the field are not just limited to research; he is also deeply committed to teaching and mentoring the next generation of computer scientists. His courses at USC are designed to inspire students and equip them with the skills necessary to tackle complex problems in robotics and artificial intelligence. Through his work, Daniel aims to bridge the gap between theoretical research and practical applications, ensuring that his innovations have a tangible impact on society. In addition to his academic pursuits, Daniel actively collaborates with industry partners to translate his research into real-world solutions. His work has been recognized in numerous publications and conferences, reflecting his dedication to advancing the field of robotics. Daniel continues to push the boundaries of what is possible in robot manipulation, striving to create systems that are not only intelligent but also adaptable to the dynamic challenges of the modern world.