Zoom: https://illinois.zoom.us/j/84595638473?pwd=ZGFUVC9yaEJ2N3B3K0NpSVhXUi9wdz09
Abstract:
The rapid advancement of computer science, the high demand for skilled computer scientists, and the growing student interest in computer science require proactive approaches to ensure the learning goals are achieved in heterogeneous classrooms and academic settings. To fully benefit students, we can take advantage of the growing availability of technology tools and novel insights from pedagogical research. I will present several lessons, perspectives, plans, and goals that can benefit students’ long-term learning in various academic scenarios from the views and experiences acquired from teaching and tutoring various computer science courses in the USA and Ecuador.
Bio:
Pablo Robles-Granda received his Ph.D. in Computer Science from Purdue University in 2017. He is currently a postdoctoral research associate in the Computer Science department at the University of Illinois at Urbana-Champaign and a visiting postdoctoral scholar at Stanford Artificial Intelligence Lab (SAIL). His teaching goal is to cultivate students’ enthusiasm for computer science. He has received a teaching award as a Wakonse College Teaching Fellow and has taught various courses at both graduate and undergraduate levels. The courses taught include Applied Machine Learning, Advanced Machine Learning, Data Science, Theory and Implementation of Programming Languages, Data Structures, and Computer Essentials/Intro to Computing. He has served as a mentor and advisor for several research projects and has also been a part of Ph.D. dissertation committees and outreach programs. His research interests include Machine Learning and Data Science applied to Cognitive & Physical Well-being, Health Informatics, and Network Science. He came to Illinois as an Illinois Future Faculty Fellow in the Computer Science department and was previously a research assistant professor at the University of Notre Dame, an intern at Apple Inc, and a Research Assistant at Purdue University. He has received several honors and awards, including being a Top Reviewer at the International Conference on Machine Learning (ICML) 2020 and receiving an Academic Excellence Fellowship from the National Science Foundation of Ecuador in 2011, among other honors.
Faculty Host: Geoffrey Challen
Meeting ID: 845 9563 8473; Password: csillinois
