Friday, Jan. 24, 2025
10:20 – 11:10 a.m. (CST)
ETB 1020
Dr. Toros Arikan
Postdoctoral Researcher, Electrical and Computer Engineering Dept.
Rice University
Title: “Deep Learning for Smarter Algorithms in Detection, Estimation, and Navigation”
Abstract
By deploying deep learning methods as global optimizers that learn algorithms, we can solve long-standing ill-posed problems in joint parameter estimation. Neural networks can also produce human-interpretable results that de-mystify the algorithm design process, allowing us to rigorously determine hyperparameters such as training lengths. I will introduce two recent works where this methodology is used to tackle open problems in remote sensing and navigation. In underwater environment estimation, I will present a U-Net method for the acoustic mapping of reflective boundaries such as the sea surface and seafloor, with state-of-the-art performance and the new capability of jointly estimating the number of boundaries in the environment. In the field of robotic path planning, I will present a recurrent convolutional neural network (RCNN) method for solving Obstacle Avoiding Rectilinear Steiner Minimum Tree (OARSMT) problems. By learning an algorithm via reinforcement learning, whose intermediate stages are visible to the user, we devise augmentations that yield strong accuracy and runtime performances, which can lead to lower power consumption. Beyond their immediate applications, these new methods point to a general strategy of solving a broad class of joint parameter estimation problems via deep learning.
Biography
Dr. Toros Arikan was born in Mount Kisco, NY, USA, in 1993. He obtained his B.S. and M.S. degrees from the University of Illinois at Urbana-Champaign, with a focus on digital communications and signal processing; and his Ph.D. degree from the Massachusetts Institute of Technology, specializing in localization, tracking, and remote sensing. He is currently a postdoctoral researcher at Rice University, where he continues his research on deep learning methods for environment estimation and algorithm development.
Please join us on Friday, 01/24/25 at 10:20 a.m. in ETB 1020 to learn more and meet Dr. Toros Arikan.
For more on Dr. Toros Arikan visit his website at https://torosarikan.github.io/.