Abstract: One of the main challenges of modern medicine is the detection of silent progression and migration of various diseases through the human body. For instance, cancer is one of the leading causes of death because in most situations tumors appear and develop undetected by many of the current screening tests or the immune system. Nevertheless, a large body of research in the analysis of tumor angiogenesis suggests that tumors’ silent progression is most of the time accompanied by an increased demand for nutrients and oxygen. Most of the time, these events are not easily detected by the immune system and the cancer cells can corrupt the neighboring and remote organs up to the point where surgery cannot help with a cure. To address these challenges, we exploit the bacterial motility and molecular communication capabilities in order to design dense networks of bacteria for monitoring, detecting and delivering targeted drugs within the human body. We cease to view bacteria microrobots as point-like particles, but rather as truly interactive Turing machines performing complex intracellular biochemical processing for disease cue searching in the environment. In addition, we propose a non-equilibrium statistical physics approach capable of accounting for both medium-range interaction among bacteria via molecular messengers and volume exclusion effects. Of note, to account for the molecular communication and processing at both inter and intra-cellular levels we develop a multiscale simulation environment. This computational framework enables the identification of various design trade-offs for dense networks of bacteria.
This research is a joint effort with Guopeng Wei and Radu Marculescu of Carnegie Mellon University.
Bio: Paul Bogdan received his Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh. He is an assistant professor in the Ming Hsieh Department of Electrical Engineering at University of Southern California. His work has been recognized with a number of distinctions, including the 2012 A.G. Jordan Award from the Electrical and Computer Engineering Department, Carnegie Mellon University for outstanding Ph.D. thesis and service, the 2012 Best Paper Award from the Networks-on-Chip Symposium (NOCS), the 2012 D.O. Pederson Best Paper Award from IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, the 2012 Best Paper Award from the International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), the 2013 Best Paper Award from the 18th Asia and South Pacific Design Automation Conference, and the 2009 Roberto Rocca Ph.D. Fellowship. His research interests include performance analysis and design methodologies for multicore systems, the theoretical foundations of cyber-physical systems, the modeling and analysis of bio-inspired computing, and the applications of statistical physics to biological systems and regenerative medicine.