Category: ECE

Master’s Defense: Chinmay Kondekar

Electrical Engineering Master’s candidate Chinmay Kondekar (advisor: Aleksandr Sergeyev), will present his master’s defense at 11 a.m. tomorrow (April 13) via Zoom.

The title of his presentation is “Integration of Robotic and Electro-Pneumatic Systems Using Advanced Control and Communication Schemes.”


ECE Doctoral Defense – Adam Webb

by Electrical and Computer Engineering Department

Electrical Engineering doctoral candidate Adam Webb will present his PhD defence at 3:30 p.m. Thursday (April 15) via Zoom.

The title of his presentation is “Novel Methods in Computational Imaging with Applications in Remote Sensing.”

Webb’s co-advisors are Timothy Schulz (ECE) and Timothy Havens (CC).


ECE Master’s Defense: Chinmay Rajaram Kondekar

by Electrical and Computer Engineering

Electrical Engineering Master’s candidate Chinmay Kondekar (advisor: Aleksandr Sergeyev), will present his master’s defense at 11 a.m. Tuesday (April 13) via Zoom

The title of his presentation is “Integration of Robotic and Electro-Pneumatic Systems Using Advanced Control and Communication Schemes.” 


Sidike Paheding, Applied Computing, Publishes Paper in IEEE Access

A paper co-authored by Sidike Paheding, Applied Computing, has been published in the journal, IEEE Access. “Trends in Deep Learning for Medical Hyperspectral Image Analysis,” was available for early access on March 24, 2021.

The paper discusses the implementation of deep learning for medical hyperspectral imaging.

Co-authors of the paper are Uzair Khan, Colin Elkin, and Vijay Devabhaktuni, all with the Department of Electrical and Computer Engineering, Purdue University Northwest.

Abstract

Deep learning algorithms have seen acute growth of interest in their applications throughout several fields of interest in the last decade, with medical hyperspectral imaging being a particularly promising domain. So far, to the best of our knowledge, there is no review paper that discusses the implementation of deep learning for medical hyperspectral imaging, which is what this work aims to accomplish by examining publications that currently utilize deep learning to perform effective analysis of medical hyperspectral imagery.

This paper discusses deep learning concepts that are relevant and applicable to medical hyperspectral imaging analysis, several of which have been implemented since the boom in deep learning. This will comprise of reviewing the use of deep learning for classification, segmentation, and detection in order to investigate the analysis of medical hyperspectral imaging. Lastly, we discuss the current and future challenges pertaining to this discipline and the possible efforts to overcome such trials.

DOI: 10.1109/ACCESS.2021.3068392

IEEE Access is a multidisciplinary, applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE’s fields of interest. Supported by article processing charges, its hallmarks are a rapid peer review and publication process with open access to all readers.


Emily Zhang Is ME-EM Graduate Seminar Speaker

by Mechanical Engineering – Engineering Mechanics

The next virtual Graduate Seminar Speaker will be held at 4 p.m. tomorrow (Feb. 25) via Zoom.

Lan (Emily) Zhang (ECE) will present “Augmenting Radio Environments for better Wireless Ecosystems.”

Zhang is a member of the Institute of Computing and Cybersystems’s (ICC) Center for Cyber-Physical Systems.


Computing Programs Ranked Among Best in Nation

Several Michigan Tech College of Computing degree programs have been ranked among the best in the nation by Intelligent.com. In addition, the research guide ranked the University number three among all colleges in Michigan.

Intelligent.com looked at nearly 2,300 accredited colleges and universities nationwide making evaluations based on curriculum quality, graduation rate, reputation and post-graduate employment. Programs were evaluated on a scale of 0 to 100 with Michigan Tech making it to the final list for 12 separate degree programs.

The four College of Computing programs and their national ranking as rated by Intelligent.com are:

Additional Michigan Tech degree programs included in the ranking are:


Nathir Rawashdeh Presents, Publishes Research at Mechatronics Conference

A conference paper published in IEEE Xplore entitled, “Interfacing Computing Platforms for Dynamic Control and Identification of an Industrial KUKA Robot Arm” has been published by Assistant Professor Nathir Rawashdeh, Applied Computing.

In this work, a KUKA robotic arm controller was interfaced with a PC using open source Java tools to record the robot axis movements and implement a 2D printing/drawing feature.

The paper was presented at the 2020 21st International Conference on Research and Education in Mechatronics (REM). Details available at the IEEE Xplore database.


Lan Zhang, ECE, to Present Lecture Jan. 15, 3 pm

Assistant Professor Lan “Emily” Zhang, Electrical and Computer Engineering, will present her lecture, “Augmenting Radio Environments for Better Wireless Ecosystems,” on Friday, January 15, 2021, at 3:00 p.m., via online meeting.

The lecture is hosted by the Michigan Tech Department of Computer Science. Zhang is a member of the Cyber-Physical Systems (CPS) research group of the Institute of Computing and Cybersystems (ICC).

Zhang’s research interest span the fields of cyber-physical systems, distributed machine learning, wireless communications, and cybersecurity. In her talk, she will discuss a series of studies leveraging smart-surfaces, e.g., meta-surfaces or reconfigurable intelligent surfaces (RISs), to augment radio environments for various purposes.

Lecture Abstract

In the last several decades, wireless technologies have become well-established to fight against propagation obstacles. Most conventional efforts are focused on optimizing end devices, such as transmitters and receivers, in order to adapt to the given transmission environment for better communications. However, the recent rapid convergence of the cyber and physical worlds (Cyber-Physical Systems or CPSs) presents unprecedented challenges to the wisdom of conventional design. Given ever-growing service demands, as well as the diverse wireless application scenarios, it is critical to adaptively augment the radio environments in a cost-effective way, while maintaining the aesthetic nature of living environments.

In her talk, Zhang will discuss a series of studies leveraging smart-surfaces–e.g., meta-surfaces or reconfigurable intelligent surfaces (RISs)–to augment radio environments for various purposes. Specifically, she will focus on three promising areas for enhancing the throughput and reliability of wireless communications, mitigating the physical-layer security threats, and facilitating wireless sensing activities. Both model-based and learning-based methods will be used for theoretical and practical analysis.

Biography

Dr. Lan Zhang is an assistant professor in the Department of Electrical and Computer Engineering at Michigan Tech. She received a Ph.D. degree in computer engineering from the University of Florida in 2020, and M.S. and B.Eng. degrees in telecommunication engineering from the University of Electronic Science and Technology of China in 2016 and 2013, respectively.

Zhang has served as a technical program committee member for several respected conferences, such as NeurIPS-SpicyFL 2020 and the 2020 IEEE IFOCOM poster/demo section. She has also served as reviewer for leading journals, such as IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, IEEE Transactions on Mobile Computing, and IEEE Transactions on Wireless Computing.

Lan Zhang, ECE