Category: Research

Weihua Zhou Receives PHF Seed Grant

The Michigan Tech Vice President for Research office has announced the Spring 2020 Research Excellence Fund (REF) awards. Among the recipients is Assistant Professor Weihua Zhou, Applied Computing/Health Informatics, who received a Portage Health Foundation Research Seed Grant.

Zhou’s areas of expertise include image processing and computer vision, machine learning, medical image analysis, health informatics, and text mining.

Read the full Tech Today announcement here.

Learn more about Michigan Tech REF awards here.


ICC Releases FY19 Annual Report

The Institute of Computing and Cybersystems has released its FY 19 Annual Report, which can be viewed and downloaded on the ICC website.

We had a strong year in 2018-19,” says Timothy Havens, director of the ICC and associate dean for research, College of Computing.

“In FY20, new awards and research expenditures were even stronger, and I look forward to sharing more accomplishments with you in the coming months.”

Tim Havens, ICC Director

Signature Research, Michigan Tech win $1 Million NGA Research Award

Signature Research Inc. has partnered with Michigan Technological University to accomplish a Phase II STTR project sponsored by the National Geospatial-Intelligence Agency. The two-year, $1 Million project is titled, “Algorithms for Look-Down Infrared Target Exploitation-Phase II.” Michigan Tech’s portion of the $1 million contract is $400K.


Principal investigator of the project is Dr. Timothy Havens, director of the Institute of Computing and Cyberystems (ICC) and associate dean of research for the College of Computing. Havens is joined by Signature Research, Inc. (SGR) Program Manager Matt Blanck, who will lead the SGR side of the project.

At Tech, Havens will be assisted in accomplishing the goals of this project by Research Scientist Adam Webb of the Michigan Tech Research Institute (MTRI) and Nicholas Hamilton, a Computer Science Ph.D. candidate.

“This project will identify physics-based novel signatures and data processing techniques to exploit overhead infrared (IR) imagery using machine learning algorithms.”

“The SGR/MTU Team will generate, collect, and label a wide body of data, implement learning algorithms, develop use cases and tests on those data, and perform a comprehensive study to determine ways in which learning algorithms can automate IR imagery recognition tasks.”

Dr. Timothy Havens

And while this effort is focused on overhead IR imagery, Havens says the methods and software developed will have applicability to other sensing modalities, leading to investigations of multi-modal fusion of all-source data.


Signature Research, Inc. (SGR) solutions to DoD and Intelligence Community customers, and specializes in in Signature Phenomenology, Analysis, and Modeling of items of military interest covering the breadth of the electromagnetic spectrum.

The National Geospatial-Intelligence Agency (NGA) is a combat support agency under the United States Department of Defense and a member of the United States Intelligence Community, with the primary mission of collecting, analyzing, and distributing geospatial intelligence in support of national security.

The Institute of Computing and Cybersystems (ICC) promotes research and learning experiences in the areas of cyber-physical systems, cybersecurity, data sciences, human-centered computing, and scalable architectures and systems for the benefit of Michigan Tech and society at large.

The Michigan Tech Research Institute (MTRI) is an innovator in building information from data through the marriage of phenomenological understanding and implementation of mathematically rigorous algorithms. Together with University and other national and international collaborators, MTRI researchers and scientists work to solve critical problems in national security, protecting and evaluating critical infrastructure, bioinformatics, Earth sciences, and environmental processes, according to their website.


Nathir Rawashdeh Publishes Paper in BioSciences Journal

A paper co-authored by Assistant Professor Nathir Rawashdeh (DataS, Applied Computing) on Skin Cancer Image Feature Extraction, has been published this month in the EurAsian Journal of BioSciences.

View the open access article, “Visual feature extraction from dermoscopic colour images for classification of melanocytic skin lesions,” here.

Additional authors are Walid Al-Zyoud, Athar Abu Helou, and Eslam AlQasem, all with the Department of Biomedical Engineering, German Jordanian University, Amman, Jordan.

Citation: Al-Zyoud, Walid et al. “Visual feature extraction from dermoscopic colour images for classification of melanocytic skin lesions”. Eurasian Journal of Biosciences, vol. 14, no. 1, 2020, pp. 1299-1307.

Rawashdeh’s interests include unmanned ground vehicles, electromobility, robotics, image analysis, and color science. He is a senior member of the IEEE.


Sergeyev, Students Earn ASEE Conference Awards

Professor Aleksandr Segeyev (DataS), Applied Computing, and a group of Michigan Tech students presented two papers at the 2020 American Society for Engineering Education (ASEE) Gulf-Southwest Annual conference, which was conducted online April 23-24, 2020. Both papers received conference awards.

Faculty Paper Award

“Pioneering Approach for Offering the Convergence MS Degree in Mechatronics and Associate Graduate Certificate”
by Sergeyev, Professor and Associate Chair John Irwin (MMET), and Dean Adrienne Minerick (CC).

Student Paper Award

“Efficient Way of Converting outdated Allen Bradley PLC-5 System into Modern ControlLogix 5000 suit”, by Spencer Thompson (pictured), Larry Stambeck, Andy Posa, Sergeyev, and Lecturer Paniz Hazaveh, Applied Computing.

Sergeyev is director of the Michigan Tech Mechatronics Graduate Program and FANUC Certified Industrial Robotics Training Center.

Founded in 1893, the American Society for Engineering Education is a nonprofit organization of individuals and institutions committed to furthering education in engineering and engineering technology.


Thomas Oommen PI of 41K RD Contract

Professor Thomas Oommen (DataS, GMES, EPSSI) is the principal investigator on a one-year project that has been awarded a $41K research and development contract with the University of Nebraska-Omaha.

The project is titled “Flood Hazard Map to Water Management & Planning.”

Oommen’s research focuses on developing improved susceptibility characterization and documentation of geo-hazards (e.g. earthquakes, landslides) and spatial modeling of georesource (e.g. mineral deposits) over a range of spatial scales and data types.

To achieve his research interests, he has adopted an inter-disciplinary research approach joining aerial/satellite based remote sensing for obtaining data, and artificial intelligence/machine learning based methods for data processing and modeling.


Recap: Virtual Parallel-in-Time Workshop 2020

The virtual 2020 Parallel-in-Time conference, co-organized by Assistant Professor Benjamin Ong (DataS, Mathematics), took place June 8 to 12, 2020.

The conference consisted of 20 presentations, including one by Mathematics department graduate student, Nadun Dissanayake.

140 participants in more than a dozen countries registered and participated in the conference. View the conference video lectures and program information here.

The primary focus of the Parallel-in-Time Workshop was to disseminate cutting-edge research and facilitate scientific discussions on the field of parallel time integration methods.

Download the conference program booklet here.


Bo Chen, Grad Students Present Posters at Security Symposium

College of Computing Assistant Professor Bo Chen, Computer Science, and his graduate students presented two posters at the 41st IEEE Symposium on Security and Privacy, which took place online May 18 to 21, 2020.

Since 1980, the IEEE Symposium on Security and Privacy has been the premier forum for presenting developments in computer security and electronic privacy, and for bringing together researchers and practitioners in the field.

Chen leads the Security and Privacy (SnP) lab at Michigan Tech. He is a member of Michigan Tech’s Institute of Computing and Cybersystems (ICC) Center for Cybersecurity (CyberS).

Chen’s research focuses on applied cryptography and data security and he investigates novel techniques to protect sensitive data in mobile devices/flash storage media and cloud infrastructures. Chen is also interested in designing novel techniques to ensure security and privacy of big data.

Chen will serve as general chair for the First EAI International Conference on Applied Cryptography in Computer and Communications (AC3), which will be held in Xiamen, China, in May 2021.

Visit Bo Chen’s faculty webpage here.

Poster: A Secure Plausibly Deniable System for Mobile Devices against Multi-snapshot Adversaries
Authors: Bo Chen, Niusen Chen
Abstract: Mobile computing devices have been used broadly to store, manage and process critical data. To protect confidentiality of stored data, major mobile operating systems provide full disk encryption, which relies on traditional encryption and requires keeping the decryption keys secret. This however, may not be true as an active attacker may coerce victims for decryption keys. Plausibly deniable encryption (PDE) can defend against such a coercive attacker by disguising the secret keys with decoy keys. Leveraging concept of PDE, various PDE systems have been built for mobile devices. However, a practical PDE system is still missing which can be compatible with mainstream mobile devices and, meanwhile, remains secure when facing a strong multi- snapshot adversary. This work fills this gap by designing the first mobile PDE system against the multi-snapshot adversaries.

Poster: Incorporating Malware Detection into Flash Translation Layer
Authors: Wen Xie, Niusen Chen, Bo Chen
Abstract: OS-level malware may compromise OS and obtain root privilege. Detecting this type of strong malware is challeng- ing, since it can easily hide its intrusion behaviors or even subvert the malware detection software (or malware detector). Having observed that flash storage devices have been used broadly by computing devices today, we propose to move the malware detector to the flash translation layer (FTL), located inside a flash storage device. Due to physical isolation provided by the FTL, the OS-level malware can neither subvert our malware detector, nor hide its access behaviors from our malware detector.

The 41st IEEE Symposium on Security and Privacy was sponsored by the IEEE Computer Society Technical Committee on Security and Privacy in cooperation with the International Association for Cryptologic Research. The Symposium was May 18-20, 2020, and the Security and Privacy Workshops were May 21, 2020.


Computing Awards COVID-19 Research Seed Grants

The College of Computing is pleased to announce that it has awarded five faculty seed grants, which will provide immediate funding in support of research projects addressing critical needs during the current global pandemic.

Tim Havens, College of Computing associate dean for research, said that the faculty seed grants will enable progress in new research that has the potential to make an impact on the current research. Additional details will be shared soon.


Congratulations to the winning teams!

Guy Hembroff (AC, HI): “Development of a Novel Hospital Use Resource Prediction Model to Improve Local Community Pandemic Disaster Planning”

Leo Ureel (CS) and Charles Wallace (CS): “Classroom Cyber-Physical Simulation of Disease Transmission”

Bo Chen (CS): “Mobile Devices Can Help Mitigate Spreading of Coronavirus”

Nathir Rawashdeh (AC, MERET): “A Tele-Operated Mobile Robot for Sterilizing Indoor Space Using UV Light” (A special thanks to Paul Williams, who’s generous gift to support AI and robotics research made this grant possible)

Weihua Zhou (AC, HI) and Jinshan Tang (AC, MERET): “KD4COVID19: An Open Research Platform Using Feature Engineering and Machine Learning for Knowledge Discovery and Risk Stratification of COVID-19″

Weihua Zhou

Nathir Rawashdeh

Jinshan Tang

Guy Hembroff

Leo Ureel

Charles Wallace

Bo Chen


Havens, Yazdanparast Publish Article in IEEE Transactions on Big Data

Timothy Havens

An article by Audrey Yazdanparast (2019, PhD, Electrical Engineering) and Dr. Timothy Havens, “Linear Time Community Detection by a Novel Modularity Gain Acceleration in Label Propagation,” has been accepted for publication in the journal, IEEE Transactions on Big Data.

The paper presents an efficient approach for detecting self-similar communities in weighted graphs, with applications in social network analysis, online commodity recommendation systems, user clustering, biology, communications network analysis, etc.

Paper Abstract: Community detection is an important problem in complex network analysis. Among numerous approaches for community detection, label propagation (LP) has attracted a lot of attention. LP selects the optimum community (i.e., label) of a network vertex by optimizing an objective function (e.g., Newman’s modularity) subject to the available labels in the vicinity of the vertex. In this paper, a novel analysis of Newman’s modularity gain with respect to label transitions in graphs is presented. Here, we propose a new form of Newman’s modularity gain calculation that quantifies available label transitions for any LP based community detection.

The proposed approach is called Modularity Gain Acceleration (MGA) and is simplified and divided into two components, the local and global sum-weights. The Local Sum-Weight (LSW) is the component with lower complexity and is calculated for each candidate label transition. The General Sum-Weight (GSW) is more computationally complex, and is calculated only once per each label. GSW is updated by leveraging a simple process for each node-label transition, instead of for all available labels. The MGA approach leads to significant efficiency improvements by reducing time consumption up to 85% relative to the original algorithms with the exact same quality in terms of modularity value which is highly valuable in analyses of big data sets.

Timothy Havens is director of Michigan Tech’s Institute of Computing and Cybersystems (ICC), the associate dean for research for the College of Computing , and the William and Gloria Jackson Associate Professor of Computer Systems.

View the article abstract here.