Chee-Wooi Ten Negotiates Two Book Contracts with CRC Press

By Karen S. Johnson, Communications Director, Institute of Computing and Cybersystems

Associate Professor Chee-Wooi Ten, Electrical and Computer Engineering, recently finalized contracts to write two books for CRC Press, a major publisher of humanities, social science, and STEM books and textbooks. Ten is a member of the Institute of Computing and Cybersystems’s Center for Cyber-Physical Systems.

The first book is titled, Electric Power Distribution System Engineering, 4th edition. Ten has been teaching EE5250 Distribution Engineering I at Michigan Tech for 10 years.

The second book, Modern Power System Analysis, 3rd Edition, is used to accompany a senior-level power engineering elective. Both books are tentatively scheduled to be published in January 2022.

The new editions continue the work of the late Professor Turan Gönen, a leading expert and popular professor of electrical engineering at California State University, Sacramento. Gönen devoted his life to the writing of four textbooks. One of them, “Electric Power Distribution System Engineering,” published in 2013, is still taught in college classrooms worldwide. Ten notes that it is one of only a few Distribution Engineering textbooks that remains highly regarded by the international research community.

Book contract negotiations were initiated by Nora Konopka, editorial director of engineering at CRC Press/Taylor & Francis. Konopka worked with Ten on a previous book published by the company.

And although Ten did not personally know Prof. Gönen, he has used Gönen’s books in his courses. Ten says he believes Konopka contacted him because she has confidence that he will do an excellent job in carrying on Gönen ‘s work and legacy.

“As a course instructor, especially when you’ve just started, you explore the textbook and master the materials while teaching,” Ten reflects. “Written and revised throughout his long career, the contents of Gönen’s books are enriched from his decades of experience in pedagogy.”

Konopka’s original proposal was for Ten to write four new editions of books by Prof. Gönen. Ten told her, “I cannot do four books, but I can find two other authors who have the expertise to complete those books.”

So, with collaborators at University of Hong Kong and Virginia Tech, all four books will be completed and published. Two of them written by Ten, one each by his collaborators.

“My colleagues on this project are research-active faculty, and I am very proud to have an opportunity to collaborate with them,” Ten says, noting that they represent two of the best engineering programs in the world.

“These books are collaborative, and we will work together to ensure the next editions of these textbooks reflect today’s industrial and academic knowledge and best practices,” Ten says.

But there are challenges associated with this kind of project. Ten explains that the book materials he has inherited, which are in Microsoft Word, must be converted to the typesetting format he prefers, LaTeX. Only then can he begin editing the books. Fortunately, Ten was able to hire a few students; he expects them to complete the conversions by year-end.

“Then, for the next year, I can focus on qualitative development of the content,” Ten predicts. “I plan to ‘test drive’ some of the new content in the power engineering courses I have been teaching.”

Read an obituary of Prof. Turan Gönen here.

CRC Press. is an imprint of Taylor & Francis Group, part of Informa PLC, one of the world’s leading business intelligence and academic publishing businesses. The company publishes more than 2,700 journals and 5,000 new books each year. CRC Press specializes in Science, Technology and Medical books.

Founded in 2015, the Institute of Computing and Cybersystems (ICC) promotes collaborative, cross-disciplinary research and learning experiences in the areas of computing education, cyber-physical systems, cybersecurity, data sciences, human-centered computing, and scalable architectures and systems, for the benefit of Michigan Technological University and society at large.

The ICC creates and supports an arena in which faculty and students work collaboratively across organizational boundaries in an environment that mirrors contemporary technological innovation. The ICC’s 55+ members working in six research centers represent more than 20 academic disciplines at Michigan Tech. Member scientists are collaborating to conduct impactful research, make valuable contributions in the field of computing, and solve problems of critical national importance.

Full Citations

Turan Gönen, Chee-Wooi Ten**, and Ali Mehrizi-Sani, “Electric Power Distribution System Engineering,” 4th Edition CRC, January 2022 (tentatively).

Turan Gönen, Chee-Wooi Ten**, and Yunhe Hou, “Modern Power System Analysis,” 3rd Edition, CRC, January 2022 (tentatively).

Jim Keller to Present ICC Distinguished Lecture October 30

Dr. James Keller, recently retired Curators’ Distinguished Professor in the EE/CS department at University of Missouri, Columbia, will present his lecture, “Soft Streaming Classification,” on Friday, October 30, 2020, at 3:00 p.m., via Zoom online meeting.

The talk is an Institute of Computing and Cybersystems’ (ICC) Distinguished Lecture Series event.

Join the meeting here.


A Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE), Keller recently received the IEEE Frank Rosenblatt Award for his “fundamental work on fuzzy pattern recognition, fuzzy clustering, and fuzzy technologies in computer vision.” He holds a number of additional professional and academic honors and awards.

Lecture Abstract

As the volume and variety of temporally acquired data continues to grow, increased attention is being paid to streaming analysis of that data. Think of a drone flying over unknown terrain looking for specific objects which may present differently in different environments. Understanding the evolving environments is a critical component of a recognition system.

With the explosion of ubiquitous continuous sensing (something Lotfi Zadeh predicted as one of the pillars of Recognition Technology in the late 1990s), this on-line streaming analysis is normally cast as a clustering problem. However, examining most streaming clustering algorithms leads to the understanding that they are actually incremental classification models.

These approaches model existing and newly discovered structures via summary information that we call footprints. Incoming data is routinely assigned crisp labels (into one of the structures) and that structure’s footprints are incrementally updated; the data is not saved for iterative assignments.

The three underlying tenets of static clustering:

  1. Do you believe there are any clusters in your data?
  2. If so, can you come up with a technique to find the natural grouping of your data?
  3. Are the clusters you found good groupings of the data?

These questions do not directly apply to the streaming case. What takes their place in this new frontier?

In this talk, I will provide some thoughts on what questions can substitute for the Big 3, but then focus on a new approach to streaming classification, directly acknowledging the real identity of this enterprise. Because the goal is truly classification, there is no reason that these assignments need to be crisp.

With my friends, I propose a new streaming classification algorithm, called StreamSoNG, that uses Neural Gas prototypes as footprints and produces a possibilistic label vector (typicalities) for each incoming vector. These typicalities are generated by a modified possibilistic k-nearest neighbor algorithm.

Our method is inspired by, and uses components of, a method that we introduced under the nomenclature of streaming clustering to discover underlying structures as they evolve. I will describe the various ingredients of StreamSoNG and demonstrate the resulting algorithm on synthetic and real datasets.

NSF Research to Study Household Dynamics in Pandemic

David Watkins (CEE/SFI) is the principal investigator on a project that has received a $190,764 research and development grant from the National Science Foundation (NSF).

The project is titled “RAPID: COVID-19, Consumption, and Multi-dimensional Analysis of Risk (C-CAR)“. Chelsea Schelly (SS/SFI), Robert Handler (ChE/SFI) and Charles Wallace (CS/SFI) are co-PIs on this one-year project.

Extract

The COVID-19 pandemic has transformed household dynamics and dramatically changed food, energy, and water consumption within the home. Stay-at-home orders and social distancing has caused U.S. households to shift to working and schooling from home, curtail outside activities, and stop eating in restaurants. Furthermore, as many households face job loss and increasing home utility and grocery bills, U.S. residents are experiencing the economic impacts of the crisis, while at the same time assessing and responding to health risks. The project team has a unique opportunity to study these shifting household consumption and behavioral responses and quantify the associated economic and environmental impacts. The team will collect household food, energy, and water consumption data as well as survey response data from 180 participating households in one Midwestern county and compare it to data collected before the stay-at-home orders were put in place.

Read more at the National Science Foundation.

Tim Schulz to Present Michigan Tech Research Forum Oct. 14

Timothy Schulz

University Professor Timothy Schulz (ECE) will be featured at the Michigan Tech Research Forum (MTRF) at 4:30 p.m. Wednesday, Oct. 14.
Schulz’s presentation is titled “Direct Measurement of Coherent Fields.” Additional details can be found on the MTRF website.

The presentation will be available via Zoom and a limited number of people will be permitted to attend in person, dependent on university guidelines on the date of the event. If you wish to be considered for in-person attendance, complete this form by today (Oct. 9).

Schulz is a member of the ICC’s Center for Data Sciences.

The MTRF is presented by the Office of the Provost in coordination with the Office of the Vice President for Research. The forum showcases and celebrates the work of Michigan Tech researchers and aims to strengthen discussions in our community. All are welcome, including the general public.

Kanwal Rekhi to Receive Melvin Calvin Medal of Distinction

A Michigan Tech alumnus with a long history of philanthropy and support of students will receive the University’s highest honor.

At its meeting, Friday, (Oct. 8, 2020), the Michigan Tech Board of Trustees approved awarding the Melvin Calvin Medal of Distinction to Kanwal Rekhi. The native of Punjab, in what was then British India (now Pakistan), earned a master’s in electrical engineering from Michigan Tech in 1969. In the more than half a century since his time on campus, MTU has never been far from Rekhi’s thoughts … and generosity.

After leaving Michigan Tech, Rekhi worked as an engineer and manager before becoming an entrepreneur. In 1982, he co-founded Excelan a company that made Ethernet cards to connect PCs to the fledgling Internet. Excelean became the first Indian-owned company to go public in the U.S. In the early 90s, he became a venture capitalist investing in more than 50 startups and sitting on the board of directors of more than 20 companies.

In the past few decades, Rekhi has been a tireless supporter and benefactor to Michigan Tech. He developed and funded the Rekhi Innovation Challenge a crowdfunding competition to help promote and support student innovation. He provided major funding for the Silicon Valley Experience, an immersive tour during spring break of San Francisco area companies that includes meetings with entrepreneurs and Michigan Tech alumni, and is a sponsor of the 14 Floors Entrepreneur Alumni Mentoring Sessions.

“Kanwal and his accomplishments epitomize the values we share as an institution. His passion for Michigan Tech is unparalleled and he is most deserving of this award,” said Rick Koubek, President.

While the Melvin Calvin Medal of Distinction is Michigan Tech’s highest honor, it is far from the first recognition the University has given Rekhi. He has received the Distinguished Alumni Award, the Board of Control Silver Medal, an honorary Doctorate in Business and Engineering, and was inducted into the Electrical Engineering Academy.

Additionally, every student who has walked the Michigan Tech campus in the past 15 years has passed the Kanwal and Ann Rekhi Computer Science Hall, dedicated in April of 2005.

The Melvin Calvin Medal of Distinction is bestowed on individuals associated with the University who have exhibited especially distinguished professional and personal accomplishments. It is named for 1931 Michigan Tech alumnus Melvin Calvin, who won the Nobel Prize in Chemistry for unraveling the biochemical secrets of photosynthesis. The series of biochemical reactions Calvin identified is known as the Calvin Cycle.

CEE’s Zhen Liu Is PI of $689K Dept. of Transportation R-D Contract

Zhen Liu

Associate Professor Zhen Liu, Civil and Environmental Engineering, is the principal investigator on a project that has received a $689,239 research and development contract from the U.S. Department of Transportation, Federal Highway Administration.

Liu is a member of the ICC’s Center for Cyber-Physical Systems.

The project is titled, “Autonomous Winter Road Maintenance Decision Making Enabled by Boosting Existing Transportation Data Infrastructure with Deep and Reinforcement Learning.”

Yongchao Yang (ME-EM), Tim Colling (CEE) and Michael Billmire (MTRI) are Co-PI’s on this three-year project.

College of Computing Welcomes Six New Faculty Members

The Michigan Tech College of Computing welcomed six new faculty members this fall to the Departments of Applied Computing and Computer Science.

College off Computing Dean Adrienne Minerick says the new hires reflect the fast growth of the new College, which was launched July 1, 2019.

“We are thrilled to welcome these six talented new faculty members,” Minerick says. “Even amid the challenges we are all facing, our proactive recruitment and retention activities are making a difference.”

Assistant Professor Briana Bettin, Computer Science, has a Ph.D. in computer science from Michigan Tech. She is also an affiliated assistant professor for the Cognitive and Learning Sciences department. Bettin’s research interests include user experience; human factors; human-computer interactions; mental models; information representation; rural digital literacy; education, engagement, and retention; and digital anthropology. Bettin is a member of the ICC’s Computing Education Center.

Assistant Professor Sidike Paheding, Applied Computing, has a Ph.D. in electrical engineering from University of Dayton, Ohio. Prior to joining Michigan Tech Paheding was a visiting assistant professor at Purdue University Northwest. His research interests include image/video processing, machine learning, deep learning, computer vision, and remote sensing. Paheding is a member of the ICC’s Center for Data Sciences.

Assistant Professor Junqiao Qiu, Computer Science, has a Ph.D. in computer science and engineering from University of California Riverside. His research focuses on parallel computing, programming systems, and compiler optimization. Qiu is a member of the ICC’s Center for Scalable Architectures and Systems.

Assistant Professor Ashraf Saleem, Applied Computing, has a Ph.D. in mechatronics engineering from DeMontfort University, UK. He comes to Michigan Tech from the electrical and computer engineering department at Sultan Qaboos University, where he served the mechatronics engineering program. Ashraf will be on campus starting in the spring 2021 semester.

Saleem’s research interests are in autonomous systems, vision-based unmanned vehicles, Artificial Intelligence, control of Piezoelectric actuator, and servo-pneumatic systems.

Assistant Professor Leo Ureel, Computer Science, has a Ph.D. in computer science from Michigan Tech. He has been teaching at the college level for 10 years, and has over 20 years of industry experience. Ureel is also coordinator of the College of Computing Learning Center. Ureel is a member of the ICC’s Computing Education Center.

Ureel’s research focuses on a constructionist approach to introductory computer science that leverages code critiquers to motivate students to learn computer programming. His areas of expertise include software engineering, computer science education, and intelligent tutoring systems.

Assistant Professor Brian Yuan, Applied Computing and Computer Science, has a Ph.D. in computer science from University of Florida. His areas of expertise include machine learning, security and privacy, and cloud computing. Yuan is a member of the ICC’s Center for Cybersecurity and Center for Data Sciences.

Paper by Yakov Nekrich Accepted for ACM-SIAM SODA21 Symposium

A paper by Associate Professor Yakov Nekrich, Computer Science, has been accepted for the 61st ACM-SIAM Symposium on Discrete Algorithms 2021 (SODA21), which will take place virtually January 10-13, 2021.

Nekrich is sole author of the accepted article, “New Data Structures for Orthogonal Range Reporting and Range Minima Queries.” An extended version of the paper is available for download on ArXiv.

The annual ACM-SIAM Symposium on Discrete Algorithms (SODA) is an academic conference in the fields of algorithm design and discrete mathematics. It is considered among the top conferences for research in algorithms.


Paper Abstract

In this paper we present new data structures for two extensively studied variants of the orthogonal range searching problem.
First, we describe a data structure that supports two-dimensional orthogonal range minima queries in O(n) space and O(logεn) time, where n is the number of points in the data structure and ε is an arbitrarily small positive constant. Previously known linear-space solutions for this problem require O(log1+εn) (Chazelle, 1988) or O(lognloglogn) time (Farzan et al., 2012). A modification of our data structure uses space O(nloglogn) and supports range minima queries in time O(loglogn). Both results can be extended to support three-dimensional five-sided reporting queries.

Next, we turn to the four-dimensional orthogonal range reporting problem and present a data structure that answers queries in optimal O(logn/loglogn+k) time, where k is the number of points in the answer. This is the first data structure that achieves the optimal query time for this problem. Our results are obtained by exploiting the properties of three-dimensional shallow cuttings.


The Society for Industrial and Applied Mathematics (SIAM) is an international community of 14,500+ individual members. Almost 500 academic, manufacturing, research and development, service and consulting organizations, government, and military organizations worldwide are institutional members.

What Lies Ahead: Cooperative, Data-Driven Automated Driving

Kuilin Zhang

Associate Professor Kuilin Zhang, Civil and Environmental Engineering and affiliated associate professor, Computer Science, was featured in a recent article on Michigan Tech News. The article appears below. Link to the original article here.


By Kelley Christensen, September 28, 2020.

Networked data-driven vehicles can adapt to road hazards at longer range, increasing safety and preventing slowdowns.

Vehicle manufacturers offer smart features such as lane and braking assist to aid drivers in hazardous situations when human reflexes may not be fast enough. But most options only provide immediate benefits to a single vehicle. What if entire groups of vehicles could respond? What if instead of responding solely to the vehicle immediately in front of us, our cars reacted proactively to events happening hundreds of meters ahead?

What if, like a murmuration of starlings, our cars and trucks moved cooperatively on the road in response to each vehicle’s environmental sensors, reacting as a group to lessen traffic jams and protect the humans inside?

This question forms the basis of Kuilin Zhang’s National Science Foundation CAREER Award research. Zhang, an associate professor of civil and environmental engineering at Michigan Technological University, has published “A distributionally robust stochastic optimization-based model predictive control with distributionally robust chance constraints for cooperative adaptive cruise control under uncertain traffic conditions” in the journal Transportation Research Part B: Methodological.

The paper is coauthored with Shuaidong Zhao ’19, now a senior quantitative analyst at National Grid, where he continues to conduct research on the interdependency between smart grid and electric vehicle transportation systems.

Vehicle Platoons Operate in Sync

Creating vehicle systems adept at avoiding traffic accidents is an exercise in proving Newton’s First Law: An object in motion remains so unless acted on by an external force. Without much warning of what’s ahead, car accidents are more likely because drivers don’t have enough time to react. So what stops the car? A collision with another car or obstacle — causing injuries, damage and in the worst case, fatalities.

But cars communicating vehicle-to-vehicle can calculate possible obstacles in the road at increasing distances — and their synchronous reactions can prevent traffic jams and car accidents.

“On the freeway, one bad decision propagates other bad decisions. If we can consider what’s happening 300 meters in front of us, it can really improve road safety. It reduces congestion and accidents.”Kuilin Zhang

Zhang’s research asks how vehicles connect to other vehicles, how those vehicles make decisions together based on data from the driving environment and how to integrate disparate observations into a network.

Zhang and Zhao created a data-driven, optimization-based control model for a “platoon” of automated vehicles driving cooperatively under uncertain traffic conditions. Their model, based on the concept of forecasting the forecasts of others, uses streaming data from the modeled vehicles to predict the driving states (accelerating, decelerating or stopped) of preceding platoon vehicles. The predictions are integrated into real-time, machine-learning controllers that provide onboard sensed data. For these automated vehicles, data from controllers across the platoon become resources for cooperative decision-making. 

CAREER Award 

Kuilin Zhang won an NSF CAREER Award in 2019 for research on connected, autonomous vehicles and predictive modeling

Proving-Grounds Ready

The next phase of Zhang’s CAREER Award-supported research is to test the model’s simulations using actual connected, autonomous vehicles. Among the locations well-suited to this kind of testing is Michigan Tech’s Keweenaw Research Center, a proving ground for autonomous vehicles, with expertise in unpredictable environments.

Ground truthing the model will enable data-driven, predictive controllers to consider all kinds of hazards vehicles might encounter while driving and create a safer, more certain future for everyone sharing the road.

Tomorrow Needs Mobility

Michigan Technological University is a public research university, home to more than 7,000 students from 54 countries. Founded in 1885, the University offers more than 120 undergraduate and graduate degree programs in science and technology, engineering, forestry, business and economics, health professions, humanities, mathematics, and social sciences. Our campus in Michigan’s Upper Peninsula overlooks the Keweenaw Waterway and is just a few miles from Lake Superior.

Kuilin Zhang

About the Researcher: Kuilin Zhang

  • Data-driven optimization and control models for connected and automated vehicles (CAVs)
  • Big traffic data analytics using machine learning
  • Mobile and crowd sensing of dynamic traffic systems
  • Dynamic network equilibrium and optimization
  • Modeling and simulation of large-scale complex systems
  • Freight logistics and supply chain systems
  • Impact of plug-in electric vehicles to smart grid and transportation network systems
  • Interdependency and resiliency of large-scale networked infrastructure systems
  • Vehicular Ad-hoc Networks (VANETs)
  • Smart Cities
  • Cyber-Physical Systems