Dr. Dongqing Wang to present Seminar

Dr. Dongqing Wang from Qingdao University in Qingdao, China will present at the first Seminar of the semester Wednesday September 6 at 2:00pm in Room 114 for the W. A. Baker Chemistry Research Building (CRB). Dr. Wang’s presentation title, abstract, and biographical sketch are below.

Title: Block-oriented Nonlinear System Identification—-Standard Least Square Methods and Least Square Methods for a Block-Oriented System
Author: Dr. Dongqing Wang
Picture2011-DQ WangLocation: W. A. Baker Chemistry Research Building (CRB) Room 114
Date: Wednesday, September 6
Time: 2:00pm – 3:00pm

Abstract: System parameter identification has been a significant research topic due to its wide application in fault diagnosis, signal processing, process control and economic fields. In this presentation, the standard least squares (LS) method is first introduced. Secondly, least squares methods for block-oriented systems is introduced, including the over-parametrization based least squares (OP-LS) method, the hierarchical least squares (H-LS) method and the key term separation principle based least squares (KT-LS) method. The mentioned methods are applied to Hammerstein systems, Wiener systems, and Hammerstein-Wiener systems. Finally, the future research proposal is given related to the compressive sensing based identification methods. The main contributions are the proposed framework of the hierarchical least squares based identification method for block-oriented systems by using the hierarchical identification principle, and the presented auxiliary model based key term separation principle based least squares for block-oriented systems.

Biographical Sketch: Dr. Dongqing Wang was born in Shenyang, Liaoning Province, China. She received B.S. and M.S. degrees from the Department of Electrical Engineering, Shandong University (Jinan, China) in 1986 and 1988, respectively. She joined the College of Automation Engineering, Qingdao University (Qingdao, China) as a faculty member since 1988. During work with Qingdao University, she received her Ph.D. degree from the School of Electrical Engineering and Automation, Tianjin University (Tianjin, China) in 2006. She was a Visiting Scholar in the Department of Electrical and Computer Engineering at the University of Tennessee (Knoxville, USA) from August 2004 to February 2005. Since December 2010, she has been a Full Professor in the College of Automation Engineering at Qingdao University, Qingdao, China. Her current research interests include process modeling and control, system identification, parameter estimation, Robot Path Planning, and Wireless Power Transfer. She has published over 50 papers on modeling and identification as the first author. She has won 5 research awards from the Chinese government and best paper award from the European Association for Signal Processing as the first author, she received more than ten funded projects from the NSF of China government and industrial field as a PI. She is a Recipient of Special government allowances of the State Council. She was ranked as the 2nd tier professor by the Ministry of Education in P.R China.


Dr. Chanhaeng Rhee to present Seminar

Dr. Chanhaeng Rhee from the University of Texas Southwestern Medical Center in Dallas will present at the Seminar Monday April 24 at 1:15pm in Nedderman Hall 106. Dr. Rhee’s presentation title, abstract, and biographical sketch are below. 

Title: Improving Health Outcomes through Systems Engineering

Author: Dr. Chanhaeng Rhee

Location: Nedderman Hall Room 106
Date: Monday, April 24
Time: 1:15pm – 2:15pm

Abstract: In 2000 and 2001, the Institute of Medicine (IOM) issued two reports, “To Err Is Human” and “Crossing the Quality Chasm”. The first report estimated systems failures in healthcare delivery were responsible for at least 98,000 deaths each year. The second report revealed a wide “chasm” between the quality of care the health system should be capable of delivering today. In 2005, National Academy of Engineering and Institute of Medicine issued a report “Building a Better Delivery System: a New Engineering/Health Care Partnership”. This report was to provide a framework and action for a systems approach to healthcare delivery based on a partnership between engineers and health care professionals. I would like to demonstrate 2 cases of use of systems engineering tools to improve patient cares in the hospital (“Viewing Prevention of Catheter-Associated Urinary Tract Infection as a System: Using Systems Engineering and Human Factors Engineering in a Quality Improvement Project in an Academic Medical Center”) and outpatient setting (“Sustainable Self-Management & Elevating Wellness for Persons with Diabetes through Optimizing the Chronic Care Model”).

Biographical Sketch: Dr. Chanhaeng Rhee is an Endocrinology Specialist in Dallas, Texas. He graduated from Boston University with a BS in chemistry in 1992, from Kyungpook National University College of Medicine with an MD in 2000 and from UT Dallas with an MBA in 2012. He completed his residency at St. Elizabeth Health Center in 2004 in internal medicine and a fellowship at the University of Texas Southwestern Medical Center in 2007 in endocrinology and metabolism. Dr. Rhee is a Medical Director for Diabetes Management Program at UT Southwestern Medical Center and a Quality Officer at UT Southwestern Medical Center. Dr. Rhee affiliates with many hospitals including  William P. Clements Jr. University Hospital, Zale Lipshy University Hospital,  Parkland Health and Hospital System, and cooperates with other doctors and specialists in the medical group at UT Southwestern Medical Center in Dallas. He is a member of the American Diabetes Association, the Endocrine Society, the American Association of Clinical Endocrinologists, the Texas Medical Association, and the Dallas County Medical Society.

Speaker Seminar -This Thursday

Chen Kan from the Department of Industrial and Manufacturing Systems Engineering at Pennsylvania State University will present a Seminar this Thursday, April 7, at 1:30pm in the Rady Room, Nedderman Hall (NH) 601.  Mr. Kan’s presentation title, abstract, and biographical sketch are below.


All students and faculty are encouraged to attend. Because this is a Thursday seminar, there will be no attendance sheet for GTAs and on-campus GRAs. However, there will be a student meeting on Friday at which attendance will be recorded. More on the student meeting is forthcoming.

Chen Kan -1

Author: Chen Kan

Title: Dynamic Network Modeling and Analysis of Large-scale Internet of Things with Manufacturing and Healthcare Applications

Location: Rady Room, NH 601

Date: Thursday, April 6

Time: 1:30pm – 2:50pm


Abstract: Rapid advancement of sensing technology brings the proliferation of high-dimensional data with complex structures. Realizing full potentials of sensing data depends on the development of new sensor-based methods and tools for process monitoring and control, as well as data-driven system optimization. However, the complexity of sensing data poses significant challenges: 1) Distributed sensing leads to multi-channel signals, which show high levels of nonlinear and nonstationary behaviors in the presence of extraneous noises. 2) Advanced imaging technology leads to 2-D, 3-D or higher dimensional functional images (i.e., dynamic and time-varying), which contain rich information about the underlying processes. 3) Internet of Things connects large amounts of machines in digital manufacturing, as well as human subjects in smart and connected health. This gives rise to big and networked data that call for next-generation methodologies for system informatics and control. The goal of my research is to develop innovative sensor-based methodologies for modeling, monitoring and optimization of large-scale complex systems. Specifically, my research focuses on the development of nonlinear and stochastic network models for process monitoring and control. This research will enable and assist in 1) the handling of massive, complex data generated from advanced sensing systems in manufacturing and healthcare settings; 2) the extraction of pertinent information about system dynamics; and 3) the exploitation of acquired knowledge for decision making and performance optimization.


Biographical Sketch: Chen Kan is currently a Ph.D. candidate in the Department of Industrial and Manufacturing Engineering, the Pennsylvania State University. His research focuses on wireless sensing systems and network theory for large-scale IOT-based monitoring, modeling and control of complex systems, with applications for advanced manufacturing and smart health. He was the Entrepreneurial Lead of NSF I-Corps Team of the Mobile E-network Smart Health (MESH) project in 2014. He has published multiple papers in top journals, including Journal of Manufacturing Systems, Quality and Reliability Engineering International, Computers in Biology and Medicine, IEEE Journal of Biomedical and Health Informatics, and IEEE Transactions on Automation Science and Engineering.

Alumni Win Awards at Americold

 Umit Sarilar and Sarah Moore, recent IMSE grads, were awarded Experienced Industrial Engineer 2016 and Industrial Engineer Tech 2016.

Both of the students gained experience through their Capstone Class and Senior Design Project.
“It was a great year for UTA graduates in Americold and I wanted to say thank you again for helping me to initiate that senior design project last year.” Umit Sarilar
Congratulations to you both!

Seminar Series: Guest Speaker Thursday 3/30

Dr.  Caroline Krejci from the Department of Industrial and Manufacturing Systems Engineering at Iowa State University will present a Seminar this Thursday, March 30, at 1:30pm in the Engineering Research Building (ERB) 228.  Dr. Krejci’s presentation title, abstract, and biographical sketch are below.

All students and faculty are encouraged to attend.

Author: Dr. Caroline Krejci
Title: Evaluating Sociotechnical Systems Using Agent-Based Modeling
Location: Engineering Research Building (ERB) 228
Date: Thursday, March 30
Time: 1:30pm – 2:50pm

Abstract: Mathematical modeling is often used to optimize or gain a better understanding of the behavior of sociotechnical systems (e.g., supply chains, production systems).  However, such models typically ignore or make unrealistic assumptions about the behavior of a system’s human participants, which can limit model validity.  By contrast, agent-based modeling (ABM) is a computational modeling method that allows the human actors and/or organizations in sociotechnical systems to be modeled as autonomous and intelligent agents.  These agents can be programmed with empirically valid human characteristics and capabilities, including bounded rationality, social skills, and the ability to adapt and learn from accumulated experience and system feedback.  Over time, individual agent decisions, interactions, and adaptations may yield emergent system-level behaviors of interest, which are observable via ABM outputs.  ABM can also be combined with other modeling methods, such as discrete-event simulation, GIS, and building energy simulators.  These hybrid simulation models enable the integration of a variety of useful nonsocial system properties (e.g., queueing behavior) into an ABM.

This presentation will describe several novel approaches to sociotechnical system modeling using ABM and hybrid simulation.  The attributes, preferences, and decision-making processes of the agents in these models are empirically informed, using data that was collected via interviews, surveys, and experiments.  The resulting models have been used to provide strategic decision support to participants and stakeholders in regional food supply chains, humanitarian relief chains, urban communities, and production systems.

Biographical Sketch: Dr. Caroline Krejci is an Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering at Iowa State University.  She worked as an industrial engineer for UPS and as an operations engineer for Lutron Electronics before earning a Ph.D. in Industrial Engineering from the University of Washington in 2013.  Dr. Krejci’s research interests are focused on the development of quantitative methodologies for the analysis and management of sociotechnical systems.  She specializes in modeling supply networks as complex adaptive systems, which enables the realistic representation of network participants as autonomous and heterogeneous agents that are capable of complex planning, decision making, interactions, and adaptations in a dynamic environment.  Such complex systems often exhibit unpredictable and nonlinear behavior, which can be captured through the use of agent-based modeling techniques.  Dr. Krejci is particularly interested in using these techniques to explore the implications of different management policies on long-term social, environmental, and economic system sustainability.


Speaker Series Presentation- Monday 3/27

Dr. Ramtin Madani from the Department of Electrical Engineering from the University of Texas at Arlington will present at the Seminar Monday March 27 at 1:15pm in Nedderman Hall 106.  Dr. Madani’s presentation title, abstract, and biographical sketch are below.

All students and faculty are encouraged to attend. Attendance is expected for GTAs and on-campus GRAs. There will be signature sheets for GTA’s located in the room. Please sign in to note your attendance.

Author: Dr. Ramtin Madani
Title: Mathematical Programming Methods for Control and Optimization of Power Systems
Location: Nedderman Hall Room 106
Time: 1:15pm – 2:15pm

Abstract: This talk is concerned with the development of efficient computational methods for the design, operation and control of power systems. Due to difficulties such as the nonlinearity induced by laws of physics and binary parameters, several power system optimization problems cannot be solved based on a full model and have remained open for decades. Real-world approaches involve inherited approximations and heuristics, based on linearization and local search algorithms, that are believed to be costly and jeopardize the operation of the grid. We introduce a variety of graph-theoretic and penalized optimization techniques that facilitate performing fundamental, yet challenging optimization tasks such as the optimal power flow, state estimation and security constraint unit commitment. A novel method will be discussed for the classical problem of designing distributed controllers for stochastic systems with applications to renewable energy. Lastly, a distributed numerical algorithm with low-complex iterations is presented in order to address the need for solving large-scale conic optimization programs for power system applications. The goal is to develop the essential pieces for a powerful optimization and decision-making engine tailored for the modern grid requirements. The proposed techniques are simulated on real-world nationwide electrical systems.

Biographical Sketch: Ramtin Madani is an Assistant Professor with the Department of Electrical Engineering at the University of Texas at Arlington. He received the Ph.D. degree in electrical engineering from Columbia University in 2015 and was a postdoctoral scholar in the Department of Industrial Engineering and Operations Research at University of California, Berkeley in 2016. His research focuses on developing algorithms for optimization, control and design of real-world complex systems such as electric power grids. Ramtin Madani’s work has received the 2016 Best Publication Award in Energy from the Institute for Operations Research and the Management Sciences (INFORMS) Section on Energy, Natural Resources, and the Environment. His recent work has been a best paper finalist for the flagship conference of the Control Systems Society (53rd Annual Conference on Decision and Control).