Industrial, Manufacturing, and Systems Engineering

The IMSE seminar is returning the Monday after Thanksgiving. Specifically, our own Ph.D. student Nahal Sakhavand is giving her dissertation defense as a seminar at noon on Monday, November 30 on Microsoft Teams.  Information and a link to Ms. Sakhavand’s presentation are below. 

All students and faculty are encouraged to attend.

Title: New Algorithms for Stochastic Power Systems Planning and Operations Problems 
Presenter: Nahal Sakhavand
Date: Monday, November 30, 2020
Time: noon

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Abstract: In this paper, we present a two-stage stochastic programming and simulation-based framework for tackling large-scale planning and operational problems that arise in power systems with significant renewable generation. Traditional algorithms such as the L-shaped method used to solve the sample average approximation of the true problem suffer from computational difficulties when the number of scenarios or the size of the subproblem increases. To address this, we summarize a cutting plane method that uses sampling internally within optimization to select only a random subset of subproblems to solve in any iteration.  In addition, we present a demonstration of the design and analysis of computer experiments approach (DACE) to the stochastic unit commitment-economic dispatch problem. We use a multivariate adaptive regression splines algorithm to approximate the second stage of the problem with an endeavor to provide more computationally tractable solutions over the traditional L-shaped method. We conduct the experiments on a modified IEEE118 test system and assess the quality of the solutions obtained from both the DACE and L-shaped method in a replicated procedure. The results obtained from this approach attest to the significant improvement in the computational performance over the L-shaped method. 

Biographical Sketch: Nahal Sakhavand is a Ph.D. candidate in the Industrial, Manufacturing, and Systems Engineering department at UTA. She received her M.S. in Operations Research from SMU and in Industrial Engineering from UTA. She holds a B.S in Applied Mathematics from the National University of Iran and in Industrial Engineering from the University of Tehran North branch. Her research interests are in large-scale stochastic optimization, data analytics, statistical modeling, and their applications. 

IMSE’s Center on Stochastic Modeling, Optimization, & Statistics (COSMOS) has posted advice for schools and businesses that are hoping to reopen.  The advice uses their key contact partitioning questionnaire and includes a reference to Pro Bono Analytics planning assistance offered by the Institute for Operations Research and the Management Sciences (INFORMS).  In the U.S., compliance with CDC guidance on social precautions has been inconsistent.  Knowing which individuals are COVID-19 key contacts can enable schools, businesses, and other organizations to focus their efforts on protecting those that are at higher risk for severe illness.  The majority of children and younger adults will be low-risk themselves, but the challenge of the novel coronavirus is pre-symptomatic and asymptomatic spread, so it must be conservatively assumed that low-risk individuals can spread the virus without knowing it.  The U.S. does not have sufficient COVID-19 testing to mitigate this spread.  By specifically adhering to protective precautions around key contact individuals, the population at higher risk can be protected, reducing cases of severe illness and ultimately controlling the fatality rate.  Further, the COSMOS key contact partitioning approach does not rely on total compliance by the broader U.S. population.

Check out the COSMOS COVID-19 project page: https://cosmos.uta.edu/projects/covid-19/. 

Reopening is possible with careful planning and commitment.  For example, COSMOS Director Victoria Chen has been impressed with the reopening by Texas Dreams Gymnastics, where her sons are competitive gymnasts on the boys’ team.  Texas Dreams is owned by World Champion Kim Zmeskal and her husband Chris Burdette.  The boys’ coaching team is led by Japanese Olympian Norimasa Iwai and includes NCAA Pommel Horse Champion Michael Reid.  The coaches and any spectators wear masks, temperature checks are conducted at the door, and everyone is instructed to maintain social distancing, with the measurement help of 6-foot tall coach Alex Wright.  Team practice sessions are carefully scheduled in small groups that rotate through the facility and are supplemented by online training sessions at home.  Each gymnast has their own chalk and hand sanitizer, which they use between turns on equipment.  The equipment is also cleaned between rotations.  When not on the gym floor, such as entering and departing the gym, everyone is required to wear a mask.  Dr. Chen’s sons and coaches Michael, Alex, and Kim can be seen wearing masks in the photos.  Currently, the gym is occupied from 7:00 AM to 10:00 PM to maintain low occupancy levels, but when school begins, practices will need to be outside of school hours, potentially increasing occupancy levels.  COSMOS reopening advice has been shared with Texas Dreams, as they re-organize their schedule for the school year.

IMSE’s Center on Stochastic Modeling, Optimization, & Statistics (COSMOS) has developed a COVID-19 online tool, called COSMOS COVID-19 Linear Programming (CC19LP), to assist county-level decision-makers in planning the reopening of their communities.  The CC19LP tool allows decision-makers to explore the two primary conflicting objectives, namely (1) maintaining a low COVID-19 fatality rate and (2) enabling recovery of the U.S. economy via reopening.  The recent rise in COVID-19 cases due to reopening, despite significant increases in contact tracing efforts, has created urgency in finding alternate approaches to controlling the impact of the pandemic in the U.S.  Other than contact tracing, the major control policy that decision-makers have implemented in the U.S. is the complete lockdown of communities.  While the lockdown policy can successfully lower the fatality rate, it is severely detrimental to the U.S. economy, and subsequently does not achieve balance in the two objectives.  Reopening strategies were specified to alleviate stress on the economy, but no quantitative analysis was employed to confirm that communities were prepared to reopen.  Simply imploring with the U.S. public to be responsible has not worked, and non-compliance continues to be a major issue.

CC19LP employs a key contact partitioning structure that focuses compliance on a smaller percentage of the population that has direct connections with individuals that are at higher risk for severe illness.  COSMOS researchers have created a questionnaire to assist individuals in identifying if they are a key contact.  Finally, COSMOS Director Victoria Chen posted a 15-minute podcast with the Institute for Operations Research and the Management Sciences (INFORMS) that motivates the development of CC19LP.  This podcast, the key contact partitioning questionnaire, and the CC19LP online tool are all accessible from the COSMOS COVID-19 project page: https://cosmos.uta.edu/projects/covid-19/.

Dr. G. Don Taylor is a distinguished alumni here at UTA, having received both M.S and B.S degrees for the IMSE department. Dr. G. Don Taylor is now Vice Provost for Learning Systems Innovation and Effectiveness, and Charles O. Gordon Professor in ISE at Virginia Tech. He is also a Fellow and a Past-President and Member of the Board of Trustees of the Institute of Industrial and Systems Engineers (IISE).

Amongst many accomplishments, Dr. G. Don Taylor has served as Principal Investigator or Co-Principal Investigator on more than 60 externally funded projects. His research has led to the publication of 10 edited books, more than 75 journal articles and book chapters, more than 120 conference papers and technical reports.

Our own Dr. Yuan Zhou will present at the IMSE seminar on Monday, April 29, 2019 at 1:00pm in Nedderman Hall, Room 105. Please note that this seminar is in the usual room, but we are moving the time up 15 minutes to accommodate faculty schedules. Dr. Zhou’s presentation title, abstract, and biographical sketch are below. 

Title: Modeling Complex Adaptive Systems: Agent-Based Simulation and Its Applications
Author: Yuan Zhou
Location: Nedderman Hall Room 105
Date: Monday, April 29, 2019
Time: 1:00pm 

Abstract: Modeling the behavior of complex adaptive systems, such as infectious disease transmissions and policing systems, plays an important role in management decision-making towards improving systems’ performance. However, it is often challenged by inherent complexities of the underlying systems: nonlinear interactions in between systems’ entities (e.g., contacts between humans), entities’ adaptive behaviors (e.g., criminals’ response to policing actions and other environmental factors), and dependent happenings of certain events (e.g., parent-offspring disease transmissions). Traditionally, equation-based models, such as differential equations and Markov models, have been used to represent the average system behavior, but they usually fail to capture those complexities appropriately. In recent years, agent-based simulation (ABS) has received growing attentions because it enables realistic representations of systems’ complexities at a micro-level. ABS is a class of computational models that is built upon the unique behaviors of individual entities, or agents, who are interacting with each other, autonomously making decisions, and collectively driving the macro-level behavior of the system. In this talk, we will discuss several projects involving ABS modeling in healthcare systems, policing systems, and traffic systems. Our goal is to address some critical issues in design and implementation of ABS models, including model granularity, data needs, and model validation, and provide some strategies to overcome these issues. 

Bio: Yuan Zhou is an Assistant Professor of Department of Industrial, Manufacturing and Systems Engineering at The University of Texas at Arlington. She received a B.S. degree in Mechanical and Electrical Engineering from Beijing Institute of Technology, Beijing, China and a Ph.D. degree in Industrial and Systems Engineering from The University at Buffalo, Buffalo, NY. Dr. Zhou’s primary research interests include healthcare delivery systems engineering, agent-based simulation, infectious disease modeling and policy development, health data analytics, and dynamic policing decision analytics. Currently, she is also working with local healthcare and law enforcement partners to develop analytical tools to support their management decision making and improve operations performance.

AT&T Professor Mario Beruvides from the Whitacre College of Engineering’s Industrial, Manufacturing & Systems Engineering Department at Texas Tech University will present at the IMSE seminar on Wednesday, April 24, 2019 at 1:15pm in Nedderman Hall, Room 106.

Title: Systems Dynamics and its Role in Industrial & Engineering Management Research: A look at Minsky’s Financial Instability Hypothesis & Technology Diffusion Curves
Author: Mario Beruvides
Location: Nedderman Hall Room 106
Date: Wednesday, April 24, 2019
Time: 1:15pm

Abstract: The role of the industrial engineer has always been deeply entrenched in the analysis of industrial and social technical systems.  Systems theory and its off-shoot, systems dynamics, is a critical development encompassing a revolutionary theory of how we look at complex systems as well as how to model, analyze and ultimately practice industrial engineering knowledge.  In this talk, comprised of two parts – a look at Minsky’s Instability Hypothesis and Technology Diffusion curves, the speaker will provide some insights into the changing role of industrial engineering when addressing complex technical system.  With respect to the analysis of the Minsky Instability Hypothesis, the research analyzed eleven financial debt ratios related to the level of debt associated to the U.S. households, nonfinancial and financial businesses. The validation process utilized nonparametric statistical analysis of Page and binomial tests to provide statistical evidences that supported the validity of FIH. This confirmatory research found evidence to suggest FIH concepts were indeed applicable to the 1945-1980s era and remains relevant to the 1990-2017 periods.  In analyzing technology diffusion curves, the research looks at the potential of classifying and developing an economic procedure to optimize entrance and exit strategies for organizations with respect to their technology portfolios.

Bio: Mario Beruvides, Ph.D., P.E., is an AT&T Professor at Texas Tech University in the Whitacre College of Engineering’s Industrial, Manufacturing & Systems Engineering Department.  His current research interests include: Management of Technology, Engineering Management, Knowledge work Performance, Measurement, Production and Quality Systems Engineering, and Advanced Economic Analysis.  Dr. Beruvides has a Ph.D. in Industrial Engineering from the Virginia Polytechnic Institute and State University, a M.S. in Industrial Engineering from the University of Miami, and a B.S. in Mechanical Engineering from the University of Miami.

Assistant Professor Leili Shahriyari from the Department of Mathematics will present at the IMSE seminar on today, April 15, 2019 at 1:15pm in Nedderman Hall, Room 105. Dr. Shahriyari’s presentation title, abstract, and biographical sketch are below.

Title: Data-Driven Models for Discovery of Effective Personalized Cancer Treatments

Author: Leili Shahriyari
Location: Nedderman Hall Room 105
Date: Monday, April 15, 2019
Time: 1:15pm

Abstract: Carcinogenesis is a complex stochastic evolutionary process. One of the key components of this process is evolving tumors, which interact with and manipulate their surrounding microenvironment in a dynamic spatio-temporal manner. Recently, several computational models have been developed to investigate such a complex phenomenon and to find potential therapeutic targets. In this talk, we present novel computational models to gain some insight about the evolutionary dynamics of cancer. Furthermore, we propose an innovative framework to systematically employ a combination of mathematical methods and bioinformatics techniques to arrive at unique personalized targeted therapies for cancer patients.

Bio: Leili has a Ph.D. degree in Mathematics and an M.S.E. degree in Computer Science from Johns Hopkins University (JHU). She studied Computer Science with a specific focus machine learning (ML) and data science, and Mathematics with focus on differential geometry. She conducted her first postdoctoral training in computational biology at the University of California Irvine (UCI). At UCI, she developed stochastic models to improve our understanding of cell dynamics during tumorigenesis and improved an artificial neural network model for obtaining gene regulatory networks. During her second postdoctoral training, as an NSF/MBI funded postdoc fellow at the Mathematical Biosciences Institute (MBI), she pursued an independent research program and established collaboration with biologists, physicians, and mathematicians. She is currently an assistant professor of Data Science at the University of Texas at Arlington, where she has been awarded STARs grant. Her lab, currently with three PhD, one Master, and four Undergraduate students, develops innovative frameworks to systematically employ a combination of machine learning and statistical methods as well as mathematical techniques to arrive at unique personalized therapies.

Dr. Zeyi Sun from the Department of Engineering Management and Systems Engineering from Missouri University of Science and Technology will present at the IMSE seminar on Monday, March 25, 2019 at 1:15pm in Nedderman Hall, Room 105. Dr. Sun’s presentation title, abstract, and biographical sketch are below

Title: Interdisciplinary Fellowship Program in Engineering

Abstract: Missouri University of Science and Technology (Missouri S&T) is inviting students to apply for Ph.D. program in engineering management, systems engineering, or civil engineering and become GAANN fellows to conduct cutting-edge research on various aspects of infrastructure studies, including resilience, safety, sustainability, connectivity, and smartness, to name a few.
The primary objective of this proposed GAANN program is to increase the number of U.S. PhD scholars in engineering management and systems engineering – areas identified as a national need by the Department of Education. The GAANN Fellows will assume educational and leadership roles, particularly in advancing new methodologies for infrastructure studies. Rebuilding infrastructure to allow Americans to build their lives on top of the best infrastructure in the world is a national need.
GAANN faculties and the academic advisors provide academic support and research mentoring to the selected GAANN fellows. Mentored teaching experiences (e.g., teaching one undergraduate course as an instructor for two semesters) are provided. Up to $34,000 fellowship stipend is offered annually depending on financial need (decided by FAFSA). In addition, up to $15,750 education allowance is offered annually to cover tuition, research related expense, and travel.
Without losing generality, three research thrusts by Dr. Zeyi Sun in the relevant areas are briefly introduced. The first one is biofuel supply chain infrastructure restructuring to accommodate the switch from first generation biofuel manufacturing (corn grain based) to second generation biofuel manufacturing (corn stover based). Various infrastructure deployment strategies have been investigated. Both economic viability and environmental sustainability have been systematically examined and compared. The second one is the design and control of distributed generation system (microgrid) with renewable energy sources for manufacturing end use customers towards cost effectiveness and environmental sustainability. A neural network integrated Q-learning algorithm is proposed to identify the optimal control strategies for both microgrid and manufacturing plant to reduce the overall energy consumption cost without sacrificing production throughput. The third one is the integration of aggregated electric vehicles (EVs) in smart grid for frequency regulation. Gradient-based reinforcement learning algorithm is being investigated to identify the optimal control policy with respect to the energy flow between the EVs and grid considering the benefits and interests from both the EV owners and grid operator.

Biographical Sketch: Dr. Zeyi Sun obtained his PhD degree in Industrial Engineering and Operations Research from the University of Illinois at Chicago in 2015. His research interest is complex system integration towards sustainability. His current research thrusts include: 1) integration of onsite generation systems with renewable energy sources into manufacturing operations; 2) integration of electric vehicles as a source for frequency regulation in smart grid; and 3) biofuel supply design and restructuring to accommodate second generation biofuel manufacturing. He teaches two undergraduate courses, i.e., Operations and Production Management (required), and Industrial Systems Simulation (selected) at Missouri S&T. He has graduated two M.S. students and is currently mentoring one M.S. student and three Ph.D. students.

Dr. Sridhar Nerur, a Professor of Goolsby-Virginia and Paul Dorman Endowed Chair in Leadership at the University of Texas at Arlington will present a seminar on March 18 at 1:15pm in Nedderman Hall 105.

Title: Understanding Your Research Domain: Drawing Insights from Bibliometrics and Text Analysis
Author: Professor Sridhar Nerur
Location: Nedderman Hall Room 105
Date: Monday, March 18, 2019
Time: 1:15pm

Abstract: Scholars strive to extend the intellectual boundaries of their discipline by “standing on the shoulders of giants”. The first step in pursuing good research, therefore, is to have a good grasp of what has already been accomplished and what challenges remain. Regrettably, it takes an enormous amount of time and effort to sift through a discipline’s extensive corpora to understand the extant cumulative research traditions and the opportunities they afford for future research. Bibliometric tools that rely on citations and text mining algorithms that exploit the lexical structure of articles are increasingly being used to quickly unravel latent themes in large corpora. The purpose of this presentation is to demonstrate how such tools can accelerate the literature review process and provide insight that would otherwise take months of effort.

Biographical Sketch: Sridhar Nerur is currently Professor of Goolsby-Virginia  and Paul Dorman Endowed Chair in Leadership at the University of Texas at Arlington. As Chair of the Graduate Studies Committee on Business Analytics, he has been actively involved in updating the curriculum to ensure that it is consistent with industry practices. His research has been published in the MIS Quarterly, Strategic Management Journal, Communications of the ACM, Communications of the AIS, The DATA BASE for Advances in Information Systems, European Journal of Information Systems, Information Systems Management, Information & Management, IEEE Software, and the Journal of International Business Studies. He has served as an associate editor of the European Journal of Information Systems, and was on the editorial board of the Journal of AIS until December 2016. His research and teaching interests include social networks, machine learning/AI, text analytics, self-organizing systems, and neuroeconomics.

It’s never too late to celebrate our graduates! We want to congratulate all our students who graduated in the Fall 2018 semester.

Undergraduates:
Abell, David
Acharya, Nayan
Allen, Robert
Aper, Courtney
Biju Vallappilly, Athul
Boradia, Kunj Jayesh
Carneiro Leon, Virgilio
Dhakal, Alisha
Franciamone, Hang
Guajardo-Caballero, Eduardo
Gupta, Lalit
Hamdy, Mirage
Hasan, Tonni
Mahmood, Jamal
Mudgett, Ian
Pass, Elizabeth
Rodriguez, Aaron
Shafi, Mohammed
Shakergayen, Venugopal
Tabe, Gderrick

Masters:
Adeshara, Maharshi Bharatkumar
Ali, Olabisi
Alungal Kamal, Sharukh
Baste, Mohit
Batra, Vineet
Borkar, Shivani
Champaneriya, Viraj Vijaykumar
Dalal, Deep
Devaraj, Pranesh
Dhage, Aditya Shankar
Doshi, Kush Sukumar
Fashafsha, Raji
Garud, Kedar Kiran
George, Julian
Gonzalez, Joana
Gopalakrishnan, Harikailash
Griffin, Nickolas
Guddi, Parth Yogindra
Harikrishnan, Rahul
Iyyamperumal, Ramkumar
Jadhav, Swati Jayantilal
Kapoor, Ankit
Khaja, Firasath Uddin Ahmed
Khisti, Omkar Subodh
Kolla, Goutam
Lad, Rohit
Lee, Hao-Wei
Mahadevan, Vivek
Mahalingam, Anandhi
Manoharan, Thamizhvanan
Medina, Eric
Mishra, Rajkumar
Modiyil, Hemant
Mulla, Safwan Riyazahmed
Muneer, Mohammed Areeb
Palanikumar, Shanmuga
Pandey, Rakshit
Pandey, Vivek Shriprakash
Pareek, Abhishek
Pasumpon, Vishnupraveen
Patel, Harshkumar Maheshkumar
Pathak, Vishesh Jayesh
Ponnamparambil, Akhil Das
Quintero, Maryuri
Radhakrishnan, Aravindakshan
Rukari, Aniket Vaijnath
Sethu, Rajesh
Shah, Parth
Shah, Parth Pareshkumar
Sharma, Manish
Sheth, Nishil
Shukla, Madhav
Siingh, Rishabh
Sukjaijaroenporn, Supannee
Talanikar, Ketaki
Venugopal Srinivasakumar, Prasanthnithin
Xu, YanYan
Yadav, Gaurav Harish

Doctoral:
Banakar, Zahra
Haque, Khan MD

Below are a couple of photos of our graduates. You can view video of the commencement ceremony here: https://www.uta.edu/commencement/photos-videos/2018-december/engineering.php.