Umit Sarilar and Sarah Moore, recent IMSE grads, were awarded Experienced Industrial Engineer 2016 and Industrial Engineer Tech 2016.
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.
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).
Event is open to All.
Local Food inspection company looking for a recent IE grad to be Day Shift production manager
Undergrad students preferred…December 2016 or May 2017 graduates ONLY
Has to be able to work in the US without sponsorship
MUST be fluent in both English & Spanish
Contact Kye Luker at firstname.lastname@example.org
Dissimilarity Plots: A Visual Exploration Tool for Partitional Clustering
Date: Monday, February 13, 2017
Time: 1:15 p.m. – 2:15 p.m.
Location: Nedderman Hall Room 106
Abstract: Cluster analysis tries to uncover structure in data by assigning each object in the data set to a group (called cluster) so that objects from the same cluster are more similar to each other than to objects from other clusters. Exploring the cluster structure and assessing the quality of the cluster solution have been a research topic since the invention of cluster analysis. This is especially important since all popular cluster algorithms produce a clustering even for data without a “cluster” structure. Many visualization techniques to judging the quality of a clustering and to explore the cluster structure were developed, but they all suffer from certain restrictions. For example, dendrograms cannot be used for non-hierarchical partitions, silhouette plots provide only a diagnostic tool without the ability to explore structure, data dimensionality may render projection-based methods less useful, and graph-based representations hide the internal structure of clusters. In this talk we introduce a new visualization technique called dissimilarity plots which is based on solving the combinatorial optimization problem of seriation for (near) optimal cluster and object placement in matrix shading. Dissimilarity plots are not affected by data dimensionality, allow the user to directly judge cluster quality by visually analyzing the micro-structure within clusters, while they make misspecification of the used number of clusters instantly apparent. Dissimilarity plots are implemented in the R extension package seriation.
Biographical Sketch: Dr. Michael Hahsler is assistant professor of Engineering Management, Information, and Systems (EMIS), Lyle School of Engineering, Southern Methodist University (SMU). He also holds a courtesy appointment with the Department of Computer Science and Engineering, and an adjunct appointment with the Department of Clinical Sciences at UT Southwestern Medical Center. He received his Ph.D. in business informatics from the Vienna University of Economics and Business, Austria, where he worked as an assistant professor and core researcher at the Research Institute for Computational Methods. Dr. Hahsler’s research focuses on methods used in the interdisciplinary field of data science including data mining, data visualization, data streams and combinatorial optimization with applications in bioinformatics, healthcare analytics, quantitative marketing, earth sciences and other engineering disciplines. He has published more than 60 papers in peer-reviewed international journals and conference proceedings and has organized several workshops. He also currently serves as editor of the Journal of Statistical Software, the secretary of the INFORMS Data Mining Section and is the principal developer of several popular data mining related extension packages for R, a free software environment for statistical computing and graphics.
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.
The spring Engineering Career Fair is approaching!
Tuesday, February 21
10 a.m.-3 p.m.
Maverick Activities Center
Dress professionally, bring your résumé, and come prepared to speak to potential future employers!
Carole Coleman will present a RÉSUMÉ WORKSHOP (Wednesday, February 8, 12-1 p.m., NH 105) and an INTERVIEW WORKSHOP (Wednesday, February 15, 12-1 p.m., NH 105) to help you prepare.
In addition, this year the list of companies scheduled to attend is fully online and available on mobile devices. It is filterable by major, type of job, and citizenship status and will be updated often. This will allow you to plan your visit to the career fair and learn more about the companies you want to work for, even as you’re standing in line at the event.
Find the list of companies at uta.engineering/career.
A separate event for job-seekers, UTA’s All-Majors Job Fair, is scheduled for the following day, Wednesday, February 22, from 10 a.m.-3 p.m. in the MAC.