Dr. Li Wang to Present Seminar

Dr. Li Wang from UT Arlington’s Math Department will present at the Seminar Monday February 26 at 1:15pm in Room 105 of Nedderman Hall.  Dr. Wang’s presentation title, abstract, and biographical sketch are below.

Title: Graph Structure Learning based on Reversed Graph Embedding
Author: Li Wang
Location: Nedderman Hall (NH) Room 105
Date: Monday, February 26
Time: 1:15pm – 2:15pm

Abstract:  Many scientific datasets are of high dimension, and the analysis usually requires retaining the most important structures of data. Many existing methods work only for data with structures that are mathematically formulated by curves, which is quite restrictive for real applications. To get more general graph structures, we develop a novel graph structure learning framework that captures the local information of the underlying graph structure based on reversed graph embedding. A new learning algorithm is developed that learns a set of principal points and a graph structure from data, simultaneously. Experimental results on various synthetic and real world datasets show that the proposed method can uncover the underlying structure correctly.

Biographical Sketch:  Dr. Li Wang is currently an assistant professor with Department of Mathematics, University of Texas at Arlington, Texas, USA. She worked as a research assistant professor with Department of Mathematics, Statistics, and Computer Science at University of Illinois at Chicago, Chicago, USA from 2015 to 2017. She worked as the Postdoctoral Fellow at University of Victoria, BC, Canada in 2015 and Brown University, USA, in 2014. She received her Ph.D. degree in Department of Mathematics at University of California, San Diego, USA, in 2014. She received the master degree in Computational Mathematics from Xi’an Jiaotong University, Shaanxi, China, in 2009 and the Bachelor degree in Information and Computing Science from China University of Mining and Technology, Jiangsu, China in 2006. Her research interests include data science, polynomial optimization and machine learning.

 

-Posted by Jay Rosenberger

Dr. Andrew Liou to Present Seminar at DFW INFORMS

Senior Vice President, Dr. Andrew Liou, from Foxconn will present at the DFW INFORMS Seminar on Thursday, February 15th, at 6:00 pm in Room 100, Nedderman Hall (NH).  Dr. Andrew Liou’s presentation title and biographical sketch are below.

DFW INFORMS will offer refreshments (pizza, soft drink & water). The room is open from 5:30 pm. All students and faculty are encouraged to attend.

Title: Transformation to an Industrial Internet Operation: A Foxconn Story
Author: Dr. Andrew Liou
Location: Nedderman Hall (NH) Room 100 (http://www.uta.edu/maps/?building=NH)
Date & Time: Thursday, February 15 @ 6:00 pm

Biographical Sketch:
Andrew Liou, Ph.D, P.E.
1979, Tunghai University, BS IE
1981-1986, Auburn University, MS IE and Ph.D
1986-2002, Cleveland State University, Assistant, Associate, Professor and Chairman of IE Department
Assistant Director, Advanced Manufacturing Center
Director, Productivity and Quality Center
1994-1996 (Sabbatical leave), Director of Quality, Black and Decker
2002-2008, CEO, Uniworld Consulting for more than 30 international companies
2008-2013, Vice President, Foxconn Industrial Engineering Academy
2013-current, Interim General Manager and Senior Vice President, Foxconn iPhone business group, for daily operations, automation and intelligent manufacturing

 

-Posted by Jay Rosenberger

Dr. Eli Olinick to Present Seminar

Dr. Eli Olinick from Southern Methodist University will present at the Seminar Monday February 12 at 1:15pm in Room 105 of Nedderman Hall. Dr. Olinick’s presentation title, abstract, and biographical sketch are below.

Title: Compact Multicommodity Flow Formulation with Applications to Vehicle Routing, Concurrent Flow, and Social Network Analysis
Author: Eli Olinick
Location: Nedderman Hall (NH) Room 105
Date: Monday, February 12
Time: 1:15pm – 2:15pm

Abstract: We present a compact mixed integer program (MIP) for the vehicle routing problem with optional pickup and delivery in which a freight carrier seeks to generate revenue from an empty delivery vehicle’s backhaul trip from its last scheduled delivery to its depot by allowing it to deviate from the least expensive (or fastest) route to accept delivery requests between intermediate points as allowed by its capacity and required return time. The MIP is inspired by a novel representation of multicommodity flow, the triples formulation, that significantly reduces the size of the constraint matrix and the linear programming upper bound on optimal profit compared to a formulation based on the classical node-arc representation. This in turn leads to faster solution times when using a state-of-the-art MIP solver. In an empirical study of both formulations, problem instances with ten potential pickup/dropoff locations (including the vehicle’s current location and its depot) were solved three to twelve times faster with our formulation while instances with 20 locations were solved 90 to 2,000 times faster. The largest instances in the study had 40 locations and 1,482 delivery requests; these instances could not be solved with the node-arc-based formulation, but were solved within an average of 90 minutes of CPU time using our compact formulation. We present a similar study applying the triples formulation to the notoriously difficulty maximum concurrent flow problem (MCFP), an optimization problem concerning the equitable use of resources in congested networks. In this study we found that the CPLEX linear programming solvers solved 89% of the MCFP instances in our computational study faster with the triples formulation than it did with the other two formulations, typically two to four times faster than the node-edge formulation when available computer memory allowed both to be solved. The triples formulation appears to be particularly well suited for problem instances defined on dense graphs; on average, CPLEX solved these types of problems in our study 10 times faster with the triples formulation. Finally, we propose a new clustering algorithm based on hierarchical maximum concurrent flow (HMCF) and its duality relation to the sequence of sparsest cuts, and discuss theoretical properties which make it more accurate and often more robust than many popular algorithms in the literature. We present a new measure of node centrality, determined from the HMCF, called flowthrough centrality, and empirical results comparing its improved stability relative to currently used centrality measurements employed in social network analysis when knowledge of the network topology is incomplete or in transition.

Biographical Sketch: Eli V. Olinick is an Associate Professor in the Department of Engineering Management, Information, and Systems at SMU’s Bobby B. Lyle School of Engineering. He completed his B.S. in Applied Mathematics (1989) at Brown University and earned his M.S. (1994) and Ph.D. (1999) in Industrial Engineering and Operations Research at the University of California at Berkeley. Professor Olinick’s research interests include applied optimization and network design problems. His research activities have been funded by multiple government and industry grants totaling over $1.6M, and he has published over 20 refereed research articles in prominent journals in operations research and network engineering. He is a past president of the INFORMS Technical Section on Telecommunications, the Dallas/Fort Worth INFORMS chapter, and an Associate Editor of Networks and Spatial Economics.

 

-Posted by Jay Rosenberger

Dr. Robert Schafrik to Present Seminar

Dr. Robert Schafrik from IMSE and the National Academy of Engineering will remotely present at the Seminar Wednesday February 7 at 1:15pm in Room 101 of College Hall (CH). Dr. Schafrik’s presentation title, abstract, biographical sketch, and a link to CH on the campus map are below.

Title: Materials for a Non-Steady State World 
Author: Robert Schafrik 
Location: College Hall (CH) Room 101
Date: Wednesday, February 7
Time: 1:15pm – 2:15pm

Abstract: Since antiquity, human society has greatly benefited from advancements in materials and processes, and anticipation for continued improvements are a cornerstone of societal progress in the modern world. Expectations for successful introduction of new products continue to rise non-linearly–implementation of the appropriate material solution is the key to success. This presents great challenges to the materials and manufacturing communities; the top challenges include:  increasing the speed of development; high reliability of the end product; exceeding expectation in product performance; and attractive value proposition for the supplier base and the end users. These challenges are being addressed by many technologists, including those in the aero engine community. The successful algorithm has three key elements: forward-looking strategy, development guided by senior design engineers, and partnership with the supply chain. A critical constituent of each element is nurturing the materials and manufacturing team to incorporate vision and creativity with expert knowledge. This presentation will discuss these elements with examples of how it was successfully employed. It will conclude with go-forward challenges.

Biographical Sketch: Robert E. Schafrik, Ph.D., NAE was elected to the National Academy of Engineering in 2013 for more than 40 years of innovation in materials for gas turbine engines. He retired as general manager of the Materials and Process Engineering Department at GE Aviation in 2014 after more than 16 years in the position. During his tenure he and his team reduced the development time for several new materials, including low rhenium turbine blade alloy, R65 (a high-temperature cast-and-wrought disk alloy), and titanium aluminide turbine blade alloy, and greatly expanded the use of composite applications in engines. He was hired in 1997 as a senior staff department engineer. From 1991-97, he staffed the National Research Council’s National Materials Advisory Board (NMAB) and Board on Manufacturing and Engineering Design (BMAED), following three years as vice president of research and development at Technology Assessment and Transfer, Inc. Schafrik spent 20 years on active duty in the U.S. Air Force before retiring as a lieutenant colonel in 1988. He served as chief of the Long-Term Planning Division with the Strategic Defense Initiative Organization (SDIO) at the Pentagon and, before that, as chief of the Air Superiority Division for the Headquarters Air Force Systems Command (AFSC) at Andrews Air Force Base. He chaired the NRC National Materials and Manufacturing Board and the External Advisory Committee for the Materials Science and Engineering Department at Ohio State University, and was a member of the Air Force Scientific Advisory Board. Schafrik earned his B.S. degree in metallurgy from Case Western Reserve University, an M.S. in aerospace engineering from the Air Force Institute of Technology, a second M.S. in information systems from George Mason University, and a Ph.D. in metallurgical engineering from Ohio State University.

 

-Posted by Jay Rosenberger