Getting Math Off the Ground: Applied Mathematics at Boeing
Thomas Grandine (The Boeing Company) /
Boeing's applied mathematics group works with engineers on the design and manufacture of Boeing products, conducts applied research and development, and does consulting and software development for non-Boeing customers. This talk describes the types of problems and applications we deal with and the mathematical disciplines and other skills which are important. It also deals with the special constraints that arise in an industrial setting and outlines some considerations of importance for a mathematician contemplating an industrial career.

How one mathematician ended up at Google
Geoff Davis (Google) /
Three experiences I had in graduate school turned out to be surprisingly important for my ending up at Google. I'll describe them, discuss what I learned, and explain why it mattered. I'll also suggest some similar things someone interested in an industry career might try.

IBM Research - Thinking Out of the Blue
Lior Horesh (IBM) /
We will begin with an introduction to the mission, milestones and strategy of the largest industrial research institute in the world. Later, a more personal perspective regarding the parallels and differentiators of industrial vs. academic research environment will be glanced. Lastly, we will go through few case studies, in which we shall witness how the universality of mathematical skills will bridge across a broad spectrum of real life problems.

Research, Development, and Engineering in Industry: Issues and Opportunities for Mathematicians and Scientists
Tariq Samad (Honeywell) /
I have been with Honeywell for almost thirty years, always in R&D organizations but with substantial interactions with other functions, especially in the last decade or so. As a Corporate Fellow in the company, my current responsibilities include oversight of university relationships, leadership of our Fellows community, and engagement with research associations, government agencies, and other external organizations. I will offer some remarks based on my experience, focusing on topics such as how research, development, and engineering is performed in industry, how value chains and development processes affect technology transfer, how and why industries and companies differ in their research horizons, and why realizing effective industry-university cooperation is often so difficult. I will also give a brief overview of Honeywell and its businesses, discussing the industries the company serves and the scientific and technological disciplines relevant to each. Examples from past and present projects and collaborations will also be presented. I hope to leave the audience with a sense of the importance of science and mathematics to many companies as well as an awareness of the challenges that scientists and mathematicians seeking to work with industry must overcome.

Mathematics in Electric Energy
Hyoseop Lee (Encored Technologies) /
In this presentation, we will talk about mathematics in electricity market. Unlike the conventional practice in this market such as economic power dispatch, optimal control for renewables and national-wide demand forecasting, we approach the industry not from the supplier’s viewpoint but from the customer’s perspective. Our service is founded on the disaggregation technology: the estimation of electricity consumption of each appliance from total consumption. It is modeled via a combinatorial optimization problem or the hidden Markov model. The disaggregation problem is interesting as it is, but it is even more useful if it is exploited as an input for another problems. Prediction of total electricity usage through each appliance’s power usage model and optimal operation strategy under a budget constraint for individual appliance are examples of the problems. In addition to such power usage analysis for individual appliance, we also analyze electricity consumer’s price sensitivity especially for each appliance, and it is utilized in the demand-response market.

A Mathematical Career in the Pharmaceutical Industry
Andrew Stein (Novartis Institute for Biomedical Research) /
This talk will begin with an overview of my career path as an engineer who became a mathematician and then joined a pharmaceutical company where I support drug candidate selection, dose optimization, and clinical trial design. There will be a brief overview of the drug industry, a discussion of tradeoffs between academia and industry, and a case study where a mathematical model was used to help identify the optimal dose of Afinitor in patients with metastatic renal cell carcinoma. The talk will conclude with a historical example from NASA demonstrating the importance of good communication and guidelines for how to communicate effectively in industry.

Panel: Industry-Academic partnerships
Richard Braun (University of Delaware / IMA) / Thomas Grandine (The Boeing Company) / Carlos Tolmasky (University of Minnesota, Twin Cities / IMA) / Bogdan Vernescu (Worcester Polytechnic Institute) /
This panel will present activity in several kinds of partnerships. These include short term efforts such as 10-day graduate student workshops and week-long industrial study groups, industrial postdoctoral fellowships, institutes housing collaborative projects, and regular industrial seminars. Resources for information about these partnerships including possible involvement will be given. Discussion and questions will be encouraged.

Mathematics of Networks and Systems at Bell Labs, Alcatel-Lucent
Iraj Saniee (Alcatel-Lucent Technologies Bell Laboratories) /
After an overview of the current Bell Labs research organization, I'll talk about the Mathematics of Networks and Systems center and how the math organization works both as 1) a research entity and also as 2) an integral part of Alcatel-Lucent, contributing to new products and services. I'll finish with a summary of my recent work on graph analytics, some of its implications, both as a new research direction and also how we are leveraging it for new initiatives within the emerging ALU services.

Panel: Academic Programs
Ali Nadim (Claremont Graduate University) / Fadil Santosa (University of Minnesota, Twin Cities / IMA) / Bogdan Vernescu (Worcester Polytechnic Institute) /
Building an academic program to educate future industrial scientists presents plenty of challenges. Examples of existing programs will be discussed by three leading academics. Different models for courses and degree programs, as well as descriptions of workshops and activities, will be presented. Discussion and questions will be encouraged.

What Scientists Bring to our Industry?
Benoit Couet (Schlumberger-Doll) /
This talk will first give some background on Schlumberger, a large company with a relatively low profile. It will show why science and technology is critical for our industry and provide some topics of interest for applied mathematicians in that context. A specific problem will be presented in more detail to illustrate the need for mathematicians. Finally, we will conclude with an emphasis on what makes a good scientist/mathematician within our organization with some suggestions for potential candidates who may consider working in our industry.

A Mathematical Route to Data Science
Richard Sharp (Globys) /
A typical path to the data science industry starts in a computer science department, but mathematicians have a lot to offer. I will discuss my current work at Globys, Inc. a Seattle based contextual marketing firm. I began my career as a student of numerical analysis and will describe how I have adapted this experience to pursue a career in the data science industry.

The Mathematics of High Value Solutions
Sumanth Swaminathan (W. L. Gore & Associates) /
At a glance, Industrial Mathematics at W.L. Gore & Associates is a tool for advancing understanding of Materials through physical modeling and engineering type calculations. Given the complexity of Gore’s fluoropolymer based materials, one may argue that a purely empirical approach to correlating product performance and material structure would take a seemingly infinite amount of time without the aid of modeling efforts. In this talk, we will highlight the efficacy of studying industrial product performance through mathematical modeling. Moreover, we will discuss how applied mathematicians have a rare combination of analytical skills that gives them an advantage in delivering important, highly valued solutions.

My Career Path in the Pharmaceutical Industry – Trajectory and Work
Jeffrey Saltzman (AstraZeneca) /
I am often questioned by both laymen and professionals about “… what exactly do I do in pharmaceuticals? …”. Of course in recent times colleagues and students in applied mathematics have more exposure to the life sciences and the resulting questions are more refined “… do you work in genomics, cheminformatics, pharmacometrics…?”. In this talk I summarize my career path both prior and during my tenure within the pharmaceutical industry. Next, I will present a few postcards or vignettes of technical work carried out by a mathematician in a company such as AstraZeneca or Merck. At the end of the talk the listener should have a better idea of “what exactly do I do in pharmaceuticals? …”.​

Mathematics: A Key Partner in Industrial Problem Solving
Genetha Gray (Intel Corporation) /
Even if it is not specifically listed on a job posting, most industrial jobs require some knowledge of mathematics. There are very few problems examined that would not benefit from mathematical expertise. In this talk, I will describe the training that I underwent in order to make myself a valuable partner in industrial problem-solving activities. I will also give a brief overview of the wide range of projects of which I have been involved including applications from biology, engineering, energy, and environmental science. I will also describe how this experience has led me to my current position as a data scientist in the human resources department.

Theory and Practice of Neural Networks for Deep Machine Learning
Wonsuk Lee (Samsung Electronics) /
Neural Networks for Deep Machine Learning moved from a small community of academic researchers to a wide spectrum of developers and engineers who are building products with them. However neural networks and machine learning is not yet an magical blackbox nor a toolbox that companies can easily use to make meaningful products. Though, many leading IT companies around world are investing sizable resources to advance the related technologies. In this case study, we discuss a glimpse of the theoretical and practical knowledge of neural networks - machine learning (especially deep learning) and discuss why leading IT companies are keenly interested in the technologies.

Panel: Impact of Mathematicians in Industry
Albert Gilg (Siemens) / Michael Ray (ExxonMobil) / Daniel Reich (Ford Motor Company) / Jeffrey Saltzman (AstraZeneca) / Hyunmi Yang (GSMA) /
Experiences, example projects and outlook from mathematicians in industrial positions will be presented. Discussion and questions will be encouraged.

How Mathematics Will Support the Next $1 Trillion of Growth in the Mobile Ecosystem
Hyunmi Yang (GSMA) /
The mobile ecosystem is forecast to grow by $1.1 trillion between 2012 and 2020 driven by network technology evolution, smartphone penetration and service innovation. Dr. Hyunmi Yang will explain how mathematics is a fundamental enabler for growth at each stage of the mobile telecoms value chain – from designing networks to using data analytics underpinning new business models – and how her background in Applied Mathematics led her to become the first female ICT executive in Korea and now Chief Strategy Officer of the GSMA, the association for the global telecoms industry.

Vortex Flow Reconstruction using Ultrasound
Kiwan Jeon (NIMS) /
Vortex flow imaging has recently been proposed as a new medical imaging modality for cardiac functional assessment. It is based on the velocity computation of intra-ventricular blood flow fields. In this project, we propose a new method to restore the blood flow velocity fields inside left ventricle (LV) using Doppler echocardiography. For the successful reconstruction of the velocity fields, there are several challenging issues mathematically. In this talk, we talk about what we did and discuss about our next issues in the project.

How I Ended up Working at a Real Estate Startup
Laura Lurati (Redfin) /
This talk will be about my transition to Redfin, a real estate startup, from Boeing, an aerospace corporation. I will discuss the challenges of changing jobs and answer the question "What exactly does a mathematician do at a real estate company?" This talk will compare and contrast the experience of working at large company versus a small one, as well as a few of the skills I have found useful for both.

Some Impacts of Mathematics in a Big Industry
Albert Gilg (Siemens) /
Interaction of industry with academia as well as roles and impact of mathematicians in industry is very diverse in particular with respect to company organization structure and culture. And there are even several more business and personal characteristics beyond academic curricula that strongly affect a mathematicians non-academic career. Selected from personal experience this talk discusses these key factors and viewpoints along three industrial mathematics topics: Engineering simulation approaches and progress of academic theory of differential-algebraic equations and their industrial application in microelectronics. Followed by two areas still at evolving stages: Optimization in engineering with increasing impact of robustness and uncertainty. And finally, challenges and first mathematical approaches for the transition form mechatronic products to cyber-physical systems.

Panel: Internship programs and success stories
Thomas Grandine (The Boeing Company) / Ali Nadim (Claremont Graduate University) / Fadil Santosa (University of Minnesota, Twin Cities / IMA) / Sumanth Swaminathan (W. L. Gore & Associates) / Bogdan Vernescu (Worcester Polytechnic Institute) /
Internships are valuable to both student and also potential employers. However, matching needs from both sides can be tricky. Panelists from both academia and industry will describe their experiences as far as running a successful internship program. Discussion and questions will be encouraged.

Scheduling Destructive Tests on Expensive Resources
Daniel Reich (Ford Motor Company) /
Ford’s Safety organization performs crash tests on prototype vehicles at multiple planning phases of each new vehicle program. These tests ensure the vehicles meet all government and company requirements by the time the vehicles reach the production phase. However, crash tests are quite expensive to perform due to the high cost of prototype vehicles compared with that of production vehicles. Accordingly, improvements in scheduling that reduce the number of prototypes crashed yield a significant cost savings. This scheduling problem has many sources of complexity: varying deadlines, precedence relationships between tests, incompatibilities in vehicle specs required, etc. Currently, engineers spend weeks of time manually planning the crash schedule for each new vehicle program and coordinating with all the other prototype vehicle users. We are developing an automated system for crash test planning that both minimizes the resources needed and significantly reduces the time engineers spend planning.