USF Industrial and Management Systems Engineering Impulse Magazine - Fall 2019

Industrial and Management Systems Engineering

Annual News Magazine

In this Issue:

Issue 5 — Fall 2019

Emergency Medicine Benefits from Real-Time Data

Page 4

Cyber Physical Infrastructure for Shared Autonomous Electric Vehicles Using Engineering to Build Wealth

Page 6

Page 13

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Message from the IMSE Chair Dear Alumni, Friends, and Students, In 2015 IMSE faculty won the “Innovation in Curriculum

IISE. Our congratulations and sincere appreciation for the

Award” from IISE for the revised BSIE curriculum that

leadership and community engagement of our students at

was put in place in Fall 2013. Rapid evolution of the

all levels.

marketplace has once again set IMSE faculty in motion We are proud that we have added two

for another major curriculum restructuring effort. The goal is to

new faculty to our ranks: Dr. Jamie

further realign BSIE curriculum with

Chilton, PhD in Bioengineering from

the fast evolving needs of the data

Georgia Tech and Dr. Ankit Shah,

driven economy. The driving force

PhD in Information Technology and

for the change is that our graduates

Cyber Security from George Mason

must understand engineering to

University.

solve problems that arise from manufacturing and service systems,

Finally, I would be remiss if I didn’t

while also being experts in being

remind you how much we depend

able to extract knowledge from

on your gifts to implement new ideas

big data through modeling and

for student success. In 2019 fall, we

computing. We already have a

have implemented a new program

four course analytics sequence

“Interns Present Competition,” which is

(programming, data bases, and a

designed to bring out the best from our students’ internship experiences.

two course analytics sequence) in our curriculum that is required for all. We plan to further strengthen the knowledge of computing and data security.

I wish you the best of success and happiness in your profession and family.

Our master’s programs Master of Science in Engineering Management (MSEM) and Master of Science in Industrial Engineering (MSIE)) continue to thrive. We have also expanded the data science and computing training for

Most sincerely,

Tapas K. Das Professor and Chair

our master’s degree seeking students. Our goal is to further strengthen those in line with the enhancements we seek for our BSIE program.

Our Ph.D. student cohort continues to be as productive and engaged as ever. Among many other achievements in the last year, they have contributed a significant

To donate to the IMSE Annual Fund, please go to the following website: http://www.usf.edu/engineering/ imse/give-to-imse/

number of very high quality peer reviewed papers to the literature. The INFORMS student chapter once again received the Summa Cum Laude award from INFORMS in 2019 (sixth in the last nine years). Our IISE student chapter also received the highest “Gold Award” from 2

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JOIN HERE http://bit.ly/2zLkUdA

Introducing New IMSE Faculty Dr. Ankit Shah IMSE department is most delighted to welcome Dr. Ankit Shah as a new faculty who brings expertise in analysis and design of cybersecure systems. He received a B.S. degree in computer science from Florida Atlantic University, Boca Raton, FL, in 2001, an M.S. degree in operations research from George Mason University, Fairfax, VA, in 2016, and an interdisciplinary Ph.D. degree in information technology from George Mason University, Fairfax, VA, in 2019. His specific research interests include cybersecurity analytics, decision-making under uncertainty, combinatorial optimization, stochastic dynamic programming, adversarial machine learning, and deep reinforcement learning. He has authored or coauthored ten articles in refereed journals and conference proceedings (IEEE, ACM, and Springer) and three book chapters in the application area of cybersecurity.

He has served as a reviewer for security conferences and a session chair for security analytics at the INFORMS optimization 2018 conference. He was invited as a panelist at the AAAI 2019 workshop on artificial intelligence for cybersecurity. He is serving as a program committee member for the military applications track at the Winter Simulation Conference 2019. He has been invited for more than twelve technical talks and seminars by government organizations, industry partners, and conferences.

Dr. Jamie Chilton Jamie Chilton, PhD, received her BA in Biochemistry and Molecular Biology (2000) from Agnes Scott College, while also minoring in Mathematics and completing the requirements for Agnes Scott’s Business Prep Program. Dr. Chilton holds a PhD in Biomedical Engineering (2008), a joint program between Georgia Institute of Technology and Emory University’s School of Medicine. At Georgia Tech, she also earned her certificate in Engineering Entrepreneurship and won 2nd place with her team in Georgia Tech’s 2005 Business Plan Competition. Dr. Chilton has over 10 years of experience in a variety of research, technology, business, teaching and consulting roles in higher education and private industry, particularly in biotechnology. Her previous work in the biotech industry includes developing innovative cell culture systems for disease modeling, drug discovery and toxicity studies for customers ranging from academia and government to large biotech and pharmaceutical companies. Dr. Chilton has published in the Journal of Clinical Investigation, Nature Methods, Journal of Biotechnology, and Biotechnology and Applied Biochemistry. Her teaching interests include engineering and change management, creativity, and technology-based entrepreneurship. Her broader research interests include engineering management, healthcare engineering and security, and education engineering.

Dr. Chilton is very happy to be back in her home state of Florida and enjoying the Tampa Bay life with her husband.

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Featured Faculty Research

Dr. Devashish Das (right) with his research colleagues from Mayo Clinic.

Emergency Medicine Benefits from Real-Time Data

By Randy Fillmore

I

mproving health care has been a goal throughout the

in patients with traumatic injuries,” says Das. “Our

first decade of the 21st century. New technologies

goal is to enhance the physiological understanding

and improving the patient database through electronic

of hemorrhage, which can lead to better trauma care

medical records have played a big role. But more

practices.”

needs to be done. Hospital emergency departments (EDs) want to increase their patient flow efficiency to

The development of non-invasive sensors has rapidly

help provide optimal patient care. First responders

changed medical practice related to monitoring

and ED physicians want to be able to better control

blood hemoglobin, the molecule that carries oxygen

hemorrhage in trauma patients and optimize blood

through the body. Two such sensors are the SpHb that

transfusions.

monitors hemoglobin levels without drawing blood and the Compensitory Reserve Indicator (CRI) that

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Devashish Das, Assistant Professor of IMSE, and

measure blood loss volume. Both provide valuable,

colleagues, have been working on these two critical

real-time information about trauma patients. However,

issues and developing novel ways to use data-driven

the understanding of these signals is limited, and we

models to enhance and improve emergency medical

do not know how to use them for deciding blood

care and, ultimately, save lives.

transfusion dosages, Das explains.

“Hemorrhage is a major cause of preventable death

According to Das, the application of stochastic

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modeling and machine learning methods are

enhance Emergency Department (ED) efficiency

often limited in these sensors because of a lack

and improve the quality of emergency medical

of computing resources in portable devices; this

care by monitoring patient flow. Because the

is especially true for biomedical devices that

increasing use of EDs not only increases the

require need vast amounts of real-time data.

national health care expenditure, but can also affect and diminish the quality of emergency

“Continuous measurement from these

service, researchers are aiming at improving the

noninvasive sensors is not yet part of standard

efficiency and quality of service by developing a

trauma care,” he says. “We have devices that

scheme to optimize ED staffing and, at the same

clip over the finger and use light signals to

time, reduce patient wait time and length of

measure how much hemoglobin is in the blood.

patient stays.

We can also measure the volume of hemoglobin.

However, if someone has lost a large volume

“Most emergency departments in the U.S. are

of blood, that reduces the amount of oxygen in

overburdened by surging patient volumes,”

the blood. In the past, to determine hemoglobin

explains Das, whose research involved a case

amounts one would have to send a blood

study at the Mayo Clinic’s ED. “Improved

sample to the lab, and then get a number back to

efficiency is important.”

determine whether a patient needs a transfusion.

Ideally, it would be better to have real-time

Das and his team initiated a case study and

information that automatically starts a transfusion

introduced and evaluated a Statistical Process

when needed.”

Control (SPC) scheme to detect delays in service and slow-down in patient-flow. “The real-time

Research being carried out by Das and

monitoring scheme provides a continuous

colleagues is aimed at identifying hemoglobin

performance measure,” explains Das. “It can

and CRI dynamics in real-time and developing

identify patterns of inefficiency or delays-

methods to predict mortality risk by using

in-service that are difficult to detect using

compressed sensing algorithms and transmitting

traditional monitoring algorithms. This method

hemoglobin and CRI signals to a cloud

may offer a practical approach for monitoring

computing platform.

service systems and determining when staffing levels need to be re-optimized.”

“This model could produce a graph that shows clinicians hemoglobin levels over time,” explains Das. “Ideally, it could inform clinicians of when to start or stop a blood transfusion. In future, this technology could start a transfusion automatically.”

In another project involving emergency medicine, Das and colleagues at the Mayo Clinic in Rochester, Minnesota are helping to Impulse

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Cyber Physical Infrastructure for Shared Autonomous Electric Vehicles

By Randy Fillmore “Ride-sharing service providers in cities and the suburbs

answers. For example, what are the optimal locations for

may soon begin to replace human-driven cars with fleets

multiple charging hubs across the city to accommodate

of shared, autonomous electric vehicles, or SAEVs,” says

perhaps 10,000 vehicles? What is the potential strain on

Tapas Das, IMSE professor and chair. “This transformation

the power network during charging? How can we balance

will demand fleet operators make optimal real-time

quantity and timing of charging of the vehicles with the

decisions regarding controlling operations of the vehicles

transportation needs? How do we benefit from selling

as well as the smart hubs for charging/discharging of

stored energy in the batteries back to the grid when the

the vehicles. Our research is aimed at facilitating the

price is high?

impending convergence of electricity and transportation by transforming the city transportation systems to be smart,

“One model aims at reducing the cost of fleet operation by

autonomous, and connected.”

optimizing hub infrastructure cost, the cost of electricity consumption, revenue for energy sharing, passenger ride

Das and his faculty colleagues and partners from the City

revenue, revenue from renting hub charging spots when

of Tampa and the Tampa Electric Company (TECO) are

not in use, and looks at the benefits of load balancing and

collaborating to develop a three-tier modeling approach to

reduction in price spikes in the power network,” explains

support the above transformation. The bottom tier model

Chang Kwon, Associate Professor of IMSE.

assesses projected passenger travel needs and demands on the SAEV fleet; the middle tier model considers electric

Because a “team approach” is at the foundation of taking

power networks and their constraints to find optimal

on and solving these issues, experts from the City of Tampa

location and sizing of the smart hubs; the top tier model

and TECO are participating. Their expertise is crucial, says

obtains the optimal operational strategy for the SAEV fleet

Das, and they are working as investigators alongside the

including plans for optimal charging of the vehicles based

academic team members.

on varying price of electricity and exploitation of arbitrage opportunities for the energy stored in the vehicles.

“The City of Tampa works towards an efficient, sustainable transportation system,” says Vik Bhide, Smart Mobility

The team is addressing several practical questions needing 6

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Division Manager with the City of Tampa. “The strength of

this team is that the private and public sectors are working

For Hernandez and TECO, the charging hub locations and

with the assistance of academia. The academics are the

their clustering, and their potential impact on the local

‘brains’ that can evaluate what might work and what might electric grid, and possible variable pricing for recharging not.”

hubs, are important to consider now. “We are helping to develop a market that we don’t yet fully understand

Bhide sees a day, albeit perhaps a decade or more away,

and continues to evolve, but we want to be prepared to

when the majority of cars on the road will be electric,

address the needs of the market in any growth scenario.”

automated and shared, with access to transportation

he says.

services being more important to society than individual ownership. “Mobility is changing right before our eyes,”

Also a partner in this effort is the Tampa Bay Smart City

says Bhide. “Our roadways are failing to meet travel

Alliance (https://tbsmartcities.com/) initiated by the City

demand. One solution is to have more people using

of Tampa, Florida Department of Transportation District 7,

shared, high-occupancy transportation, and the City

and the Center for Urban Transportation Research (CUTR)

of Tampa‘s main interest is to identify the best ways to

at the University of South Florida.

facilitate smart mobility hubs.”

Team member Michael Maness, assistant professor in Kenneth Hernandez, whose role at TECO is in

Civil and Environmental Engineering and CUTR, sees

business development and modernization for electric

wide public benefit in SAEVs, and not just for ride-sharing

transportation, says that TECO’s involvement in the SAEV

commuters or younger people who don’t want to own

project comes with a shared interest with USF and IMSE

cars. “I think SAEVs can improve mobility for a wide

researchers.

range of people,” says Maness, whose research covers travel behaviors. “For example, older people with night

“USF has been a great partner over the years,” says

vision issues or other driving difficulties can benefit

Hernandez. “We’re excited to work with the brilliant

by ride-sharing.” According to Maness, the benefits of

minds at USF to help us to prepare for and leverage the

SAEVs extend to increasing vehicle occupancy rates thus

big changes that will come with this new technology so

reducing people’s carbon footprint and potentially fewer

that, as shared mobility increases, we can continue to

accidents caused by impaired and distracted driving.

provide safe, reliable, affordable energy to this new market segment. We want to do it right, and do it equitably across our service territory.”

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“Let’s Make a Deal!”

By Randy Fillmore

“A fundamental problem in natural resource management is determining which sites or parcels of land within a geographical region should be protected in order to preserve biodiversity,” says Hadi Charkhgard, IMSE assistant professor. In the past he has worked with members of the U.S. Geological Survey (USGS) on natural resource conservation projects and is currently helping USGS on a project aimed at saving an endangered South Carolina coastal environment.

Charkhgard, who just received a two-year, $174, 985 National Science Foundation grant to help find solutions to problems involving natural resources, has offered his USGS partners a novel model to help protect the Cape Romain National Wildlife Refuge (NWR), a vast geographical area of barrier islands, salt and freshwater marshes, sea turtle and bird nesting beaches, and maritime forest, now at-risk because of sea-level rise (SLR) and rapidly expanding urban pressures.

To adapt to anticipated changes, USGS conservationists want to identify specific parcels of land within the NWR that will preserve a representative collection of habitat types in sufficient quantity

Dr. Hadi Charkhgard

to provision future ecosystem services. The approach to selecting which land parcels should be marked for protection is, for Charkhgard, a little like ‘making a deal’ with the important “players” in the environment (including species and conservationists) by “buying” and “selling” selected parcels to optimize conservations efforts.

“We are using the principles of Modern Portfolio Theory (MPT), which quantifies risk as the variance and correlation among assets, to formalize diversification as an explicit strategy for managing risk in a climate-driven reserve design,” he explains.

MPT is used to specify a framework evaluating multiple conservation objectives for plants and animals, and even for specific species, in

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23 distinct habitats. MPT allows decision makers to balance management benefits and risk when preferences are contested or unknown, and includes additional decision options such as parcel divestment when evaluating candidate reserve designs. “It is designed to make everyone happy,” says Charkhgard with a smile.

Their recent study, titled “Spatial conservation planning under uncertainty: adapting to climate change risks using modern portfolio theory,” was published in June 2019 as an e-pub in Ecological Applications.

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New Marketplace for New Transportation Models

By Randy Fillmore

N

ot only will autonomous

He suggests that future car dealers

vehicles (AVs) change how,

may become “Uberized,” with

when, and where we “drive,”

their own fleet of AVs, and possibly

they will also change the vehicle

get involved with setting up car

marketplace, says Changhyun Kwon,

sharing designs for co-owners or

Associate Professor of Industrial and

co-leasers. They may also operate

Management Systems Engineering.

charging hubs and orchestrate ride sharing operations, matching up

“As AVs arrive on the American

potential co-owners who need

highway scene in ever-greater

schedules that fit each of their

numbers, people will not only stop

needs in terms of the times of day

driving automobiles, they will also

they need vehicles.

likely stop being the sole owners or sole leasers of automobiles and opt

Dr. Changhyun Kwon

for vehicle sharing,” he projects.

“You may go to a Ford dealer and get a Ford Mustang for use Monday

through Friday from 8 am to 9 am, then need it again Kwon expects a paradigm shift in not only how

from 5 pm to 6 pm for the ride home,” speculates Kwon.

autonomous electric vehicles will affect how we get

“While you are at work, that same AV may travel to pick

where we are going, but also how the AVs will be

up a co-owner who is in sales and needs the car daily

made available in the market. “My focus is on creating

from 9:30 am until 4:30 pm.” Many other issues that the

and designing new markets for fractional ownership

new marketplace will need to work out include repairs,

of autonomous vehicles,” explains Kwon. “Fractional

insurance, and legal issues, says Kwon.

ownership, where vehicles will be owned by more than one person, may not be unlike having a time-share

On the “upside,” he expects the cost of individual

vacation condo.”

transportation will go down and convenience will rise.

“In some ways, changes for users may not be big,”

Kwon suspects the market will develop two new models

says Kwon. “But, as the use of AVs grows, the vehicle

matching owners who have ride-sharing compatible

marketplace will see enormous change.”

schedules and an auction to sort out co-ownership costs and usage patterns that are beneficial to co-owners.

He also acknowledges the cultural shift Americans will be faced with as individual car ownership eventually goes away. But finding ways to share AVs takes some thought, as well as ingenuity, and a bit of entrepreneurial risk on the part of car dealers.

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Celebrating the Academic Career of Dr. Paul Schnitzler A

fter 14 years with the IMSE Department in the College of Engineering, Dr. Paul Schnitzler will be embarking on a new venture of his career. Before joining

academia, he has served as an electrical engineer in the middle and upper management positions for well-known U.S. corporations. While there is much he will remember from his time at USF, Schnitzler believes that the following will stand out. He had the opportunity to work with an amazing group of colleagues. He found that the IMSE faculty are very smart people, but they are also caring individuals. They listen to each other and value constructive conflict. Schnitzler says that he has not found that in many groups that he had worked with. The backgrounds of IMSE faculty range widely and thus provide important contributions to departmental issues.

Dr. Paul Schnitzler

He was pleased to watch the department grow under this diverse influence. As per Schnitzler, students often can “replay” what they are taught but frequently have difficulty using it. He valued the opportunity to help young minds learn to use the content. In the process of teaching about change, Schnitzler discovered a problem that seems to have not been addressed: Why do change initiatives fail 70% of the time? He believes he found the solution and wrote the book “Lead Change without Fear.” He has been gratified by readers’ responses. Schnitzler fondly reminisces that had the opportunity to tell his stories to anyone who would listen!

Cindy Amor (Tampa Electric Company): Longest Serving IMSE Advisory Board member and Chair Retires “When I reflect on my time as Chair for the IMSE Advisory Board, it feels like yesterday when I accepted the position. Although, the efforts and achievements made by the group carry much more than a few moments of memories. I first took over as the AB chair 16 years ago. I wanted an opportunity to give back to my alma mater in a way that would have an impact on the students and my college. During my time as chair there have been three deans for the College of Engineering, two different IMSE Department Chairs and three ABET accreditations. The board has sponsored numerous events, such as guest lectures, mentoring and career panel sessions with students. I’m very proud of the work we have done over the past 16 years and will miss the interactions and opportunities to work with

Cindy Amor

the faculty, staff and students. Although, I will be continuing to assist the board as the Past Chair, it is difficult to move on from something I have valued and worked hard to sustain and develop. Moving forward, I know the Board will only continue to grow with Ms. Jana Iezzi’s leadership as the new Chair. I wish the IMSE Advisory Board, IMSE Department and all IMSE Students the best as we move into this new school year.”

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Students, Faculty, and Alumni at INFORMS Annual Meeting at Seattle, October 2019.

INFORMS Student Chapter at IMSE Organizes Annual Data Science Boot Camp This year this event took place on Saturday March 30 and Saturday April 6, 2019. More than 100 students from different engineering disciplines in the College of Engineering as well as from outside engineering departments joined the twoday-long workshop. The Bootcamp’s main objective was to transfer knowledge about the most used software in data analysis and optimization to the undergraduate students who are close to finishing their degrees. The 2019 Bootcamp focused on basics of programming, pre-processing, visualization, linear models, tree/ensemble models, text analytics, and neural networks. INFORMS@USF members volunteered to teach the sessions that included beginners, intermediate, and advanced classes, all of them highly synchronized. This year, the participants at the end of the Bootcamps were able to implement all the analytical techniques using the two most used analytics software: R and Python. The Data Science Boot Camp by INFORMS@USF has become a sought after event for students.

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Using Engineering to Build Wealth in the Financial Industry

By Brad Stager A financial services company might seem an unusual place for industrial engineers to work, but Laura Pradilla, BSIE, a USF alumna, has been using her data driven modeling skills to improve business at one of the world’s major investment banks and financial services companies.

After graduating in 2014, Laura Pradilla was hired as an operations analyst

Laura Pradilla

by the firm Goldman Sachs, which generated more than $36.6 billion in net revenue for 2018, according to its annual report. She says the knowledge and skills she acquired at the College of Engineering are applicable in an industry where efficiency and accountability are valued.

“An assembly line is the same as what my team does. The skill set I learned, I can use anywhere. There is nothing you can’t break down into steps to better understand.”

Pradilla and her team provide operational support and oversight of assets for Goldman Sachs clients ranging from the wealth of private investors to portfolios held by businesses such as insurance companies.

Goldman Sachs conducts business on a global scale, meaning deadlines and professional relationships cross the International Date Line as well time zones.

“We work with managers across the globe on a daily basis,” said Pradilla, who works out of the firm’s Salt Lake City office.

According to Pradilla, her success as an industrial engineer in the financial industry is a powerful demonstration of the opportunities available to graduates entering the field.

“The market for industrial engineers is infinite. You can work anywhere,” said Pradilla, who has since been promoted to senior analyst and is now an associate with Goldman Sachs.

Pradilla’s journey to becoming an engineer was a step-by-step process, as Impulse

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she originally came to the Tampa Bay area from Colombia to study English. She earned her associate’s degree in Engineering from St. Petersburg College before coming to USF to pursue her Industrial Engineering degree.

“I always knew I wanted to be an engineer, I just didn’t know what kind,” said Pradilla, who was active with the Society of Hispanic Professional Engineers and the College’s annual Engineering Expo.

“USF helped me a ton with scholarships and the program they had was flexible, so I was able to work part time as a student. The Department of Industrial Engineering gave me the tools to succeed.”

Applying Lessons Learned at USF to Teach and Meet Global Challenges

By Brad Stager Since graduating with his PhD in

people and gained knowledge about

“It’s important to have that

Industrial Engineering in 2015, Felipe

teaching at different levels,” said

experience when you become

Feijoo has been building his career

Feijoo, who is creating a similar

faculty.”

by focusing on the trinity of higher-

program in Valparaiso, Chile, where

level scholarship: Service, Research,

he is an assistant professor at the

One of the elements Feijoo wants

and Teaching.

School of Industrial Engineering,

to include in PUCV’s Industrial

Pontificia Universidad Catolica de

Engineering program is a robust

Foremost, according to Dr. Feijoo,

Valparaiso, also known as Pontifical

series of seminars to broaden

is service and he is continuing the

Catholic University of Valparaiso.

students’ perspectives, something he

work in STEM outreach he began

He also exercised leadership and

says has been beneficial to him.

while pursuing his doctorate, such

teamwork through his activities

as his leadership in a National

in the USF chapter for INFORMS

Science Foundation-funded program,

(Institute for Operations Research and

“I think that’s something very positive

known as the GK-12 STARS (Students

Management Sciences).

and unique about the PhD program

Teachers & Resources in the Sciences). This program promoted

As a teacher, Feijoo applies lessons

program and one of my ideas is a

STEM education to elementary and

he learned at USF as he works with

research seminar similar to the one

middle school students in the Tampa

other PUCV faculty to develop a

at USF.”

area, many of whom are now in

strong Industrial Engineering program

high-tech careers.

there. Getting teaching experience

Exposure to a wide breadth of

while pursuing his PhD has proven

scientific topics has been helpful

useful, he said.

in Feijoo’s research, which he

“Through the GK-12 experience, I’ve learned to work with different 14

at USF. We’re trying to build a strong

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continued after graduating from

USF as a post-doctoral scholar at

applying those two sets of tools to

Agreement in the developing

The Johns Hopkins University-

problems related to climate change,

countries in Latin America.

MIT and at the Pacific Northwest

energy and health care.”

National Laboratory´s Joint Global

Feijoo says his research speaks for

Change Research Institute. Feijoo

Support for Feijoo’s approach to

him, but what he has to say about it

has also developed international

considering social implications

is pretty straightforward.

research partnerships, by having

in energy policy has come in

visiting positions in Saudi Arabia

the form of funding from the

“When we do research, we should

(KAPSARC) and in Vienna, Austria

Government of Chile’s Comisión

be looking at how we can use the

(IIASA). His energy-related work

Nacional de Investigación

models and tools we develop to

has ranged from legacy systems

Científica y Tecnológica, or

help society. We should always be

such as the oil and gas pipeline

National Commission for Scientific

thinking how we can do the best

industry to developing and

and Technological Research. The

for society, that’s the main driver.”

integrating microgrids.

funding is the equivalent of an NSF Career Award in the U.S. Feijoo’s

“My research is mainly focused on

proposal calls for examining how

optimization and game theory, and

to achieve the goals of the Paris

Dr. Felipe Feijoo

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Data-Driven Solutions for the Industry Using AI & ML

By Brad Stager

F

or people who mine data for a living, working in the insurance industry at a global financial hub

like Singapore could be considered prospecting in a motherlode of Big Data.

“Insurance is an industry where everything is driven by data, so it’s a good fit for me,” says Vishnu Nanduri, who earned his MS and PhD Industrial Engineering degrees at USF, and is now Munich Reinsurance’s Regional Head of Data Analytics in Southeast Asia, Japan, Korea, and India.

Working out of Munich Re’s Singapore office, Nanduri is establishing and managing analytics and AI capabilities in his area of responsibility and introducing local insurers to the benefits of AI. The insurance industry overall is embracing AI & ML to make the process from application to claim payment and customer retention as efficient and seamless as possible.

Using data tools to solve problems and achieve greater levels of efficiency and optimization in the areas of energy, climate change, healthcare and insurance has been a realization of what Nanduri says he set out to do when he decided to become an engineer instead of a physician.

“The work is intellectually satisfying and gratifying,” said Nanduri who said he plans to continue developing data-driven solutions for the industry. His work has been reported in worldwide publications and he has produced online educational videos on the subject of analytics.

Being able to contribute analytical expertise in a variety of industries is part of an industrial engineer’s job and

Dr. Vishnu Nanduri

Nanduri said the College of Engineering prepared him well to do so.

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“USF gave me a very, very solid foundation and I

Olympic Dream, a memoir by Ben Ryan, coach of Fiji’s

always thank Dr. Das for teaching me and introducing

2016 Olympic Gold Medal rugby sevens team, and to

me to the amazing world of machine learning and

Upside of Irrationality by Dan Ariely.

reinforcement learning, on which my career is based.

Along with Dr. Das’s excellent mentorship, the research

“My tastes are eclectic but I don’t get to read as much

seminar organized every semester by Dr. Jose Zayas-

as I’d like,” said Nanduri, who has published and

Castro gave me a good sense of research activities and

consulted extensively on the topics of big data, game

inter-disciplinary collaborations.” Nanduri added that

theory, machine learning and artificial intelligence.

mentorship at USF is a characteristic of the College’s

His dissertation, “Generation Capacity Expansion in

graduate program.

Restructured Energy Markets,” was recognized by USF for excellence and Nanduri received an Outstanding

“There were a lot of professors who were very helpful.”

Dissertation award for the work.

Nanduri said he continues to receive guidance from Industrial and Management Systems Engineering faculty,

After receiving his PhD in 2009, Nanduri taught as

including his PhD advisor, Tapas Das, the department

an assistant professor of Industrial Engineering at the

chair.

University of Wisconsin-Milwaukee and moved to full time industry work in 2013.

Nanduri is an avid reader with a broad range of interests, from keeping up with the latest in data sciences, to the book Sevens Heaven: The Beautiful Chaos of Fiji’s

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Outstanding Senior: Vanessa Arroyo Vanessa Arroyo was born and raised in Medellin, Colombia. She is married to Jose Luis Arroyo and has two kids, Aiden and Ashton. In 2008 she moved to Puerto Rico to attend the University of Turabo on a swimming scholarship where she started her Industrial Engineering degree. Vanessa started at the University of South Florida (USF) in spring 2015 and graduated in fall 2018 with a bachelor’s degree in Industrial Engineering.

During her time at USF she actively participated in different student organizations including American Society for Engineering Management (ASEM), which she helped to establish at USF as president and treasurer.

She was also a member of the Institute of Industrial and Systems Engineers (IISE) where she along with other team members volunteered to stage a kaizen event at a local soup kitchen. Along with Jose Arroyo and Savan Dave, Vanessa won the best capstone project of the 2018 graduating class.

Their project was an initiative for alternative building materials as means of constructing affordable housing for the homeless population.

Vanessa participated in several projects with different companies during her studies at USF. She participated in a project with Lockheed Martin where she and her team developed a tool for the plant to better predict lead times. She was also part of a team that helped the local Johnson’s Control plant to evaluate one of their assembly lines and design improvements to reduce injuries. Vanessa was part of a process improvement initiative in the College of Engineering lead by the Associate Dean where her team looked at some of the staff offices and found ways to improve everyday processes.

Currently, Vanessa works for the United Stated Air Force in the Oklahoma City Air Logistics Complex as an Industrial Engineer where she is part of the budget team that oversees more than fifty projects with a yearly budget of approximately twenty million dollars. She is concurrently working on her master’s degree in Engineering Management at USF and expects to finish by 2020

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Nazmus Sakib receives the 2018-19 Teaching Innovation Award Three years ago the Dept. of IMSE introduced the Teaching Innovation Award to recognize innovation by the teaching assistants (TA) that enhances success of the undergraduate students. Nazmus Sakib, a PhD student of IMSE, was selected by a faculty committee to receive the honor this year. He has served as a TA since 2015 in courses on Engineering Economy, Deterministic Operations Research, and Probabilistic Operations Research.

“It is truly an honor! I am grateful to the faculty and students.” Nazmus stated, “I have always enjoyed teaching. The role of TA required me to educate myself more carefully, since now I had the responsibility of facilitating learning for others.”

As regards innovation, Nazmus developed and used various online visualization tools to explain difficult technical concepts. He also emphasized working out examples on the board and promote active participation of the students with a goal to achieve better learning outcomes.

Nazmus grew up in Dhaka, Bangladesh. He obtained BS in Mechanical Engineering from Islamic University of Technology (IUT). He worked for two years at Coats PLC as Supply Chain Executive – Production Planning, after which he travelled to USA for graduate studies.

Currently, he is conducting research on healthcare data analytics under supervision of Dr. Mingyang Li, Assistant Professor, Dept. of IMSE.

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2018-2019 IMSE Faculty Publications in Refereed Journals Abdel-Mottaleb, N., *Ghasemi Saghand, P., Charkhgard, H., Zhang. Q. 2019. An Exact Multi-Objective Optimization Approach for Evaluating Water Distribution Infrastructure Criticality and Geo-spatial Interdependence. Water Resources Research. https://doi. org/10.1029/2018WR024063 *Baldeon-Calisto, M., and Lai-Yuen, S. 2019. AdaResU-Net: Multiobjective Adaptive Convolutional Neural Network for Medical Image Segmentation, Neurocomputing. https://doi.org/10.1016/j.neucom.2019.01.110 Boland, N., Charkhgard, H., Savelsbergh, M. 2019.

Preprocessing and Cut Generation Techniques for Multi-objective Binary Programming. European Journal of Operational Research. https://doi.org/10.1016/j. ejor.2018.10.034 Charkhgard, H., Eshragh, A. 2019. A New Approach to Select the Best Subset of Predictors in Linear Regression Modelling: Bi-objective Mixed Integer Linear Programming, ANZIAM Journal, https://doi. org/10.1017/S1446181118000275 Charkhgard, H., Savelsbergh, M., Talebian, M. 2018.

A Linear Programming Based Algorithm to Solve a Class of Optimization Problems with a Multi-linear Objective Function and Affine Constraints. Computers & Operations research. https://doi.org/10.1016/j. cor.2017.07.015 Charkhgard, H., Savelsbergh, M., Talebian, M. 2018.

Nondominated Nash points: application of biobjective mixed integer programming. 4OR- A Quarterly Journal of Operations Research. https://doi.org/10.1007/ s10288-017-0354-2 Charkhgard, H., *Subramanian, V., Silva, W., and Das, T. K., 2018. An integer linear programming formulation for removing nodes in a network to minimize the spread of influenza virus infections. Discrete 20

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Optimization, Volume 30, November 2018, pages 144167. https://doi.org/10.1016/j.disopt.2018.06.005 *Chen, S., Kong, N., *Sun, X., Meng, H. and Li, M. 2018. Claims Data-driven Modeling of Hospital Time-to-readmission Risk with Latent Heterogeneity.

Health Care Management Science. *Chen, S., Lu, L., Xiang, Y., Lu, Q. and Li, M. 2018.

A Data Heterogeneity Modeling and Quantification Approach for Field Pre-assessment of Chloride-Induced Corrosion in Aging Infrastructures. Reliability Engineering & System Safety.

Chung, B.D., Park, S., Kwon, C. 2018. Equitable Distribution of Recharging Stations for Electric Vehicles. Socio-Economic Planning Science, 63, 1–11.

Dahigamuwa, T., Gunaratne, M. and Li, M. 2018. An Improved Data-Driven Approach for the Prediction of Rainfall-Triggered Soil Slides Using Downscaled Remotely Sensed Soil Moisture. Geosciences. *Dai, R., Charkhgard, H. 2018. A two-stage approach for bi-objective integer linear programming. Operations Research Letters. https://doi. org/10.1016/j.orl.2017.11.011 *Dai, R., Charkhgard, H. 2018. Bi-objective mixed integer linear programming for managing building clusters with a shared electrical energy storage. Computers & Operations research. https://doi. org/10.1016/j.cor.2018.01.002 Das, D., Pasupathy, K.S., Haddad, N.N., Hallbeck, M.S., Zielinski, M. D., Sir, M.Y. 2018 Improving Accuracy of Noninvasive Hemoglobin Monitors: A Functional Regression Model for Streaming SpHb Data IEEE Transactions on Biomedical Engineering 10.1109/TBME.2018.2856091

Das, D., Pasupathy, K.S., Storlie, C.B., Sir, M.Y., 2019. Functional regression-based monitoring of quality of service in hospital emergency departments IISE Transactions, https://doi.org/10.1080/24725854.2018.

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*Melendez, K. A., *Subramanian, V., Das, T. K., and Kwon, C. 2019. Empowering end-use consumers of electricity to aggregate for demand side participation. Applied Energy. https://doi. org/10.1016/j.apenergy.2019.04.092

Eaton, M., Yurek, S., *Haider, Z., Julien, M., Johnson, F., Udell, B., Charkhgard, H., Kwon., C. 2019.

Spatial conservation planning under uncertainty: adapting to climate change risks using modern portfolio theory. Ecological Applications. https://doi. org/10.1002/eap.1962

*Mendoza-Alonzo, J., Zayas-Castro, J., Charkhgard, H. 2019. Office-based and home-care for older adults in primary care: a comparative analysis using the Nash bargaining solution. Accepted for publication in Journal of Socio-Economic Planning Sciences. https://doi. org/10.1016/j.seps.2019.05.001

Farris, K. A., Shah, A., Cybenko, G., Ganesan, R., Jajodia, S., 2018. VULCON - A system for vulnerability prioritization, mitigation, and management.

ACM Transactions on Privacy and Security. https:// DOI:10.1145/3196884

*Mendoza-Alonzo, J., Zayas-Castro, J., Soto-Sandoval, K. 2018. Osteonecrosis in individuals with systemic lupus erythematosus: A predictive model; Osteonecrosis en individuos con lupus eritematoso sistémico: un modelo predictivo. https://doi.org/10.1016/j.reuma.2018.05.002

Garcia-Arce, A., Rico, F., and Zayas-Castro, J. 2018. Comparison of Machine Learning Algorithms for the Prediction of Preventable Hospital Readmissions. Journal for healthcare quality. doi: 10.1097/ JHQ.0000000000000080. *Ghasemi Saghand, P., Charkhgard, H., Kwon, C. 2019. A Branch-and-Bound Algorithm for a Class of Mixed Integer Linear Maximum Multiplicative Programs: A Bi-objective Optimization Approach. Computers & Operations Research, https:// doi.org/10.1016/j.cor.2018.08.004 *Haider, Z., Charkhgard, H., Kwon, C. 2018. A Robust Optimization Approach for Solving Problems in Conservation Planning. Ecological Modelling. https:// doi.org/10.1016/j.ecolmodel.2017.12.006 *Haider, Z., Nikolaev, A., Kang, J. E., Kwon, C. 2018. Inventory Rebalancing through Pricing in Public Bike Sharing Systems. European Journal of Operational Research, 270(1), 103–117.

*Nekooeimehr, I., Lai-Yuen, S., Bao, P., Weitzenfeld, A., and Hart, S. 2018. Automated Contour Tracking and Trajectory Classification of Pelvic Organs on Dynamic MRI. SPIE Journal of Medical Imaging. *Pal, A., Charkhgard, H. 2019. A feasibility pump and local search based heuristic for bi-objective integer programming. INFORMS Journal on Computing. https://doi.org/10.1287/ijoc.2018.0814 *Pal, A., Charkhgard, H. 2019. FPBH: A Feasibility Pump Based Heuristic for Multi-objective Mixed Integer Linear Programming in Julia. Computers & Operations Research. https://doi.org/10.1016/j. cor.2019.07.018 Rezaei, N., *Sierra Altamiranda, A., Diaz-Elsayed, N. Charkhgard, H., Zhang. Q. A multi-objective optimization model for decision support in water reclamation system planning. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2019.118227

Martinez, D. A., Feijoo, F., Zayas-Castro J., Levin, S., & Das, T. K. 2018. A strategic gaming model for health information exchange markets. Health care management science, 21(1), 119-130.

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Saghand, P.G., Charkhgard, H., Kwon, C. 2019. A Branch-and-Bound Algorithm for a Class of Mixed Integer Linear Maximum Multiplicative Programs: A Multi-objective Optimization Approach. Computers & Operations Research, 101, 263–274. *Sakib, N., Hyer, K., Dobbs, D., Peterson, L., Jester, D., Kong N., and Li, M. 2019 Data integrated predictive analytics for nursing home hurricane evacuation. Proceedings of IISE Annual Conference (Best Health System Track Paper Award) Shah, A., Ganesan, R., Jajodia, S., Samarati, P., Cam, H. 2019. Adaptive alert management for balancing optimal performance among distributed CSOCs using reinforcement learning. IEEE Transactions on Parallel and Distributed Systems. To appear.

Shah, A., Farris, K. A., Ganesan, R., Jajodia, S. 2019. Vulnerability selection for remediation: An empirical analysis, Journal of Defense Modeling and Simulation. To appear.

Shah, A., Ganesan, R., Jajodia, S., Cam, H. 2018.

A methodology to measure and monitor level of operational effectiveness of a CSOC. Springer International Journal of Information Security. https:// DOI:10.1007/s10207-017-0365-1 Shah, A., Ganesan, R., Jajodia, S., Cam, H. 2019.

A two-step approach to optimal selection of alerts for investigation in a CSOC. IEEE Transactions on Information Forensics and Security. https:// DOI:10.1109/TIFS.2018.2886465 Shah, A., Ganesan, R., Jajodia, S., Cam, H. 2018.

Adaptive reallocation of cybersecurity analysts to sensors for balancing risks between sensors. Springer Service Oriented Computing and Applications. https://DOI:10.1007/s11761-018-0235-3

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Shah, A., Ganesan, R., Jajodia, S., Cam, H. 2018.

Optimal assignment of sensors to analysts in a CSOC. IEEE Systems Journal. https://DOI:10.1109/ JSYST.2018.2809506 Shah, A., Ganesan, R., Jajodia, S., Cam, H. 2019.

Understanding trade-offs between throughput, quality, and cost of alert analysis in a CSOC. IEEE Transactions on Information Forensics and Security. https://DOI:10.1109/TIFS.2018.2871744 Shah, A., Ganesan, R., Jajodia, S., Cam, H. 2019.

Dynamic optimization of the level of operational effectiveness of a CSOC under adverse conditions.

ACM Transactions on Intelligent Systems and Technology. https://DOI:10.1145/3173457 Shah, A., Ganesan, R., Jajodia, S. 2019. A methodology for ensuring fair allocation of CSOC effort for alert investigation. Springer International Journal of Information Security. https://DOI:10.1007/s10207018-0407-3 Shireen, T., Shao, C., Wang, H., Li, J., Zhang, X. and Li, M. 2018. Iterative Multi-task Learning for Time-series Modeling of Solar Panel PV Outputs.

Applied Energy.

Shi, Y., Xiang, Y. and Li, M. 2019. Optimal Maintenance Policies for Multi-level Preventive Maintenance with Complex Effects. IISE Transactions. *Sierra Altamiranda, A., Charkhgard, H. 2019. A New Exact Algorithm to Optimize a Linear Function Over the Set of Efficient Solutions for Bi-objective Mixed Integer Linear Programming. INFORMS Journal on Computing. https://doi.org/10.1287/ ijoc.2018.0851 *Sierra Altamiranda, A., Charkhgard, H. 2019. OOESAlgorithm.jl: a julia package for optimizing a linear function over the set of efficient solutions for biobjective mixed integer linear programming. International Transactions in Operational Research. https://doi.org/10.1111/itor.12692

*Su. L., Kwon, C. Risk-Averse Network Design with Behavioral Conditional Value-at-Risk for Hazardous Materials Transportation. Transportation Science, Accepted. *Subramanian, V., and Das, T. K., 2019. A two-layer model for dynamic pricing of electricity and optimal charging of electric vehicles under price spikes. Energy 167 (2019): 1266-1277. https://doi.org/10.1016/j. energy.2018.10.171 *Subramanian, V., Das, T. K., Kwon, C., and Gosavi, A. 2019. A data-driven methodology for dynamic pricing and demand response in electric power networks. Electric Power Systems Research, Volume 174, September 2019, https://doi.org/10.1016/j. epsr.2019.105869

Wyman, A., Salemi, J. L., Mikhail, E., Bassaly, R., Greene, K. A., Hart, S., and Lai-Yuen, S. 2019.

Cost-Effectiveness of a Pre-Operative Pelvic MRI in Pelvic Organ Prolapse Surgery. International Urogynecology Journal. https://doi.org/10.1007/s00192-01904089-3

*Zhang, A., Kang, J. E., Axhausen K., Kwon, C. 2018. Multi-day Activity-Travel Pattern Sampling Based on Single-Day Data. Transportation Research Part C: Emerging Technologies, 89, 96–112.

Zhu, Z., Xiang, Y., Li, M., Zhu, W. and Schneider, K. 2019. Preventive Maintenance subject to Equipment Unavailability. IEEE Transactions on Reliability.

*Su, L., *Sun, L., Karwan, M., Kwon, C. 2019.

Spectral Risk Measure Minimization in Hazardous Materials Transportation. IISE Transactions, 59(6), 638–652. *Sun, L., Karwan, M., Kwon, C. 2019. Path-Based Approaches to Robust Network Design Problems Considering Boundedly Rational Network Users.

Transportation Research Record, 2673(3), 637–645. *Sun, X., Mraied, H., Cai, W., Liang, G. and Li, M. 2018. Bayesian Latent Degradation Performance Modeling and Quantification of Corroding Aluminum Alloys. Reliability Engineering & System Safety. *Toumazis, I., Kurt, M., Toumazi, A., Karakosta, L., Kwon, C. Comparative Effectiveness of Up-to-Three Lines of Chemotherapy Treatment Plans for Metastatic Colorectal Cancer. Medical Decision Making, Accepted.

Wen, Y., Wu, J., Das, D., Tseng, T. L. B., 2018, Degradation modeling and RUL prediction using Wiener process subject to multiple change points and unit heterogeneity. Reliability Engineering & System Safety 2018 https://doi.org/10.1016/j. ress.2018.04.005 Impulse

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NON-PROFIT ORGANIZATION U.S. POSTAGE Industrial and Management Systems Engineering University of South Florida 4202 East Fowler Avenue, ENG 030 Tampa, FL 33620

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TAMPA, FL PERMIT #257