Data Science for a Changing Planet | 2024 Gateway Magazine
Advanced sensor technologies, growth in the amount and availability of sensor data,
new computational methods, and greater computational power offer fresh approaches
to understand and address the complex environmental challenges posed by climate change.
To help prepare tomorrow’s data scientists to effectively employ these tools, Michigan
Tech has been awarded a prestigious National Science Foundation (NSF) Research Traineeship (NRT) grant titled “Integrative Training in Data Science-Enabled Sensing of the Environment
for Climate Adaptation (DataSENSE).”
The five-year, $700,000 NRT DataSENSE project will deliver training, research, and
mentoring experiences to as many as 15 Michigan Tech doctoral students from academic
departments across campus, preparing them to analyze and interpret climate-adaptation-related
problems using cutting-edge, data science-intensive tools. Participating students receive support covering the first five semesters
of their doctoral studies: one full year plus fall and spring of the next year.
“The NRT grant recognizes that Michigan Tech has all of the required pieces to provide
students with this type of training,” says Laura Brown, associate professor of computer science and the project’s principal investigator. “It allows us to connect these pieces into
a holistic student experience. Future leaders will need transdisciplinary training
like this.”
Participating PhD Programs
Principal Investigator
- Laura Brown, Associate Professor, Department of Computer Science
Co-PIs
- Dukka KC, Professor, Department of Computer Science
- Thomas Oommen, Professor, Department of Geological and Mining Engineering and Sciences
- Shiliang Wu, Professor, Department of Geological and Mining Engineering and Sciences
Senior Personnel
- Tao Liu, Assistant Professor, College of Forest Resources and Environmental Science
- Sidike Paheding, Fairfield University
- Ashraf Saleem, Assistant Professor, Department of Applied Computing
Faculty from three colleges and six PhD programs will mentor DataSENSE trainees, sharing
their expertise in data science, machine learning, computer vision, geological engineering,
environmental engineering, sensing technology, atmospheric science, and forestry science.
“We want to engage doctoral students in fantastic research opportunities and mentor
them so they can become selfconfident experts with a portfolio of essential computational
skills and sensors and application knowledge,” says Brown.
The NRT project began in March 2023. During its first year, the faculty investigators
have focused on student recruitment to build a diverse PhD trainee pool. They are
also developing courses and activities that support professional development and student
retention. NRT activities will include seminar series, symposia, workshops, faculty
and peer mentoring, and career development training. Many of these opportunities will
also be available to students who are not part of the NRT program.
Dennis Livesay, Dave House Dean of Computing, says the award represents the growing importance of
computing-centered efforts to Michigan Tech’s research mission.
“Doctoral education in today’s world is about providing students with opportunities
to contribute to society, wherever they see fit—in the academy, in industry, as entrepreneurs,
in government,” says Will Cantrell, associate provost for graduate education and dean of the Graduate School. “The NRT experience enhances Michigan Tech’s ability to do just that.”
Prospective, new, and current Michigan Tech doctoral students are invited to apply
for the NRT traineeship.
Laura Brown: Always Learning and Collaborating
When Laura Brown was a graduate student, data science wasn’t yet a separate discipline;
it was spread throughout many areas. As data science started to develop as a distinct
academic subject area, she became very interested in it and the artificial intelligence,
machine learning, and computational aspects of computer science.
“Data science can be applied to so many types of problems in so many areas. This is
something that I really enjoy about what I do,” says Brown, now an associate professor
of computer science at Michigan Tech.
Brown’s research interests focus on both theoretical data science topics and the application
of data science techniques to other domains. She works with faculty across campus
and at other universities, including experts in biology, forestry, chemistry and chemical
engineering, and social sciences.
Brown is associate dean for data science initiatives in the College of Computing and
also directs MTU’s bachelor’s and master’s degree programs in data science. She is
a member of two Michigan Tech research centers: the Institute of Computing and Cybersystems (ICC) and the Center for Agile Interconnected Microgrids (AIM).
“There’s always an opportunity to collaborate, and I’m always learning about new things
and working with fantastic collaborators.”
Undergrad Profile: Felicia Huffman, Data Science
Junior undergraduate Felicia Huffman, from Jackson, Michigan, has had a passion for
math since the fifth grade, so it was important to her to find a career where she
could apply it.
“I did some research and discovered data science,” she says. “It provides a great salary, a strong job outlook, and an opportunity
for me to be challenged. These factors, along with my computer science experience,
are why I chose data science.”
Huffman toured Michigan Tech as a high school student and loved it. “It was during
Winter Carnival. There was snow everywhere, and I was surrounded by amazing ice sculptures. I love
all the activities you can do in the snow, like skiing, snowmobiling, and snowball
fights.”
After Huffman participated in a datascience- focused exploration through MTU’s Summer Youth Programs, she decided that Michigan Tech was where she wanted to be. “I got along with the
other people at the camp better than I have with anyone,” she says. “I connected with
Dr. (Laura) Brown to confirm that the data science BS program was coming, and now
here I am today.”
Huffman is enjoying being a part of the new program, launched by the College of Computing in fall 2023 under Brown’s direction.
Huffman isn’t yet sure where she wants to take her career, but she hopes to pursue
work that helps people, potentially as a healthcare data scientist. “Data science
is still such a broad category. If I had to choose now, I would say the artificial
intelligence and machine learning side interests me the most,” she says. “It’s fascinating
to me how data can drive a machine, and how, if that data is biased, it can significantly
affect the machine’s practicality.”
Along with her bachelor’s degree studies, Huffman is planning to complete an accelerated master’s in data science. She hopes to graduate in fall 2027.
“I feel like we have a lot of flexibility and we also get to help create the path
for future students. It makes it feel more interactive, rather than the professor
doing most of the work.”
Graduate Student Profile: Pradnya Pendse, Data Science
Pradnya Pendse began her graduate studies in data science at Michigan Tech in fall
2022 after working in the automotive and manufacturing industry for four years. She
earned her bachelor’s degree in computer science and engineering in 2018 from Shivaji
University in Kolhapur, Maharashtra, India.
“As a computer science bachelor’s degree graduate with work experience as a data analyst
and engineer, I decided to study data science,” says Pendse.
Pendse’s interest in Michigan Tech was spurred by the University’s work in the manufacturing
and automotive domains. “The combination of well-rounded technical coursework in data
science and the prospect of engaging in innovative research projects made MTU an appealing
choice for me,” she says.
“The well-structured courses at Michigan Tech offer an excellent balance between technical
and functional domains,” says Pendse. “The project-driven approach to learning not
only enhances theoretical understanding, it provides opportunities to implement learning
in real-time projects, fostering practical skills and application.”
Pendse is particularly interested in the application of data science in the automotive
industry. “What excites me the most is the prospect of using advanced analytics and
machine learning to derive insights from complex datasets in manufacturing and automotive
processes,” she says. “I see the potential for impactful innovations and improvements
in efficiency, quality, and decision-making within this industry.”
“I see data science as the next logical step in my career, offering the opportunity
to solve complex problems and contribute to informed decision-making through advanced
analytical methods.”
At the 2023 IEEE ASEE Frontiers in Education Conference (FIE), Pendse presented her research paper, “Work-In-Progress: Python Code Critiquer, A Machine Learning Approach.” She says the collaborative research described in the paper develops a system that
automatically detects coding mistakes made by students in programming classes and
provides immediate feedback to improve student learning outcomes and coding skills.
The work is funded by a research and development grant from the National Science Foundation; Assistant Professor Leo Ureel of the Department of Computer Science is the principal investigator. Pendse also presented this research at the 2003 First Year Engineering Experience Conference (FYEE).
In spring 2024, Pendse is completing a co-op as a data engineer in the SML Operations
department of the Volvo Group, a major producer of trucks, buses, construction equipment, and marine and industrial
engines. In summer 2023, she worked as an advanced analytics intern with Driven Brands, the parent company of some of North America’s leading automotive services. Her primary
focus there was developing a comprehensive time series model from the ground up, which
encompassed meticulous data preprocessing and the application of sophisticated feature
selection techniques.
“One of the most interesting parts of my internship at Driven Brands was building
a strong model to predict how things change over time,” she says. “To do this, I applied
my analytical and statistical skills to make very accurate predictions. I also worked
with models that consider multiple factors to get a better understanding of how things
are connected.”
Pendse expects to graduate with her Master of Science in Data Science this spring. She plans to restart her career in the manufacturing and automotive
industry as a data engineer or data scientist.
“While I am sad to close this chapter of my career, I couldn’t be more excited for
the next.”
BS in Data Science Welcomes First Cohort
Organizations of all sizes and types are using data to drive decision-making, improve
business processes, design and develop new products, and market their products. And
the volume, availability, and potential uses for data are increasing exponentially.
As a result, data science is a rapidly growing occupational opportunity. The US Bureau of Labor Statistics identifies data science as one of the fastest-growing job sectors in the US, projecting
35 percent growth and the creation of nearly 60,000 new jobs through 2023. The 2022
median pay of data scientists was $103,500.
In response to these growing employment opportunities, the College of Computing has
launched a Bachelor of Science in Data Science, which began accepting students in fall 2023. Laura Brown is the director of the
new program.
The program delivers a broadbased education in data science fundamentals, data mining,
predictive analytics, communication, and ethics. Students gain a competitive edge
through a technical focus area in software engineering, cybersecurity, statistics, or business technology. Students also have the freedom to explore and
develop their own interests in one or more domains. Graduates of the program are well-positioned
to pursue master’s degrees.
“Our first cohort of students is really excited to be learning about data science.
There’s such a need for these skills. I’m looking forward to creating new classes
and degree pathways so we can deliver the knowledge and experience our students will
need as they begin their data science careers.”
MS in Data Science Has New Home
Michigan Tech’s interdisciplinary MS in Data Science, established in 2013, found a
permanent home in the College of Computing in fall 2023, moving from its former administrative
home in the Graduate School. Laura Brown directs the graduate program.
“Continuing to grow our presence in artificial intelligence, machine learning, and
data science is one of my biggest priorities,” adds Livesay. “We’ll continue to work
closely with our colleagues across campus, especially business and math, to ensure
that all aspects of data science are represented.”
The data science master’s program is extremely flexible, allowing students to concentrate
on a specific area of interest. “If a student is more interested in the business side
of data science, they can focus there. Or, if they wish to focus on the machine learning
or statistics side, they can do that,” says Brown. And even though the degree is a
coursebased program, students who wish to can pursue research with a faculty mentor.
“We have accepted the responsibility to grow the program, which is a tremendous opportunity
that should benefit both the University and our students.”
Michigan Technological University is a public research university founded in 1885 in Houghton, Michigan, and is home to more than 7,000 students from 55 countries around the world. Consistently ranked among the best universities in the country for return on investment, Michigan’s flagship technological university offers more than 120 undergraduate and graduate degree programs in science and technology, engineering, computing, forestry, business and economics, health professions, humanities, mathematics, social sciences, and the arts. The rural campus is situated just miles from Lake Superior in Michigan’s Upper Peninsula, offering year-round opportunities for outdoor adventure.
