Recent graduate’s data science research extracts health status from a handshake
You could describe Cameron Lee’s recent undergraduate research as “gripping.”
Lee (’24 BS Data Science) took the top prize at the campuswide undergraduate research poster competition last year for her project examining grip strength as a potential indicator of age-related frailty and overall health.
By applying machine learning algorithms, Lee analyzed factors like age, height, race, and sex to uncover meaningful patterns in grip strength data. Her findings aim to help doctors better understand patient health and create more personalized treatment plans.
The joint BS in Data Science program is a collaboration between the College of Engineering & Applied Science and the College of Letters & Science. Read more about her project and what comes next for Lee here.
Slavens honored with government’s highest award for early career scientists and engineers
Brooke Slavens, Richard and Joanne Grigg Professor of Mechanical Engineering, has been awarded the prestigious Presidential Early Career Award for Scientists and Engineers. The award is highest honor bestowed by the U.S. government on outstanding scientists and engineers early in their career.
Slavens was nominated by the National Institutes of Health for her pioneering research on shoulder pain experienced by both pediatric and adult manual wheelchair users. In addition to wheelchair mobility, Slavens’ expertise includes upper extremity modeling and rehabilitation engineering. Read more.
Two recent alums become faculty members at UW-Green Bay
UW-Green Bay has hired two recent alums as faculty members in their Richard J. Resch School of Engineering. The school is part of the College of Science, Engineering and Technology.
Md Rasedul Islam (’20 PhD, Mechanical Engineering) is an associate professor whose research interests include bio-robotics, intelligent systems and control, and automation.
Assad Uz-Zaman (’24 PhD, and ’17 MS, Mechanical Engineering) is an assistant professor who researches robotics, control robot motion planning, industrial automation, and sensor fusion.
Habib Rahman, Richard and Joanne Grigg Professor, mechanical engineering, was UWM advisor for both graduates.
College leaders visit partner universities in Taiwan to explore expanding agreements
Representatives of the college recently visited two universities in Taiwan – Chang Gung University (CGU) and Chung Yuan Christian University (CYCU) – with an eye toward expanding academic degree program collaboration, injecting more research opportunities into those programs, and exploring deeper industry-academic collaboration.
Andrew J. Graettinger, associate dean for research, Dah-Chuan Gong, scientist, and Jaejin Jang, department chair and associate professor, both in the industrial & manufacturing engineering department, made the trip. Gong, a former dean of the College of Management at CGU before coming to UWM in 2022, was instrumental in organizing the trip.
Andy Graettinger (center) joins the group at the Formosa Plastics Museum, located on the Chang Gung University campus. The model underfoot is of the Sixth Naphtha Cracker Complex of Formosa Plastics Group.
New program proposed with CGU
A proposed new degree program being discussed with CGU is a 3+2 program. Students would take three years of undergraduate business management courses in Taiwan and, during their first year at UWM, they would complete their undergraduate coursework, but in engineering. They would receive their bachelor’s degree in business management from CGU and then continue their studies at UWM to receive an MS in engineering from UWM.
“The two degrees stand alone, which is rather unique,” Graettinger said. “We have a path forward that suggests it would work.” This potentially would result in 20 or more new UWM master’s degree students a year, he said.
The college and officials at CGU have signed a memorandum of intent to establish the proposed 3+2 accelerated degree program.
The existing partnership programs with CGU includes:
a dual master’s program between the college and CGU’s College of Management
a dual master’s program between the college and CGU’s College of Engineering
a non-degree program for undergraduates
Programs with CYCU growing
At CYCU, the 2+2 undergraduate program has grown from 20 in a cohort to 26. The 2+2 program with CYCU is a dual degree program that began in 2023 and offers students the opportunity to study in Taiwan for their first two years and complete their final two years at UWM.
Tzu-Yun Yen, a senior in electrical engineering, is a student from CYCU in the 2+2 joint program with UWM.
Students in computer science, computer engineering and electrical engineering are eligible. A dual master’s program in electrical and industrial & manufacturing engineering has been ongoing since 2018.
Also, the UWM team pledged to provide students in the existing 2+2 program with opportunities in UWM engineering and computer science research and financial support through the Support for Undergraduate Research Fellows (SURF) program.
Tzu-Yun Yen, a senior in electrical engineering, who is participating in CYCU’s 2+2 program, shared, “In the classroom at UWM you will meet students from different countries. The good thing about studying at UWM is that the environment will help you find out your future goals sooner.”
Aligning research for more student involvement
The proposal falls in line with another aim – to identify pathways to increase collaborative research in both partnerships.
“We have good research topic alignment with both CYCU and CGA,” Graettinger said. “We both have faculty who are active in the areas of medical devices, electrical engineering, industrial optimization, and membranes and filtration, for example. We’re trying to cultivate those.”
For the first step, UWM will begin working on a proposal that will be submitted to International Network-to-Network Collaborations (AccelNet) to enable joint research. That would open the way for graduate students to also conduct research as they work on their dual degrees.
There also was interest from all parties to grow the partnerships’ research ties in tandem with industry in both countries, Gong said.
Students currently enrolled in partnership programs have had work opportunities at Foxconn in southeast Wisconsin. But the team is exploring additional possibilities.
During their trip, UWM representatives learned about CGU’s semiconductor program and its industrial support and visited the semiconductor clean room on the campus.
At CYCU, the UWM team toured the R&D Center for Smart Manufacturing (SMC), a facility that is introducing smart manufacturing concepts into the injection molding industry in Taiwan. Graettinger said the teams discussed promoting the SMC, led by Professor Shia-Chung Chen, to the sector industries in the Milwaukee region.
Currently the college’s programs with the two Taiwanese universities involves about 50 students, both undergraduates and master’s students enrolled in one of the dual programs at UWM. Students benefit by receiving an international education, access to research and internship and career opportunities.
Winning Fall 2024 Senior Design projects impress the judges
In the required Senior Design courses, students apply what they’ve learned and demonstrate their knowledge within their major as they participate in a team-based project. This provides experiential learning including teamwork, communication, and project management.
With the exception of the Materials Science & Engineering Department, one winning team from each department was recognized at the Order of the Engineer ceremony on Saturday, Dec. 14, 2024. Students in materials science & engineering will compete in the spring of 2025.
A shout-out of thanks to GE HealthCare, which sponsors the Senior Design competition, and to all the companies who submitted projects. Full descriptions are here.
Biomedical: “Sensing and Proximity Innovations” Team Members:
Aaron Brandner
Josh Lopez
Adrian Nazario-Valdez
Ryan Taylor
Advisor: Grace McClatchey, instructor
Civil & Environmental Engineering: “Bold & Brash” Team Members:
Sydney Block
Ryan DeVries
Rebekah Downs
Hunter Hanegmon
Noah Thompson-Hall
Advisors: Sarah Blackowski, assistant professor, and Clayton Cloutier, adjunct instructor
Computer Science: “Foraging Tracker” Team Members:
Anya Flickinger
Jennifer Justus
Danh Le
Henry Retzer
Ivan Sosa
Advisor: Ayesha Nipu, teaching faculty
Electrical Engineering: “Atomic Clock Receiver” Team Members:
Sam Catania
Aisha Mian
Chase Nicpon
Advisors: Jeff Kautzer, adjunct professor, and William Dussault, teaching faculty
Industrial & Manufacturing Engineering: “Developing an Effective Inventory Model” Team Members:
Muqrin Alrehaili
Thomas Schaller
Weston Schneider
Advisor: Dah-Chuan Gong, scientist II
Mechanical Engineering: “Demolding Fixture Redesign” Team Members:
Dylan Engelbright
Adrian Sanchez
Vince Swartz
Josiah Welch
Project Advisor: Mohamed Yahiaoui, teaching faculty Industry Mentor: David Hanson, Regal Rexnord
Nosonovsky blends surface science with machine learning to predict beach contamination
A interdisciplinary UWM research team, including Michael Nosonovsky, professor, mechanical engineering, collaborated to determine how to predict E. coli outbreaks at beaches more effectively.
Their goal was to identify the key sand conditions linked to E. coli growth and determine the best machine-learning method to predict these conditions.
Michael Nosonovsky
Their findings were published in an article that appeared in a 2024 volume of the journal Surface Innovations.
E. coli bacteria are often used as indicators of water contamination, and elevated levels are one of the main reasons for beach closures. The researchers focused on how the physical and chemical properties of sand influence the survival and spread of these bacteria.
“Bacterial contamination of beach sand poses a public health problem,” Nosonovsky said. “So, it’s important to establish correlations between surface properties of sand and biocontamination, allowing us to predict and prevent the latter.”
Nosonovsky, whose expertise is tribology – the study of surfaces and friction – said that how sand interacts with water plays an important role in bacterial growth.
The work was conducted using data from Bradford Beach on Milwaukee’s lakefront. The researchers tested five different machine learning techniques and concluded the artificial neural network (ANN) technique outperformed other models in predicting E. coli concentrations.
The ANN model identified three critical factors predicting E. coli levels in sand:
the state of sand, including parameters such as moisture content, pore size and the zeta potential – the difference in potential between a particle’s surface and the liquid it is suspended in.
processing temperature
the contact angle, which measures how easily water spreads across its surface. A special methodology was developed to measure the water contact angle of sand, Nosonovsky said.
The study shows the great potential of “tribo-informatics” – a new field that combines tribology, with data science and machine learning methods – to solve various problems, he said. The technique can be scaled up and applied to other beaches. Other team members were Md Syam Hasan (’22 PhD, mechanical engineering); Marcia Silva, former manager of UWM’s Water Technology Accelerator, and Alma Nunez.
Klajbor named as interim Divisional Finance Officer for the college
Paul Klajbor, Divisional Finance Officer in Academic Affairs & Strategic Enrollment Management & Student Success, will be serving as the interim Divisional Finance Officer for the college, following Bob Barry’s recent retirement.
Members of the college can direct their needs to the appropriate office, using the list of contacts below.
HR related items: hr-contact@uwm.edu, 414-229-4463
Accounting and financial items: Adam Nowaczyk, nowaczyk@uwm.edu, 414-251-6283
Building maintenance issues: Leanne Myers, myersll@uwm.edu, 414-251-5990
Procurement issues: Anna Deisinger, deising2@uwm.edu, 414-251-6340
Northwestern Mutual Data Science Institute funds more faculty and student projects
The Northwestern Mutual Data Science Institute (NMDSI) has recently awarded more than $700,000 in grants through three annual programs that aim to foster cross-institution collaboration in data science research and education.
The goal of the NMDSI, a partnership between UWM, Marquette University and Northwestern Mutual, is to establish Wisconsin as a recognized national hub for data science and technology. Building on nearly $40 million invested since its inception in 2018, the three institutions will commit $35 million to the institute over the next five years.
Seven of the 29 total awards were given to students and faculty at the college. Awardees in each program include:
Paving ROADS Seed Fund Program aims to support new research partnerships across disciplines and strengthen cross-campus research opportunities.
Tom Shi, assistant professor, civil and environmental engineering “Enhancing Rural Connectivity in Wisconsin: A Data Science and AI-based Framework for Connected On-demand Public Transit.”
Mohammad Habib Rahman, Richard and Joanne Grigg Professor, mechanical engineering “Development of AI-driven Dynamically Adaptive Serious Games for Enhancing Home-based Robot-assisted Therapy.” Collaborators: Sheikh Lqbal Ahamed (Marquette) and Inga Wang (UWM)
Michael Nosonovsky, professor, mechanical engineering “Tribo-informatics: Societal Impact of integrating Data Science and Machine Learning methods with surface engineering.”
Tian Zhao, associate professor, computer science, is a collaborator on Lei Fan’s (Marquette) project, “Physics-informed and Machine Learning-accelerated Digital Twin Risk Prediction for Left Ventricular Assist Device.”
Pioneer Collaborative Curricula Program seeks to introduce and embed emerging areas of data science into the curricula of UWM and Marquette University.
Mohammad Habib Rahman, Richard and Joanne Grigg Professor, mechanical engineering “AI for Rehabilitation Robotics.” Collaborators: Susan McRoy, professor, computer science; Inga Wang; and Linnea Laestadius (all UWM)
Student Research Scholars Program seeks to engage students from our partner institutions in data science research, working with affiliated faculty and data science experts across disciplines.
Anirudha Subratta Mitra, master’s student, data science Faculty Mentor: Nathaniel Stern, professor, mechanical engineering “Learning the Hallucination Effect: Leveraging Machine Learning Algorithms for Novelty Generation.”
Tanvir Ahmed, PhD candidate, biomedical engineering Faculty Mentor: Mohammad Habib Rahman, Richard and Joanne Grigg Professor, mechanical engineering “Developing a Multilingual Hybrid RAG-GPT Chatbot for Personalized Therapy.”
Masoud Khani, PhD candidate, health informatics Faculty Mentor: Jake Luo, associate professor, health care informatics (affiliated faculty) “User-Centered Explainable AI Panel for Patients.”
Shi’s work is transforming traffic data into road safety solutions
Every time you drive a vehicle, one aspect of your safety comes from something you have little control over – other drivers. What if risky driving behaviors could be tracked as they are happening and immediate warnings delivered to drivers nearby?
“The idea is that drivers may be able to take a defensive stance to avoid crashes if they could be alerted to risky driving in their vicinity,” said Tom Shi, an assistant professor of civil & environmental engineering. “Or police could discover where the most dangerous locations are and intervene.”
Members of Shi’s lab have completed the first step in a multi-pronged data science project aimed at improving road safety by analyzing video for predictive modeling.
Making Waves of Impact A transportation engineer uses camera data and AI to predict where drivers exhibiting dangerous behaviors are.
Since he was looking for traffic data, Shi partnered with the UWM Police Department which maintains a large network of surveillance cameras pointed at roadways all around the campus.
Extracting answers from data
The lab members began by began by collecting the incidence of risky driving behaviors on certain stretches of road or at intersections at various intervals. Then, they built a digital map of what happened using a detection algorithm they developed.
“We use deep learning methods to extract characteristics from vehicle footage, and these characteristics help us identify distracted driving behavior, such as using a phone or taking your eyes off the road,” Shi said.
A video of one of the researchers’ digital maps shows cars as 3D boxes moving along the street where pedestrians are visible, marked in yellow.
The algorithm provides the time-stamped location of the objects and their GPS coordinates, the object’s speed and the size of each – whether it’s a car, truck or even bike.
“Given all those parameters, we can use data science to answer questions like, “How often does speeding occur and under what circumstances?” Shi said. “The lab members assigned a score from the safest conditions to the worst scenarios. So, the algorithm is using the data to pick out the unsafe anomalies.”
An unsafe pedestrian hotspot
From traffic footage that spans Maryland Avenue from the Student Union to Edgewood Avenue, a long corridor that includes three intersections, the researchers have used the modeling to help them understand and analyze the interaction between the pedestrians and vehicles.
For example, Shi’s students developed a video that re-constructs traffic moving along Maryland Avenue in front of Hartford Elementary School from data collected by a camera mounted to the northeast corner of Lapham Hall.
The group found that drivers approaching the crosswalk there often follow the car in front of them very closely in order to avoid stopping when pedestrians are present. That leaves pedestrians wondering who will stop and who won’t.
The final step
Shi said his work includes both the data science needed to clarify traffic problems and the development and testing of new technologies to address them.
The final step in this project will be to create an intervention that would send out a warning of driving aberrations happening at a location in real time.
Although the warning product has not yet been created, one idea is an audible signal on a driving app, he said. The research has the potential to lead to new products.
Further in the future, for example, the warning product can leverage the existing cellular network. This technology is called cellular-vehicle-to-everything (C-V2X) communication.
“We do plan to install a C-V2X roadside unit at the Hartford-Maryland intersection,” Shi said. “Currently, it requires the vehicle to have a C-V2X onboard unit to receive the command we broadcast. In the future, this will be equipped on vehicles by the manufacturer.”
SAE magazine published an interview with Rahman about rehab robotics
Habib Rahman, professor, mechanical engineering, was interviewed for a Q&A that recently appeared in Tech Briefs magazine on his recent research building a platform that would make remote physical therapy available to stroke patients.
Each month, the engineering magazine, put out by the SAE Media Group, features a researcher who has done innovative research.
Rahman developed a portable, assistive robotic arm, called the iTbot, that allows stroke patients to receive physical therapy without leaving their homes.
In the interview, Rahman explains how the assistive arm can adjust the right tension for a patient, which methods the arm employs to measure pain-free range of motion, what information a digital twin can give the therapist, and why a therapist is always a part of the treatment’s platform.
