Illinois Mathematics and Science Academy
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Intern at Illinois Treasurer\u27s Office
No full textThe Illinois State Treasurer\u27s Offce is a government agency that helps improve and support the financial situation of families living in the state. The office provides a variety of programs to help families save for college, save for expenses related to living with a disability, save for retirement, and more. Over the past few months, my work has focused on supporting and improving the college savings program. / analyzed data to help the program estimate future growth. Through this project, / compared the number of people that signed up with Illinois college saving plans with other States. Thus impacting the program\u27s ability to make investment decisions and provide the best growth for account holders. Moreover, I listened to stories of families \u27 interactions with the 529 college savings program. Then, I crafted their testimonies and shared them With the public. These testimonies can reach other people and motivate them to also invest in the program, which helps them prepare for college expenses. Lastly, / gathered information from many teachers from the Chicago area to tell them about the Illinois Personal Finance Challenge. This allows them to expose their students to earning income, spending, sawing, and investing
Edge Computing and Al Intern opportunity
No full textRobust and efficient face recognition and verification is becoming increasingly important in the modern age, due to the escalating presence of online interactions. For example, a manager may want to check remote employee authentication, but only has a video feed of them, or outside intrusions in secure environments. Thus, Face recognition and verification programs must be optimized. To achieve this, this internship utilized the deepface framework for python. The contemporary facial recognition pipeline consists of four core stages: detection, alignment, representation, and verification. Experiments involving distinct combinations of facial recognition models, face detectors, distance metrics and alignment models performed on the Labelled Faces in the Wild database were conducted in order to optimize the facial recognition pipeline. This internship provided valuable practical experience in this field and equipped me with necessary skills to contribute meaningfully
IT and Financial products Intern at Illinois Treasurer\u27s Office
No full textThe Illinois State Treasurer\u27s Office (STO) manages the stateS portfolio and runs several financial programs for the benefit of Illinois families, such as the Secure Choice retirement savings program and the Bright Start and First Steps college savings programs. The STO is building a new Data Team to support the Office\u27s existing programs and divisions. This team is the first of its kind in any Illinois State govemment agency and works closely with the STO\u27s IT division to build solutions to meet the needs of the various teams at the STO This work includes building a new database, creating automated ingestions pipelines for various data pieces, generating Visualizations and reports, automating manual processes, and running ad-hoc analyses on on as-needed basis. Over the past few months. I\u27ve supported this team on a variety of tasks, including analyzing Illinois Secure Choice program data to identify enforcement opportunities, and reviewing/analyzinq Illinois College Savings data to ensure the accuracy of First Steps claims \u27 eligibility determination. I have worked collaboratively with the STO\u27s internal teams to determine each team \u27s individual needs, and build the necessary infrastructure and processes to generate the required deliverables
Bethany E. Perez White, PhD
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HBCU Experience Panel 2025
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HBCU Experience Panal 2025
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Unsown Seeds: Eugenics, Immigration, Civil Rights in Twentieth-Century America
Get PDFDuring this panel, we will discuss the intersection of Progressive Era reforms and the pseudo-science of eugenics, looking at their impact on civil rights and immigration in American history and theories of Nazi Germany. This will include a full lesson plan run-through, with a set of primary sources, a PowerPoint slide deck, and extension assignments available for class use
Evaluating the Efficacy of Hydrogen Internal Combustion Engines for use in Emission-Intensive Sectors through Computational Fluid Dynamics Simulations
No full textHydrogen fuel is an alternative fuel and energy carrier for the power sector. This study outlines a framework for evaluating its efficacy as a substitute for natural gas in internal combustion (IC) engines through computational fluid dynamics (CFD) simulations. Firstly, relevant literature was reviewed to outline its properties and application considerations, and previous works that analyzed its performance through CFD were explored. Next, five CONVERGE CFD simulations were designed and run for both hydrogen fuel and methane (CH4), the primary component of natural gas, using a four-stroke singlecylinder engine model, sweeping spark timing to determine the maximum brake torque (MBT) spark timing, and adjusting the mass flow to achieve the same fuel energy input. For each simulation case, 3D ParaView visualizations and graphs of the heat release rate (HRR) and pressure curves were generated for qualitative comparison of the two fuels’ performance over one cycle and indicated thermal efficiency (ITE) was calculated and plotted to find the MBT timing for each fuel and quantitatively determine which exhibited the highest overall efficiency. The ITE metric was used to evaluate the hydrogen’s overall efficacy in IC engines, depending on whether or not its efficiency exceeded or resembled methane
Five-Year Spatiotemporal Water Quality Assessment of Horseshoe Lake Using Sentinel-2 Imagery and Google Earth Engine (GEE)
No full textSatellite-derived data analysis offers a cost-effective alternative to traditional in-situ measurements for monitoring water quality dynamics in critical water bodies. This study leverages remote sensing techniques to assess multiple zones within Horseshoe Lake, Illinois, identified based on physical barriers, hydrological flow, and proximity to water treatment facilities. To ensure scientific rigor, we applied unsupervised clustering techniques such as K-means, ISODATA, and DBSCAN to Sentinel-5P parameters. These techniques validated whether the selected zones are hydrologically distinct, allowing for a more precise characterization of spatial variations in water quality. Using Google Earth Engine (GEE), we retrieved cloud-free composite images spanning 2020-2024 and chose key water quality indicators for further analysis: chlorophyll-α concentration, turbidity, and phosphorus levels. We then applied statistical trend analysis and cross-indicator validation to explore parameter interdependence and assess how major meteorological events influence water quality trends. This study provides a comprehensive assessment of pollution dynamics within Horseshoe Lake, offering a robust methodology for long-term water quality monitoring. Future work will focus on integrating these analytical capabilities into a public dashboard, enabling users to monitor lake conditions in real time from any personal device
Integrating CNNS and LSTMs for mouse behavior classification Presenter
No full textUnderstanding animal behavior patterns is central for advancing research efforts in behavioral science. Accurately classifying behaviors allows for insights into how animals respond to different stimuli. Data frames annotated for key points on a mouse’s body were collected to identify specific mouse behaviors, such as when the mouse was shaking or licking. These labeled data points were subsequently used to train a deep learning model. The model uses both Convolutional Neural Networks (CNNs), which can obtain spatial features from individual frames of data, and Long Short- Term Memory (LSTM) networks, which are skilled at modeling long-term temporal dependencies within sequential data. This combination enabled the model to ingest both the visual data of each frame, i.e., the position of key annotated points, and the temporal patterns of behavior. The final model provides a tool for classifying mouse behaviors based on spatial and temporal information. The model was able to detect when the mouse was performing certain behaviors at the same time with precision but had difficulties identifying when only one of the behaviors was present