Science Day Archives - ��Ƶ

Science Research Day

Stephen Garone — Fri, 08 May 2026 13:30:00 +0000

At ��Ƶ’s 35th Annual Professor Louise Hainline Science Day, students working with faculty present judged posters on their research. Join us for student presentations, followed by lunch and an awards ceremony. Details and deadlines are available here.

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School of Natural and Behavioral Sciences Announces Winners of 30th Annual Science Research Day

Susan Landers — Sat, 08 May 2021 14:08:02 +0000

The School of Natural and Behavioral Sciences recently held their 30th annual ��Ƶ Science Day, the first that was held virtually, after having to cancel last year’s program due to the COVID-19 pandemic. Organized by the college’s Center for Achievement in Science Education, this year’s event featured 57 student posters from 41 undergraduate and 16 graduate students. Each poster was considered by two judges who first viewed a virtual poster described by the students in a video and then met with the students online or by telephone to ask questions and give feedback. The results were announced at a virtual award ceremony on May 7 with nearly 100 attendees. The winning research covered a diverse range of fields and inquiries, from a mouse with fatty liver disease to the role of religious experiences in interpersonal relationships.

For the undergraduate division, the winners were: In first place, Roberto DeGregorio, a chemistry student whose paper was titled Towards Gold-Based Targeted Theranostic Agents: Synthesis and Characterization of Cationic Au(Iii)-Nhc Iodo Complexes; In second place, Claudia Melo, a biology student whose paper was titled Antioxidant, Antibacterial, and Anti-Sars-Cov Activity of Commercial Products Of Xylopia (Xylopia Aethiopica) tied with Dobrushe Denburg, a chemistry student whose paper was titled Photochemical and Photophysical Study of Bis-Alkylated Lumazine and Pterin Photosynthesizers; In third place, Ominakhon Nazarzoda, a biology student whose paper was titled Trafficking Monocytes Into the Ischemic Brain And Mapping Cell Subtypes.

For the graduate division, the winners were: In first place, Eliza Altvater, a Health and Nutrition Science student whose paper was titled The Role Of Hepatic Stellate Cell Activation Via Tlr4 In Non-Alcoholic Steatohepatitis-Induced Fibrosis; In second place, Kristy St. Rose and Jasmine Williams, Health and Nutrition Science students whose paper was titled Mouse Fed A Western Diet Develop Obesity And Nonalcoholic Fatty Liver Disease; In third place, Jaclyn K. Doherty, a psychology student whose paper was titled Disclosure Of Meaningful Religious Experiences In Interpersonal Relationships.

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Two CIS Students Are Winners on Science Day

Communications — Sun, 19 May 2019 15:10:37 +0000

The CIS Department is a power in student research at ��Ƶ. CIS had two winners at Science Day in the Undergraduate Division, both of whom tied for second place: Aleksandr Kovalev, mentored by Assistant Professor Tzipora Halevi, on Android malware detection, and Joshua N. Sash, mentored by Assistant Professor Hui Chen, on determining the accuracy of code-similarity programs.

Aleksandr Kovalev

Alex Kovalev

Alex Kovalev presented his work on use of neural networks to detect malicious Android applications. The project introduced a newly designed neural network for detecting malware, based on the features extracted from Android .apk files. The proposed Neural Network (NN) is a supervised feed-forward network with two hidden layers. The algorithm was tested against two existing datasets. Multiple tests were run where the data was split into 66 percent training data and 33 percent testing data. The NN achieved a test accuracy of about 95 percent consistently on the dataset and the recall was in the range of 92 to 94 percent. The classification results were compared to the ones obtained from a previous algorithm (Drebin) and the strengths and weaknesses of both methods were analyzed. Alex was mentored by Assistant Professor Tzipora Halevi.

Joshua N. Sash

Joshua N. Sash showcased his work, “Determining Accuracy of Code Similarity Programs,” in a poster presentation. He examined a few code similarity programs with potential applications in automated plagiarism detection, for which he devised two strategies, comparing program code directly, and comparing changsets obtained from a source code management system, applied them to program code and revision histories of about 100 students, and obtained encouraging results. Joshua’s work was advised by Assistant Professor Hui Chen.