COEIT Interdisciplinary Proposal Awards

The College of Engineering and Information Technology (COEIT) announces the awardees of the COEIT Interdisciplinary Proposals (CIP). This competition is open to all COEIT tenured and tenure-track faculty, instructional faculty, and research faculty. Proposals for funding include collaborative groups across departments. This program is designed to cross pollinate ideas for use-inspired research, fostering collaborations across departments and units within COEIT, and preparing for future external grant proposals or foundation funding. In selecting the awardees, emphasis is on interdisciplinary teams and innovative ideas to increase future external funding.

2025 COEIT Interdisciplinary Proposal awards

COHERE: Collaborative Optimization of Human Engagement and Robot Effectiveness; Ramana Vinjamuri (Computer Science and Electrical Engineering), Andrea Kleinsmith (Information Systems), Christine Mallinson (Language, Literacy & Culture Program), and Charissa Cheah (Psychology)

Advanced Skin Assessments for Customized Touch Interactions; Janelle Clark (Mechanical Engineering) and Dong Li (Computer Science and Electrical Engineering)

Integrating Cybersecurity Concepts into Introductory Engineering Education; Alan Sherman (Computer Science and Electrical Engineering) and Maria Sanchez (Mechanical Engineering)

Towards AI-facilitated Collaborative Visual Sensemaking; Rebecca Williams (Computer Science and Electrical Engineering), Sanorita Dey (Computer Science and Electrical Engineering), and Karen Chen (Information Systems)

Predictive Design of Mycelial Materials; Mark Marten (Chemical, Biochemical, and Environmental Engineering) and Deepa Madan (Mechanical Engineering)

A Multidiscplinary Approach to Developing a Community-driven Framework for Sensorization in Assisted Living Communities; Roberto Yus (Computer Science and Electrical Engineering) and Tera Reynolds (Information Systems)

A Posteriori Tests of Invariance-embedded Machine Learning Models for Meso-scale Hurricane Boundary Layer Flows; Meilin Yu (Mechanical Engineering) and Tim Oates (Computer Science and Electrical Engineering)

Evaluating the Impact of Pathogen-Mediated Infective Endocarditis on Bioprosthetic Aortic Valve Function; Corine Jackman Burden (Chemical, Biochemical, and Environmental Engineering) and Sayantan Bhattacharya (Mechanical Engineering)

Secure and Verifiable Federated Unlearning for Scientific AI Models; Keke Chen (Computer Science and Electrical Engineering) and Jianwu Wang (Information Systems)

Developing Thermally Stable Energy Materials Using Physics-Based ML Models; Alok Ghanekar (Mechanical Engineering) and Rajasekhar Anguluri (Computer Science and Electrical Engineering)

Investigating the Social and Affective Aspects of Large-Language Model-based Augmentative and Alternative Communication Systems; Foad Hamidi (Information Systems) and Lara Martin (Computer Science and Electrical Engineering)

Automating Cybersecurity Compliance in Manufacturing Using Data-Driven Digital Twins; Karuna Joshi (Information Systems) and Nilanjan Banerjee (Computer Science and Electrical Engineering)

Cellular Force Generation on Extracellular Matrix Mimetic Surfaces; Molly Mollica (Mechanical Engineering) and Jorge Almodovar (Chemical, Biochemical, and Environmental Engineering)

The UMBC Ethical Software Lab; Mohammad Samarah (Information Systems); Melissa Sahl (Information Systems), Abhijit Dutt Computer Science and Electrical Engineering), Charissa Cheah (Psychology)

Microfluidic Chip Design Using Large Language Models; Neha Raikar (Chemical, Biochemical, and Environmental Engineering) and Nilanjan Banerjee (Computer Science and Electrical Engineering)

The role of Interlimb Coordination and Human-Robot Symbiosis in Dance Interventions for Mental Health and Wellbeing; Ramana Vinjamuri (Computer Science and Electrical Engineering), Andrea Kleinsmith (Information Systems), and Ann Clemmensen (Dance)

Examining the Impact of Role Models in Building Self-Efficacy and Career-Adaptability of Underrepresented Students in STEM Disciplines; Sanorita Dey (Computer Science and Information Technology and Maria  Sanchez (Mechanical Engineering)

Substrate and Defect Engineering for More Efficient Photovoltaic Systems; Ergun Simsek (Computer Science and Electrical Engineering) and Özgür Çapraz (Chemical, Biochemical, and Environmental Engineering)

Neurosymbolic AI for Scientific Discovery; Tyler R. Josephson (Chemical, Biochemical, and Environmental Engineering) and Jianwu Wang (Information Systems)

Physics-Constrained Machine Learning-Enabled Efficient Grain Growth Modeling for 3D Printed Metals; Ye Lu (Mechanical Engineering) and Houbing Herbert Song (Information Systems)

9/5/2025

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