Nawar Wali

Nawar Wali

Doctoral Student at Virginia Tech

Posts by Collection

portfolio

ECG Filter Design and Testing

Published:

Designed and tested filter components in a group project to construct an accurate ECG response system.

Audio Visual Analyzer

Published:

Designed an analyzer to convert audio input into visual representations using hardware components.

Particle Filter Localization

Published:

Implemented a robotic localization system using ROS, Gazebo, and CUDA for tracking positions using laser sensor data.

Where2Park IoT System

Published:

Built an IoT mesh network with Zigbee-connected metal detectors for real-time parking availability tracking.

publications

Enhancing Temporal Link Prediction with HierTKG.

Published in arXiv, 2024

The rapid spread of misinformation on social media, especially during crises, challenges public decision-making. To address this, we propose HierTKG, a framework combining Temporal Graph Networks (TGN) and hierarchical pooling (DiffPool) to model rumor dynamics across temporal and structural scales.

Recommended citation: Mariam Almutairi, Melike Yıldız Akta¸s, Nawar Wali, Shutonu Mitra, and Dawei Zhou. 2024. Enhancing Temporal Link Prediction with HierTKG. doi.org/10.48550/arXiv.2412.12385
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Machine Learning Insights into Academic Success in CS3: The Role of Mathematics and CS Coursework

Published in ACM Capital Region Celebration of Women in Computing, Washington D.C., United States, 2025

This research explores how we can leverage only CS and math coursework data to better support students in CS3, without relying on sensitive information like demographics.

Recommended citation: Nawar Wali and Sara Hooshangi. 2025. Machine Learning Insights into Academic Success in CS3: The Role of Mathematics and CS Coursework. In ACM Capital Region Celebration of Women in Computing, Washington D.C.

Transfer Students in Computer Science: Examining Barriers, Success Metrics, and Research Gaps

Published in Proceedings of ITiCSE 2025, Nijmegen, Netherlands, 2025

Transfer students play an important role in enhancing diversity within computer science programs. As first-generation college students, minorities, rural residents, and individuals from low-income backgrounds, transfer students represent a demographic critical to fostering innovation and inclusion in the field. However, while significant research has been conducted on transfer students in STEM disciplines, studies specifically addressing their experiences in computer science remain limited. This paper presents a preliminary systematic review of the literature to explore the challenges, successes, and gaps in the support of transfer students in computer science.

Recommended citation: Nawar Wali and Sara Hooshangi. 2025. Transfer Students in Computer Science: Examining Barriers, Success Metrics, and Research Gaps. In *Proceedings of ITiCSE 2025*. DOI:10.1145/3724363.3729118.
Download Paper | Download Slides

Transfer Student Success in CS: Modeling Pathways and Outcomes

Published in ICER, 2025

My dissertation focuses on understanding the experiences of transfer students in computer science (CS), identifying how institutions can better support them, and uncovering emerging themes to conceptualize this student population.

Recommended citation: Nawar Wali. 2025. Transfer Student Success in CS: Modeling Pathways and Outcomes. In Proceedings of ICER 2025, Charlottesville, Virginia, USA.

Diversity in Computer Science Through a Global Lens

Published in IEEE Frontiers in Education Conference (FIE), Nashville, Tennessee, USA, 2025

A global exploration of gender diversity in computer science, based on a systematic review of 260 research papers across regions.

Recommended citation: Nawar Wali and Sara Hooshangi. 2025. Diversity in Computer Science Through a Global Lens. In IEEE Frontiers in Education Conference (FIE), Nashville, TN.

talks

teaching