Md. Mahir Ashhab

About Me

I am a 2nd year Ph.D. student in Computer Science at the University of Virginia, focusing on low-latency network protocols (L4S) and real-time media systems (WebRTC). My research evaluates congestion control and end-to-end performance in multi-site testbeds.

Previously, I worked on memory management for LLM inference workloads, edge-cloud optimization, and NLP for social media content moderation. I am passionate about designing scalable, high-performance systems and applying them to real-world streaming and media applications.

Research Interests

• Low-Latency Network Protocols & Congestion Control (e.g., L4S)
• Real-Time Media Systems (WebRTC)
• Edge & Cloud Computing for Streaming Systems
• Memory Management and Caching for LLM Workloads
• Distributed Systems & Resource Optimization

Selected Projects

• PhD Research – Low-Latency Transport & WebRTC — Evaluating L4S congestion control in multi-site testbeds and analyzing end-to-end performance of WebRTC under varying network conditions.
• Lookahead Caching for Latency-Sensitive LLM Inference — Designed a caching policy improving memory reuse and latency in large-scale inference workloads.
• Laptop Components Classification for E-Waste Management — Built a labeled dataset and CNN pipeline for automated component classification.
• Neural Abstractive Text Summarization — Evaluated sequence-to-sequence models for generating high-quality abstractive summaries.
• Human-in-the-Loop Annotation for GitHub Comment Classification — Studied the impact of human feedback on improving LLM classification accuracy.

Selected Publications & Presentations

• Poster: ECN-based Congestion Control for WebRTC IMC 2025 – ACM Internet Measurement Conference 2025, Presented research on low-latency performance in real-time media.
• An Extensive Photographic Dataset to Classify Laptop Components for Automating E-Waste Management
  Data in Brief, Elsevier, Volume 57, 2023 – Accepted and Published
• A Comparative Analysis of Deep Learning Approaches in Bangla Document Categorization
  ICCIT 2023 – 26th International Conference on Computer and Information Technology, ISBN: 979-8-3503-5901-5 – Accepted and Published
• Detecting Pneumonia from X-Ray Images Using Deep Convolutional Neural Networks
  IBDAP 2023 – 4th International Conference on Big Data Analytics and Practices, ISBN: 979-8-3503-0019-2 – Accepted and Published
• An Empirical Study to Analyze the Impact of Instagram on Students’ Academic Results
  TENSYMP 2020 – IEEE Region 10 Symposium, ISSN: 2642-6102 – Accepted and Published
• Execution Delay-aware Task Assignment in Mobile Edge Cloud and Internet Cloud
  STI 2019 – International Conference on Sustainable Technologies for Industry 4.0, ISBN: 978-1-7281-6099-3 – Accepted and Published

📚 View all publications on Google Scholar

Latest News

• October 2025: Presented my poster ECN based Congestion Control for WebRTC at ACM Internet Measurement Conference (IMC) 2025. Huge thanks to the IMC organizers for the travel grant support!
• October 2025: Qualifying Examination Proposal completed. Up next: the Qual Defense
• January 2025: Started working with Professor Hyojoon Kim on L4S deployment and congestion control research at UVA.
• August 2024: Officially started my Ph.D. at the University of Virginia!

CV & Contact

📄 View my CV
📧 Email: ftm2nu [at] virginia.edu
🔗 GitHub | LinkedIn