1 citations · 2 across the 11 of their papers we have counts for
11 papers
An Approach for Embedding-Guided Function Reuse Detection in Embedded C Software
A A Talha Talukder, Omar Alam, Akramul Azim
Reusing embedded software functions across products is economically valuable but technically difficult: the same functionality implemented for two different microcontroller platfor…
FedChronos: Federated Fine-Tuning of Time-Series Foundation Models for Privacy-Preserving Commodity Price Forecasting
Amit Sharma, Nitin Auluck, Akramul Azim
Time-series foundation models (TSFMs) such as Chronos have demonstrated strong forecasting capabilities across domains, yet adapting them to institutionally fragmented settings, wh…
An Empirical Evaluation of LLM-Based Approaches for Code Vulnerability Detection: RAG, SFT, and Dual-Agent Systems
Md Hasan Saju, Maher Muhtadi, Akramul Azim
The rapid advancement of Large Language Models (LLMs) presents new opportunities for automated software vulnerability detection, a crucial task in securing modern codebases. This p…
SynRAG: A Large Language Model Framework for Executable Query Generation in Heterogeneous SIEM System
Md Hasan Saju, Austin Page, Akramul Azim +3
Security Information and Event Management (SIEM) systems are essential for large enterprises to monitor their IT infrastructure by ingesting and analyzing millions of logs and even…
From HNSW to Information-Theoretic Binarization: Rethinking the Architecture of Scalable Vector Search
Seyed Moein Abtahi, Majid Fekri, Tara Khani +1
Modern semantic search and retrieval-augmented generation (RAG) systems rely predominantly on in-memory approximate nearest neighbor (ANN) indexes over high-precision floating-poin…
Securing LLM-Generated Embedded Firmware through AI Agent-Driven Validation and Patching
Seyed Moein Abtahi, Akramul Azim
Large Language Models (LLMs) show promise in generating firmware for embedded systems, but often introduce security flaws and fail to meet real-time performance constraints. This p…
WALL: A Web Application for Automated Quality Assurance using Large Language Models
Seyed Moein Abtahi, Akramul Azim
As software projects become increasingly complex, the volume and variety of issues in code files have grown substantially. Addressing this challenge requires efficient issue detect…
Algorithmic Approaches to Enhance Safety in Autonomous Vehicles: Minimizing Lane Changes and Merging
Seyed Moein Abtahi, Akramul Azim
The rapid advancements in autonomous vehicle (AV) technology promise enhanced safety and operational efficiency. However, frequent lane changes and merging maneuvers continue to po…
Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements
Seyed Moein Abtahi, Akramul Azim
This study examined code issue detection and revision automation by integrating Large Language Models (LLMs) such as OpenAI's GPT-3.5 Turbo and GPT-4o into software development wor…
Agile Reinforcement Learning for Real-Time Task Scheduling in Edge Computing
Amin Avan, Akramul Azim, Qusay Mahmoud
Soft real-time applications are becoming increasingly complex, posing significant challenges for scheduling offloaded tasks in edge computing environments while meeting task timing…
Uncertainty measurement for complex event prediction in safety-critical systems
Maria J. P. Peixoto, Akramul Azim
Complex events originate from other primitive events combined according to defined patterns and rules. Instead of using specialists' manual work to compose the model rules, we use…