Ahmad Farooq
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Graduate Research and Teaching Assistant
Also affiliated: University of Kashmir (2024)
Graduate Student Researcher
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Ahmad Farooq's research centers on the application of Reinforcement Learning (RL) and Multi-Agent Systems for controlling autonomous robots in unknown environments. His work addresses challenges in dynamic adaptation, collaborative engagement, and decision-making under uncertainty. He also investigates learning-based perception for robot control in these settings. Concurrently, Farooq explores Natural Language Processing (NLP) for advancing text summarization, focusing on extractive and abstractive techniques. He aims to improve these methods by integrating knowledge from sources such as knowledge graphs and temporal knowledge representations. His research network includes collaborator Kamran Iqbal from the University of Arkansas at Little Rock, with whom he shares two publications. Farooq has authored eight publications with 76 citations and an h-index of 2.
Metrics
- h-index: 2
- Publications: 8
- Citations: 80
Selected Publications
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Formal Verification of Learned Multi-Agent Communication Policies via Decision Tree Distillation (2026)arXiv (Cornell University) OpenAlex
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Reimagining Peer Review Process Through Multi-Agent Mechanism Design (2026)
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Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction (2025)
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Towards Transparent Ethical AI: A Roadmap for Trustworthy Robotic Systems (2025)
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MIND-SBERT: An Explainable and Trustworthy Article Retrieval and Summarization System (2025)
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A Survey of Reinforcement Learning for Optimization in Automation (2024)
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Abstractive text summarization: State of the art, challenges, and improvements (2024)
Collaboration Network
Top Collaborators
- Towards Transparent Ethical AI: A Roadmap for Trustworthy Robotic Systems
- Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction
- Abstractive text summarization: State of the art, challenges, and improvements
- Abstractive text summarization: State of the art, challenges, and improvements
- Reimagining Peer Review Process Through Multi-Agent Mechanism Design
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