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Language Intelligence
Natural language processing, text mining, review analysis, semantic modeling, and large language model applications.
Direct PhD Student · Department of Information Systems · University of Haifa
AI for understanding language, emotion, and human experience.
I am Mohammed Kashkoush, a direct PhD student in the Department of Information Systems at the University of Haifa. My research focuses on natural language processing, large language models, synthetic data generation, AI agents and agent orchestration, narrative engagement processes, emotion analysis, and explainable AI.
NLP
LLMs
AI Agents
Emotion Analysis
Explainable AI
About
Research with technical depth and human meaning.
My work sits at the intersection of artificial intelligence, information systems, and human-centered computing. I am interested in building models that not only predict outcomes, but also explain why language, emotions, and narrative experiences matter.
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Agentic AI Systems
AI agents, agent orchestration, synthetic data generation, and intelligent pipelines for scalable research workflows.
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Explainable Human-Centered AI
Emotion analysis, narrative transportation, identification, engagement processes, and interpretable AI models.
Research
Turning text into interpretable insight.
I focus on AI methods that can analyze and explain emotional and narrative signals in text, especially in contexts such as reviews, user experience, and engagement with media content.
Core research interests
My research combines computational modeling and behavioral interpretation. I am especially interested in how LLMs, synthetic annotations, and agent-based workflows can help model complex constructs such as emotion strength, identification, and narrative transportation.
Natural Language Processing
Large Language Models
Synthetic Data
AI Agents
Agent Orchestration
Narrative Transportation
Identification
Emotion Analysis
Explainable AI
Teaching
Teaching experience in algorithms and AI-based systems.
Alongside my research, I have supported students in technical and AI-focused courses, helping them understand both foundations and applied intelligent systems.
Teaching Assistant
Data Structures and Algorithms
Supported students in core algorithmic thinking, data structures, recursion, complexity, and practical problem solving.
Teaching Assistant
Recommendation Systems Based on Artificial Intelligence
Assisted in an AI-focused course covering recommendation systems, personalization, intelligent models, and data-driven decision support.
Publication
Selected publication.
My publication work focuses on explainable emotion analysis and the use of emotion strength for improving rating prediction.
Disentangling Anticipation: Polarity-Aware Emotion Strength for Explainable Rating Prediction
This paper examines polarity-aware emotion strength as part of explainable rating prediction, with a focus on making emotional signals more interpretable in text-based analysis.
Emotion Strength
Rating Prediction
Explainable AI
ACM Publication
Contact
Let’s connect.
For research discussions, academic collaboration, AI projects, or questions about my work, you can contact me directly by email or LinkedIn.
Send a message
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Available for
Academic collaboration, NLP and LLM research discussions, AI agent workflows, synthetic data projects, data analysis, emotion analysis, and explainable AI applications.
Research Collaboration
AI Projects
Data Analysis
NLP
LLM Systems