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Lilian Stephanos

MSc Student, Mu Lab

Interests

  • Deep Learning
  • Retrieval-Augmented Generation (RAG)
  • Knowledge Graphs
  • Large Language Models

Education

  • B.Sc. in Computer Science, Specialized in Artificial Intelligence, 2024

    Cairo University

Projects

  • PRP Rebooted: Advancing the State of the Art in FOND Planning
  • PRP Rebooted: Advancing the State of the Art in FOND Planning
  • Discrete Timeseries Analysis

Biography

Pronouns: she/her/hers

I’m an first year MSc student in the School of Computing at Queen’s University, specializing in Artificial Intelligence and supervised by Prof. Christian Muise. My research focuses on Retrieval-Augmented Generation (RAG), with an emphasis on incorporating knowledge graphs to improve retrieval and reasoning with Large Language Models. I hold a B.Sc. in Computer Science from Cairo University, specializing in the Artificial Intelligence Department. My professional background spans computer vision, Large Language models, vision-language models, and applied machine learning, with two years of industry experience.

Recent Publications

  • Predicting The Cop Number Using Machine Learning.
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases. JMI
  • Analysis of Linguistic Effects of Self-Consuming Training. FLLM
  • Life Event Detection in Bank Conversations: An Industry Case Study. CASCON
  • Life Event Detection in Bank Conversations: An Industry Case Study. CASCON
  • L2P: A Python Toolkit for Automated PDDL Model Generation with Large Language Models. PLAN-FM

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