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Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A SurveyD.Y. Liu, A. Joshi, P. DawsonPreprint · 2026 · Narrative Theory & LLMsAccepted for publication in Artificial Intelligence Review (Springer) — arXiv preprint arXiv:2602.15851A survey investigating how narrative theories are applied through large language models in story generation and comprehension tasks. Categorizes NLP research using narratological distinctions and finds that narrative sources extend beyond traditional literature, theoretical synthesis and validation are achievable outcomes, and generation work lags in theoretical application and exploration of non-fiction narratives.MPhil Student · UNSW NLPI'm an MPhil student at the University of New South Wales (UNSW), researching the intersection of narrative theory, natural language processing, and large language models. I'm part of the UNSW NLP research group.My work applies narratological frameworks to the design and evaluation of story-generation systems, and explores reinforcement learning methods for producing more coherent, theory-informed narratives. I also collaborate on research applying VR and generative AI to filmmaking education.The Storytelling Machine: LLMs as Computational Models of NarrativeMPhil thesis · UNSW NLPI study LLMs as computational models of narrative, drawing on narrative theory to develop methods for story generation, understanding, and interpretability.SupervisorsDr Aditya Joshi (primary)Prof Paul DawsonDr Sebastian Sequoiah-GraysonRetell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story RetellingD.Y. Liu, X. Muston, D. Srirag, A. Joshi, S. Sequoiah-GraysonConference · 2026 · Narrative Theory & LLMsProceedings of INLG 2026Introduces RRR, a reinforcement learning approach combining narratology with scalar narrativity to teach story structure to LLMs. Using the TimeTravel dataset extended with human-annotated narrative stages, the method employs d-RLAIF to create training signals without reference outputs, outperforming few-shot and SFT baselines in logic, rationality, and completeness.NarraNeurons: Narrativity-Sensitive Neurons in Open-Weight LLMsIn progress · open-weight LLMsIdentifying narrativity-sensitive neurons in open-weight LLMs via ablation studies, showing they play a distinct, measurable role in narrative representation and generation.ResearchI'm obsessed with how language and narrative shape the way we think, perceive, and understand ourselves and others. I am also a filmmaker, which feeds my interest in storytelling and collaborative work. My research studies LLMs as computational models of narrative, drawing on narrative theory, and I am keen to explore connections with cognitive science. My current work is driven by the underlying question of how LLMs model storytelling. I am open to research directions and collaborations in these areas.Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A SurveyD.Y. Liu, A. Joshi, P. DawsonPreprint · 2026 · Narrative Theory & LLMsAccepted for publication in Artificial Intelligence Review (Springer) — arXiv preprint arXiv:2602.15851A survey investigating how narrative theories are applied through large language models in story generation and comprehension tasks. Categorizes NLP research using narratological distinctions and finds that narrative sources extend beyond traditional literature, theoretical synthesis and validation are achievable outcomes, and generation work lags in theoretical application and exploration of non-fiction narratives.MPhil Student · UNSW NLPI'm an MPhil student at the University of New South Wales (UNSW), researching the intersection of narrative theory, natural language processing, and large language models. I'm part of the UNSW NLP research group.My work applies narratological frameworks to the design and evaluation of story-generation systems, and explores reinforcement learning methods for producing more coherent, theory-informed narratives. I also collaborate on research applying VR and generative AI to filmmaking education.The Storytelling Machine: LLMs as Computational Models of NarrativeMPhil thesis · UNSW NLPI study LLMs as computational models of narrative, drawing on narrative theory to develop methods for story generation, understanding, and interpretability.SupervisorsDr Aditya Joshi (primary)Prof Paul DawsonDr Sebastian Sequoiah-GraysonRetell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story RetellingD.Y. Liu, X. Muston, D. Srirag, A. Joshi, S. Sequoiah-GraysonConference · 2026 · Narrative Theory & LLMsProceedings of INLG 2026Introduces RRR, a reinforcement learning approach combining narratology with scalar narrativity to teach story structure to LLMs. Using the TimeTravel dataset extended with human-annotated narrative stages, the method employs d-RLAIF to create training signals without reference outputs, outperforming few-shot and SFT baselines in logic, rationality, and completeness.NarraNeurons: Narrativity-Sensitive Neurons in Open-Weight LLMsIn progress · open-weight LLMsIdentifying narrativity-sensitive neurons in open-weight LLMs via ablation studies, showing they play a distinct, measurable role in narrative representation and generation.ResearchI'm obsessed with how language and narrative shape the way we think, perceive, and understand ourselves and others. I am also a filmmaker, which feeds my interest in storytelling and collaborative work. My research studies LLMs as computational models of narrative, drawing on narrative theory, and I am keen to explore connections with cognitive science. My current work is driven by the underlying question of how LLMs model storytelling. I am open to research directions and collaborations in these areas.Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A SurveyD.Y. Liu, A. Joshi, P. DawsonPreprint · 2026 · Narrative Theory & LLMsAccepted for publication in Artificial Intelligence Review (Springer) — arXiv preprint arXiv:2602.15851A survey investigating how narrative theories are applied through large language models in story generation and comprehension tasks. Categorizes NLP research using narratological distinctions and finds that narrative sources extend beyond traditional literature, theoretical synthesis and validation are achievable outcomes, and generation work lags in theoretical application and exploration of non-fiction narratives.MPhil Student · UNSW NLPI'm an MPhil student at the University of New South Wales (UNSW), researching the intersection of narrative theory, natural language processing, and large language models. I'm part of the UNSW NLP research group.My work applies narratological frameworks to the design and evaluation of story-generation systems, and explores reinforcement learning methods for producing more coherent, theory-informed narratives. I also collaborate on research applying VR and generative AI to filmmaking education.The Storytelling Machine: LLMs as Computational Models of NarrativeMPhil thesis · UNSW NLPI study LLMs as computational models of narrative, drawing on narrative theory to develop methods for story generation, understanding, and interpretability.SupervisorsDr Aditya Joshi (primary)Prof Paul DawsonDr Sebastian Sequoiah-GraysonRetell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story RetellingD.Y. Liu, X. Muston, D. Srirag, A. Joshi, S. Sequoiah-GraysonConference · 2026 · Narrative Theory & LLMsProceedings of INLG 2026Introduces RRR, a reinforcement learning approach combining narratology with scalar narrativity to teach story structure to LLMs. Using the TimeTravel dataset extended with human-annotated narrative stages, the method employs d-RLAIF to create training signals without reference outputs, outperforming few-shot and SFT baselines in logic, rationality, and completeness.NarraNeurons: Narrativity-Sensitive Neurons in Open-Weight LLMsIn progress · open-weight LLMsIdentifying narrativity-sensitive neurons in open-weight LLMs via ablation studies, showing they play a distinct, measurable role in narrative representation and generation.ResearchI'm obsessed with how language and narrative shape the way we think, perceive, and understand ourselves and others. I am also a filmmaker, which feeds my interest in storytelling and collaborative work. My research studies LLMs as computational models of narrative, drawing on narrative theory, and I am keen to explore connections with cognitive science. My current work is driven by the underlying question of how LLMs model storytelling. I am open to research directions and collaborations in these areas. Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A SurveyD.Y. Liu, A. Joshi, P. DawsonPreprint · 2026 · Narrative Theory & LLMsAccepted for publication in Artificial Intelligence Review (Springer) — arXiv preprint arXiv:2602.15851A survey investigating how narrative theories are applied through large language models in story generation and comprehension tasks. Categorizes NLP research using narratological distinctions and finds that narrative sources extend beyond traditional literature, theoretical synthesis and validation are achievable outcomes, and generation work lags in theoretical application and exploration of non-fiction narratives.MPhil Student · UNSW NLPI'm an MPhil student at the University of New South Wales (UNSW), researching the intersection of narrative theory, natural language processing, and large language models. I'm part of the UNSW NLP research group.My work applies narratological frameworks to the design and evaluation of story-generation systems, and explores reinforcement learning methods for producing more coherent, theory-informed narratives. I also collaborate on research applying VR and generative AI to filmmaking education.The Storytelling Machine: LLMs as Computational Models of NarrativeMPhil thesis · UNSW NLPI study LLMs as computational models of narrative, drawing on narrative theory to develop methods for story generation, understanding, and interpretability.SupervisorsDr Aditya Joshi (primary)Prof Paul DawsonDr Sebastian Sequoiah-GraysonRetell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story RetellingD.Y. Liu, X. Muston, D. Srirag, A. Joshi, S. Sequoiah-GraysonConference · 2026 · Narrative Theory & LLMsProceedings of INLG 2026Introduces RRR, a reinforcement learning approach combining narratology with scalar narrativity to teach story structure to LLMs. Using the TimeTravel dataset extended with human-annotated narrative stages, the method employs d-RLAIF to create training signals without reference outputs, outperforming few-shot and SFT baselines in logic, rationality, and completeness.NarraNeurons: Narrativity-Sensitive Neurons in Open-Weight LLMsIn progress · open-weight LLMsIdentifying narrativity-sensitive neurons in open-weight LLMs via ablation studies, showing they play a distinct, measurable role in narrative representation and generation.ResearchI'm obsessed with how language and narrative shape the way we think, perceive, and understand ourselves and others. I am also a filmmaker, which feeds my interest in storytelling and collaborative work. My research studies LLMs as computational models of narrative, drawing on narrative theory, and I am keen to explore connections with cognitive science. My current work is driven by the underlying question of how LLMs model storytelling. I am open to research directions and collaborations in these areas.Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A SurveyD.Y. Liu, A. Joshi, P. DawsonPreprint · 2026 · Narrative Theory & LLMsAccepted for publication in Artificial Intelligence Review (Springer) — arXiv preprint arXiv:2602.15851A survey investigating how narrative theories are applied through large language models in story generation and comprehension tasks. Categorizes NLP research using narratological distinctions and finds that narrative sources extend beyond traditional literature, theoretical synthesis and validation are achievable outcomes, and generation work lags in theoretical application and exploration of non-fiction narratives.MPhil Student · UNSW NLPI'm an MPhil student at the University of New South Wales (UNSW), researching the intersection of narrative theory, natural language processing, and large language models. I'm part of the UNSW NLP research group.My work applies narratological frameworks to the design and evaluation of story-generation systems, and explores reinforcement learning methods for producing more coherent, theory-informed narratives. I also collaborate on research applying VR and generative AI to filmmaking education.The Storytelling Machine: LLMs as Computational Models of NarrativeMPhil thesis · UNSW NLPI study LLMs as computational models of narrative, drawing on narrative theory to develop methods for story generation, understanding, and interpretability.SupervisorsDr Aditya Joshi (primary)Prof Paul DawsonDr Sebastian Sequoiah-GraysonRetell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story RetellingD.Y. Liu, X. Muston, D. Srirag, A. Joshi, S. Sequoiah-GraysonConference · 2026 · Narrative Theory & LLMsProceedings of INLG 2026Introduces RRR, a reinforcement learning approach combining narratology with scalar narrativity to teach story structure to LLMs. Using the TimeTravel dataset extended with human-annotated narrative stages, the method employs d-RLAIF to create training signals without reference outputs, outperforming few-shot and SFT baselines in logic, rationality, and completeness.NarraNeurons: Narrativity-Sensitive Neurons in Open-Weight LLMsIn progress · open-weight LLMsIdentifying narrativity-sensitive neurons in open-weight LLMs via ablation studies, showing they play a distinct, measurable role in narrative representation and generation.ResearchI'm obsessed with how language and narrative shape the way we think, perceive, and understand ourselves and others. I am also a filmmaker, which feeds my interest in storytelling and collaborative work. My research studies LLMs as computational models of narrative, drawing on narrative theory, and I am keen to explore connections with cognitive science. My current work is driven by the underlying question of how LLMs model storytelling. I am open to research directions and collaborations in these areas.Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A SurveyD.Y. Liu, A. Joshi, P. DawsonPreprint · 2026 · Narrative Theory & LLMsAccepted for publication in Artificial Intelligence Review (Springer) — arXiv preprint arXiv:2602.15851A survey investigating how narrative theories are applied through large language models in story generation and comprehension tasks. Categorizes NLP research using narratological distinctions and finds that narrative sources extend beyond traditional literature, theoretical synthesis and validation are achievable outcomes, and generation work lags in theoretical application and exploration of non-fiction narratives.MPhil Student · UNSW NLPI'm an MPhil student at the University of New South Wales (UNSW), researching the intersection of narrative theory, natural language processing, and large language models. I'm part of the UNSW NLP research group.My work applies narratological frameworks to the design and evaluation of story-generation systems, and explores reinforcement learning methods for producing more coherent, theory-informed narratives. I also collaborate on research applying VR and generative AI to filmmaking education.The Storytelling Machine: LLMs as Computational Models of NarrativeMPhil thesis · UNSW NLPI study LLMs as computational models of narrative, drawing on narrative theory to develop methods for story generation, understanding, and interpretability.SupervisorsDr Aditya Joshi (primary)Prof Paul DawsonDr Sebastian Sequoiah-GraysonRetell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story RetellingD.Y. Liu, X. Muston, D. Srirag, A. Joshi, S. Sequoiah-GraysonConference · 2026 · Narrative Theory & LLMsProceedings of INLG 2026Introduces RRR, a reinforcement learning approach combining narratology with scalar narrativity to teach story structure to LLMs. Using the TimeTravel dataset extended with human-annotated narrative stages, the method employs d-RLAIF to create training signals without reference outputs, outperforming few-shot and SFT baselines in logic, rationality, and completeness.NarraNeurons: Narrativity-Sensitive Neurons in Open-Weight LLMsIn progress · open-weight LLMsIdentifying narrativity-sensitive neurons in open-weight LLMs via ablation studies, showing they play a distinct, measurable role in narrative representation and generation.ResearchI'm obsessed with how language and narrative shape the way we think, perceive, and understand ourselves and others. I am also a filmmaker, which feeds my interest in storytelling and collaborative work. My research studies LLMs as computational models of narrative, drawing on narrative theory, and I am keen to explore connections with cognitive science. My current work is driven by the underlying question of how LLMs model storytelling. I am open to research directions and collaborations in these areas. Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time.Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time.Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time.Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time.Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time. Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time.Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time.Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time.Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time.Filmmaking Education Using Virtual Reality and Generative AI for Real-Time Feedback in Simulated EnvironmentsA. Darejeh, D. Liu, S. MashayekhConference · 2025 · AI in Filmmaking Education2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)Explores the use of virtual reality and generative AI to deliver real-time feedback to filmmaking students within simulated production environments.Metaverse and Virtual Reality Integration in Filmmaking Education: Applications in Cinematography and Artificial Intelligence FeedbackD. Liu, A. Darejeh, S.M.E. SepasgozarBook Chapter · 2025 · AI in Filmmaking EducationMetaverse, Generative AI, and Brain–Computer Interfaces (book chapter)A book chapter examining how metaverse and VR technologies integrate with AI-driven feedback systems in cinematography education.Scholarships & recognitionAwards supporting the MPhil at University of New South Wales (UNSW), in the UNSW NLP group.Research Training Program (RTP) Scholarship — UNSW, 2025–2027Domestic Research Training Grant (DRTG) — UNSW, 2026STEMM Champion — UNSW STEMM Champions Program, 2026Taste of Research Scholarship — UNSW, 2024AppointmentsTeaching and part-time engineering work alongside the MPhil.Casual Academic · UNSW · 2025–PresentI tutor across Computer Science and Engineering, and Arts and Media.Data Structures and AlgorithmsScreen Production IIFull Stack Software Engineer · Arludo · 2023–PresentI develop and maintain features for a digital education portal using React and AWS, part-time. COLOR 16019
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