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  • Sahar Mirhadi

    < Back ​ Sahar Mirhadi University of York ​ iGGi PG Researcher ​ Available for post-PhD position After completing a Master's degree in Positive Psychology and Coaching Psychology, Sahar became intrigued by the potential of games to help individuals deal with challenging times, drawing from her experience of using games to cope with burnout during the COVID-19 pandemic. After joining the IGGI program is 2021, this passion has only developed in research and advocacy work, from being a student rep and conference committee between 2021-2023. In addition to her academic pursuits, Sahar is an accomplished Magic: The Gathering player. She also runs a YouTube channel called the Legacy Gambit, which provides fun and accessible content for the eternal Magic: The Gathering formats. Sahar is also a Safe In Our World Ambassador, a recipient of the Magic: The Gathering New Perspectives Grant for Marginalised Players, and a member of the Birds of Paradise collective. A description of Sahar's research: Sahar's research delves into the multifaceted role of video games in helping individuals cope with personal difficulties. Her first study examined how specific aspects of games can facilitate various coping strategies during challenging times. The findings suggested that games have unique attributes that can assist players in dealing with difficult circumstances and engaging in different coping strategies. Her subsequent research study aims to have a deeper understanding by focusing on specific games with distinct core mechanics and features to uncover more nuanced relationships between different game elements and coping strategies, and to establish how these relationships evolve over time. Her overall aim with these studies aim to provide a comprehensive understanding of the intricate dynamics between video game aspects and coping mechanisms, shedding light on the potential benefits and limitations of video games in supporting individuals facing personal challenges. ​ sm2904@york.ac.uk Email https://linktr.ee/saharmirhadi Mastodon Other links Website https://www.linkedin.com/in/saharmirhadi/ LinkedIn https://x.com/saharmirhadi Twitter Github Supervisors: Dr Alena Denisova Dr Jo Iacovides ​ Themes Player Research Previous Next

  • Clyde: A deep reinforcement learning doom playing agent

    < Back Clyde: A deep reinforcement learning doom playing agent Link ​ Author(s) D Ratcliffe, S Devlin, U Kruschwitz, L Citi Abstract ​ More info TBA ​ Link

  • Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access

    < Back Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access Link ​ Author(s) RJ Spick, JA Walker Abstract ​ More info TBA ​ Link

  • Generating Diverse and Competitive Play-Styles for Strategy Games

    < Back Generating Diverse and Competitive Play-Styles for Strategy Games Link ​ Author(s) D Perez-Liebana, C Guerrero-Romero, A Dockhorn, L Xu, J Hurtado, Dominik Jeurissen Abstract ​ More info TBA ​ Link

  • Dubit Limited

    iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: ​ Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! ​ There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. Dubit Limited

  • Frontiers of GVGAI Planning

    < Back Frontiers of GVGAI Planning Link ​ Author(s) DP Liebana, RD Gaina Abstract ​ More info TBA ​ Link

  • Autoencoding Blade Runner: Reconstructing Films with Artificial Neural Networks

    < Back Autoencoding Blade Runner: Reconstructing Films with Artificial Neural Networks Link ​ Author(s) T Broad, M Grierson Abstract ​ More info TBA ​ Link

  • TAG: Terraforming Mars

    < Back TAG: Terraforming Mars Link ​ Author(s) RD Gaina, J Goodman, D Perez-Liebana Abstract ​ More info TBA ​ Link

  • Introversion Software Limited

    iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: ​ Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! ​ There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. Introversion Software Limited

  • Revealing game dynamics via word embeddings of gameplay data

    < Back Revealing game dynamics via word embeddings of gameplay data Link ​ Author(s) Y Rabii, M Cook Abstract ​ More info TBA ​ Link

  • Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning

    < Back Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning Link ​ Author(s) R Sasso, M Sabatelli, MA Wiering Abstract ​ More info TBA ​ Link

  • Automated motion analysis of adherent cells in monolayer culture

    < Back Automated motion analysis of adherent cells in monolayer culture Link ​ Author(s) Z Zhang, M Bedder, SL Smith, D Walker, S Shabir, J Southgate Abstract ​ More info TBA ​ Link

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