Meet our research interns who will be developing digital solutions to real-world industry problems
Our Digital Transformation research theme will be hosting three of the University’s brightest students as interns who will be working to develop our research in Expert-AI collaboration for decision-making in project management.
These students were brought onboard as part of the Faculty of Engineering’s Vacation Research Internship Program and will be helping us in understanding our data on stakeholder engagement and developing strategies on how to implement AI tools in practice.
Meet the students, below!
Shrutidhar Pratadia
I am a strategic designer studying a Master of Design Innovation at the University of Sydney. My primary interest lies in applying systems thinking to solve complex problems. I’m passionate about how AI can enhance this process by breaking down large-scale challenges into manageable parts, enabling a more effective strategic approach.
During this internship, I will be designing a practical framework for Expert-AI collaboration within infrastructure project management. The aim is to increase the trust of industry experts in leveraging AI, helping them navigate the inherent complexity and dynamic priorities of their work. The framework will guide them in using AI to make better, evidence-based decisions when facing regulatory, safety, and stakeholder challenges.
My work directly builds upon the Institute’s prior research into Expert-AI collaboration for specific sectors like construction safety and stakeholder engagement. My contribution is to apply a “system of systems” approach and attending to each of those research components to develop a strategic framework that connects them. This takes the prior work from single layers to a cohesive system for project leaders.
For industry, the framework aims to provide a validated process that gives project leaders the confidence to adopt AI-powered analysis. By doing so, it has the potential to make existing project management workflows more efficient and establish a new, more reliable standard for decision-making. For academia, it offers a novel, systems-thinking approach to designing and implementing human-AI collaboration..
During this internship, I will be designing a practical framework for Expert-AI collaboration within infrastructure project management. The aim is to increase the trust of industry experts in leveraging AI, helping them navigate the inherent complexity and dynamic priorities of their work. The framework will guide them in using AI to make better, evidence-based decisions when facing regulatory, safety, and stakeholder challenges.
My work directly builds upon the Institute’s prior research into Expert-AI collaboration for specific sectors like construction safety and stakeholder engagement. My contribution is to apply a “system of systems” approach and attending to each of those research components to develop a strategic framework that connects them. This takes the prior work from single layers to a cohesive system for project leaders.
For industry, the framework aims to provide a validated process that gives project leaders the confidence to adopt AI-powered analysis. By doing so, it has the potential to make existing project management workflows more efficient and establish a new, more reliable standard for decision-making. For academia, it offers a novel, systems-thinking approach to designing and implementing human-AI collaboration..
Jiarui Zhang
I’m Jiarui Zhang. I am currently pursuing a master’s degree in Computer science at the University of Sydney. I hold a bachelor’s degree in Business administration and have a strong interest in sociology, art and philosophy. I am passionate about making abstract ideas concrete and practical. I am very optimistic, adventurous and curious, and especially enjoy exploring the intersection of business, innovation, technology and leadership.
During my internship at the John Grill Project Leadership Institute, I will be engaged in how to enable artificial intelligence to better assist experts in decision-making.
This will entail using retrieval-augmented generations (RAGs) to enhance the performance ability of AI models. In addition to studying specific components, I will also build the front-end and back-end parts of the platform to enable users (especially decision-makers and project leaders) to have meaningful interactions with AI-driven Chatbots.
This work demonstrates the Institute’s focus on complex decision-making and leadership in major projects. With the rapid development of artificial intelligence, effectively integrating it into the decision-making process of expert leaders is both a challenge and an opportunity. By improving AI’s ability to retrieve and answer domain-specific questions, it helps support expert leaders in navigating complex project environments, demonstrating how AI can become a valuable tool for enhancing strategic thinking and informed leadership, which is of great significance to project leaders.
This project significantly reduces the risks that are typically associated with general AI models when handling domain-specific queries. Unlike mainstream AI systems that may provide misleading or inaccurate information in professional environments, this RAG based system generates more reliable and trustworthy outputs. It is more suitable for enterprise or expert decision-making. In some specific fields, it has greatly enhanced the speed and quality of leaders’ decision-making, providing experts and organisations with a practical and efficient decision support tool.
This direction is people-oriented and explores how to make AI more interpretable and credible in leadership environments, thereby enhancing decision-making efficiency. I am particularly interested in extending its application to various industries, including developing AI-driven decision support tools, innovative platforms or intelligent knowledge assistants, enabling future product managers, leaders and organizations to confidently address complex challenges. I believe that enhancing the usability of AI tools is equally important, whether for consumer (C-end), enterprise (B-end), or government (G-end) users. This is not merely about implementing our ideas in the project, but about actively listening to the opinions of stakeholders – understanding user needs and continuously iterating based on real-world feedback to create more inclusive, effective and adaptable solutions.
During my internship at the John Grill Project Leadership Institute, I will be engaged in how to enable artificial intelligence to better assist experts in decision-making.
This will entail using retrieval-augmented generations (RAGs) to enhance the performance ability of AI models. In addition to studying specific components, I will also build the front-end and back-end parts of the platform to enable users (especially decision-makers and project leaders) to have meaningful interactions with AI-driven Chatbots.
This work demonstrates the Institute’s focus on complex decision-making and leadership in major projects. With the rapid development of artificial intelligence, effectively integrating it into the decision-making process of expert leaders is both a challenge and an opportunity. By improving AI’s ability to retrieve and answer domain-specific questions, it helps support expert leaders in navigating complex project environments, demonstrating how AI can become a valuable tool for enhancing strategic thinking and informed leadership, which is of great significance to project leaders.
This project significantly reduces the risks that are typically associated with general AI models when handling domain-specific queries. Unlike mainstream AI systems that may provide misleading or inaccurate information in professional environments, this RAG based system generates more reliable and trustworthy outputs. It is more suitable for enterprise or expert decision-making. In some specific fields, it has greatly enhanced the speed and quality of leaders’ decision-making, providing experts and organisations with a practical and efficient decision support tool.
This direction is people-oriented and explores how to make AI more interpretable and credible in leadership environments, thereby enhancing decision-making efficiency. I am particularly interested in extending its application to various industries, including developing AI-driven decision support tools, innovative platforms or intelligent knowledge assistants, enabling future product managers, leaders and organizations to confidently address complex challenges. I believe that enhancing the usability of AI tools is equally important, whether for consumer (C-end), enterprise (B-end), or government (G-end) users. This is not merely about implementing our ideas in the project, but about actively listening to the opinions of stakeholders – understanding user needs and continuously iterating based on real-world feedback to create more inclusive, effective and adaptable solutions.
We are open to hearing from industry organisations who would be interested in connecting with our students to help investigate research opportunities and develop solutions to your organisation’s problems. If you are interested, please reach out to us via: john-grill.institute@sydney.edu.au.