Founder, Nexus X Labs
Fulbright Scholar • MD/PhD Candidate • AI Researcher
Bridging the gap between clinical medicine and artificial intelligence. My work focuses on equitable AI approaches for precision medicine, with a particular interest in ensuring AI tools work safely and effectively for diverse patient populations.

My research bridges the gap between clinical medicine and artificial intelligence, with a focus on fairness, safety, and real-world implementation.
Developed the TRIPOD+LLM guidelines on the publishing of LLM studies in healthcare - accepted in Nature Medicine.
Developed LLM-based pipeline (GPT-4) to analyze pediatric growth charts for abnormalities. Explored varying prompt-engineering strategies.
Implemented 3D CNNs and autoencoders to diagnose ASD from fMRI images.
Conducted qualitative research with 1st generation migrants and developing a data-driven AI-based Precision Medicine framework to mitigate screening barriers.
Proposed and implemented convolutional autoencoders to learn latent representations of cells in unlabelled pathology data.
Completed a technical review of deep learning approaches for histological analysis of lung tissue and produced a report on practical challenges.
Built an intelligent case-based medical e-learning web platform and a Wikipedia-based Q&A system using Named-Entity Recognition.
Evaluated the Stanford CheXpert model on Australian data to explore the role of AI in the triaging of chest X-rays. Proposed an alternative semi-supervised learning approach to address model drift in the Australian context.
Conducted literature review on the role of the immune system in avoiding cancer and the potential for ML to identify new therapeutic pathways. Received feedback stating research was of exceptional quality.
Developed a state-of-the-art multi-modal human-in-the-loop ML approach to automatically detect the presence of breast cancer in Fine Needle Aspirates.
Technical lead developing an intraoperative AI-assisted surgical guidance system to augment visualization of neurovascular fibres during robotic-assisted rectal cancer surgery. Developed labelling pipeline for CNN training.
I combine academic rigor with industry experience, building products that translate cutting-edge AI into practical healthcare solutions.
Developing AI Family History Pedigree Builder leveraging AI Call Agents and LLMs. Built landing page and onboarding tools.
Built AI-enhanced DICOM viewer for Chest XR pathologies. Acquired by GCUH Health System.
Contributed to the development of a frog audio classifier leveraging 1 million frog audio recordings, in collaboration with Vivanti consultants and the Australian Museum.
Instructor for graduate course HST.953 Clinical Data Learning, Visualization, and Deployments.
Developed and delivered a workshop on Deep Learning, Neural Networks, and LLMs for medical residents.
Lectured Predictive Analytics (ML Algorithms) and Statistics Using R.
Delivered tutorials for Artificial Intelligence (Neural Networks) and Web Development.
Organized large-scale holiday workshops, managing a team of 8 tutors teaching disadvantaged high school students in STEM.
Committed to fostering the next generation of AI leaders and shaping global policy for responsible AI development.
Facilitated workshop with MIT undergraduates on AI accountability, transparency, & fairness.
Selected for weekly technical reading group on AI safety research (interpretability, RLHF, etc.).
Selected as 1 of 42 Alumni Ambassadors nationally to coordinate events & liaise with industry partners.
Selected as 1 of 40 Future Leaders across 5 nations. Led team to win 1st prize for climate change policy.
Managed 907 delegates from 78 countries at the University Scholars Leadership Symposium.
A multidisciplinary foundation spanning computer science, medicine, philosophy, and research.
Recognition for academic excellence, research impact, and global leadership.
Massachusetts Institute of Technology
Top 35 students across all Harvard Medical School Masters Degrees
Full tuition/stipend to research AI for bowel cancer screening
University of Tasmania
$7500 AUD, University of Tasmania, awarded to top ICT research student
$67000 AUD Aus Govt. Award to top 100 students nationwide to study in the Asia-Pacific
$5000 AUD awarded to exceptional alumni of Newington College to pursue graduate research
Selected to participate in the AIM Overseas Summer Science program
100% fee waiver for top ranked visiting research scholar
$2000 AUD, Smart Systems & Services Research Group, University of Tasmania
$3000 AUD, University of Tasmania
University of Tasmania
University of Tasmania
University of Tasmania, recognising best ICT Honours thesis
Australian Government Honor recognising the top scholar in each location
University of Tasmania
University of Tasmania
5th Place (Globally) - Proposal for sustainable 1 million man Mars colony, judged by NASA, SpaceX
1st Place - Design contest for a charitable platform
1st Place - Best policy proposal tackling climate change @ MIKTA 40 Future Leaders Camp
2nd Place - Developed an online study tool for ICT students
A full stack engineer proficient in a number of tech stacks.

My research bridges the gap between clinical medicine and artificial intelligence, with a focus on fairness, safety, and real-world implementation.
Developed the TRIPOD+LLM guidelines on the publishing of LLM studies in healthcare - accepted in Nature Medicine.
Developed LLM-based pipeline (GPT-4) to analyze pediatric growth charts for abnormalities. Explored varying prompt-engineering strategies.
Implemented 3D CNNs and autoencoders to diagnose ASD from fMRI images.
Conducted qualitative research with 1st generation migrants and developing a data-driven AI-based Precision Medicine framework to mitigate screening barriers.
Proposed and implemented convolutional autoencoders to learn latent representations of cells in unlabelled pathology data.
Completed a technical review of deep learning approaches for histological analysis of lung tissue and produced a report on practical challenges.
Built an intelligent case-based medical e-learning web platform and a Wikipedia-based Q&A system using Named-Entity Recognition.
Evaluated the Stanford CheXpert model on Australian data to explore the role of AI in the triaging of chest X-rays. Proposed an alternative semi-supervised learning approach to address model drift in the Australian context.
Conducted literature review on the role of the immune system in avoiding cancer and the potential for ML to identify new therapeutic pathways. Received feedback stating research was of exceptional quality.
Developed a state-of-the-art multi-modal human-in-the-loop ML approach to automatically detect the presence of breast cancer in Fine Needle Aspirates.
Technical lead developing an intraoperative AI-assisted surgical guidance system to augment visualization of neurovascular fibres during robotic-assisted rectal cancer surgery. Developed labelling pipeline for CNN training.
I combine academic rigor with industry experience, building products that translate cutting-edge AI into practical healthcare solutions.
Developing AI Family History Pedigree Builder leveraging AI Call Agents and LLMs. Built landing page and onboarding tools.
Built AI-enhanced DICOM viewer for Chest XR pathologies. Acquired by GCUH Health System.
Contributed to the development of a frog audio classifier leveraging 1 million frog audio recordings, in collaboration with Vivanti consultants and the Australian Museum.
Developed computer vision projects for Enterprise & Government clients. Built internal IP for data labelling.
Instructor for graduate course HST.953 Clinical Data Learning, Visualization, and Deployments.
Developed and delivered a workshop on Deep Learning, Neural Networks, and LLMs for medical residents.
Lectured Predictive Analytics (ML Algorithms) and Statistics Using R.
Delivered tutorials for Artificial Intelligence (Neural Networks) and Web Development.
Organized large-scale holiday workshops, managing a team of 8 tutors teaching disadvantaged high school students in STEM.
Committed to fostering the next generation of AI leaders and shaping global policy for responsible AI development.
Facilitated workshop with MIT undergraduates on AI accountability, transparency, & fairness.
Selected for weekly technical reading group on AI safety research (interpretability, RLHF, etc.).
Selected as 1 of 42 Alumni Ambassadors nationally to coordinate events & liaise with industry partners.
Selected as 1 of 40 Future Leaders across 5 nations. Led team to win 1st prize for climate change policy.
Managed 907 delegates from 78 countries at the University Scholars Leadership Symposium.
A multidisciplinary foundation spanning computer science, medicine, philosophy, and research.
Recognition for academic excellence, research impact, and global leadership.
Massachusetts Institute of Technology
Top 35 students across all Harvard Medical School Masters Degrees
Full tuition/stipend to research AI for bowel cancer screening
University of Tasmania
$7500 AUD, University of Tasmania, awarded to top ICT research student
$67000 AUD Aus Govt. Award to top 100 students nationwide to study in the Asia-Pacific
$5000 AUD awarded to exceptional alumni of Newington College to pursue graduate research
Selected to participate in the AIM Overseas Summer Science program
100% fee waiver for top ranked visiting research scholar
$2000 AUD, Smart Systems & Services Research Group, University of Tasmania
$3000 AUD, University of Tasmania
University of Tasmania
University of Tasmania
University of Tasmania, recognising best ICT Honours thesis
Australian Government Honor recognising the top scholar in each location
University of Tasmania
University of Tasmania
5th Place (Globally) - Proposal for sustainable 1 million man Mars colony, judged by NASA, SpaceX
1st Place - Design contest for a charitable platform
1st Place - Best policy proposal tackling climate change @ MIKTA 40 Future Leaders Camp
2nd Place - Developed an online study tool for ICT students
A full stack engineer proficient in a number of tech stacks.