IntelMagik
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    • About Us
    • Contact Us
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  • Home | InteliMagik
  • About Us
  • Contact Us
  • More Projects

About Us

Founder

Maciej Trzaskowski, PhD


Boasting over 15 years of experience as a statistical geneticist spanning extensive analytical space in fields such as psychiatry, oncology, ophthalmology, and infectious diseases. In addition to consulting as InteliMagik, he co-founded Profenso Pty Ltd, and acts as an Adjunct Senior Fellow at the Institute for Molecular Biosciences (IMB, UQ) and as a partner investigator at the ARC-funded Centre for Information Resilience (CIRES, UQ). He is also a visiting scientist at QIMR Berghofer and QUT. His past roles include Head of Research at Max Kelsen and membership on Advisory Board committees for Health and Wellbeing Queensland, the Centre for Quantum Dynamics (Griffith University), and the Australian Academy of Technology & Engineering.


Uniquely, he melds a strong understanding of advanced mathematics and statistics, including Machine Learning and other AI techniques, with an in-depth knowledge of biological and clinical methods. His experience spans national and international speaking, media communication, academic and industry mentoring, serving on advisory boards, addressing business needs, managing budgets and KPIs, mentoring teams, fostering career progression, submitting ethics applications, and navigating regulatory pathways for FDA and TGA approvals, with a particular focus on software as a medical device (SaMD).


Personally, he takes great pride in his professional integrity. Driven by curiosity and creativity, he is conscientious and compassionate, deeply committed to equality, the right to opportunity, and the wellbeing of his colleagues and mentees. He is a skilled negotiator—fair, loyal, and skilled programmer enabling technical leadership. He thinks outside the box, making connections between seemingly disparate fields. Fearless in the face of new challenges, he seizes opportunities as they arise and remains open to unconventional propositions.

Selected Publications

 2023  Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncology. Scientific Reports.


2023 STimage:robust, confident and interpretable models for predicting gene markers from cancer histopathological images, bioRxiv. 


2022   Interpretable AI in Healthcare: Enhancing Fairness, Safety, and Trust. In: Raz, M., Nguyen, T.C., Loh, E. (eds) Artificial Intelligence in Medicine. Springer, Singapore. 


2021 Automated AI labelling of optic nerve head enables new insights into cross-ancestry glaucoma risk and genetic discovery in over 280,000 images from the UK Biobank and Canadian Longitudinal Study on Aging. American Journal of Human Genetics. 


2021 Verifying explainability of a deep learning tissue classifier trained on RNA-seq data.

 

2020 Quantifying uncertainty in deep learning systems. (white paper with AWS). 

 

2019 Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nature Genetics.


Selected Media and Talks

RADIO

  • ABC live interview 
  • 4BC live interview 


NEWSPAPERS/ONLINE

  • genomiQa – Unlocking Whole-Genome Data
  • Brisbane Times; The Sydney Morning Herald; The Age; WA 
  • iTWire: “Max Kelsen grants residency for gene researcher to discover why patients develop severe COVID symptoms” 
  • Brisbane Times: “AI trained to spot disease that sends people blind” 
  • Oncology Republic: “Algorithms need to be able to say ‘I don’t know’” 
  • CRN News: “AWS partner Max Kelsen gets academic nod with machine learning research”
  • Courier Mail in “UQ researchers’ decade-long study pays off” 
  • Brisbane Times in “New depression treatments expected after genetic link identified”  
  • Neuroscience News “44 Genetic Risk Factors for Major Depression Identified” 


INVITED TALKS

2023    ‘pdCUP: From Concept to Product. The lifecycle of SaMD’. STAT7174 Lecture, UQ.

2022     ‘Three pillars for clinical adoption of AI’. Multi-centre talk ACE, CMR, & AIMS.

2022     ‘Safer Deep Learning modelling for multi-omic and single cell applications in cancer genomics’. Institute for Glycomics. Griffith University.

2022     ‘Meet the Experts’. IMNIS REDI Connect. 

2022     ‘CRC-P Immunotherapy Outcomes Prediction’. Industry, Innovation and Science Australia Board Meeting

2022     ‘Challenges implementing AI in clinic’. Global Challenges Retreat, UQ

2021     ‘Algorithmic and Numerical Safety in AI Genomics’. Google ML Internal Workshop, Online Global

2021     ‘Industry position on single cell research’. Panel Member, Oz Single Cell 2021, UQ

2021     ‘Industry Research Career Pathways’. EMCR Career Workshop, UQ

2021     ‘Science Commercialisation’. QIMR Berghofer Biennial Student Retreat

2021     ‘AI Safety in Cancer Research’. QUT School of Computer Science

2021     ‘Research in Industry’. University of Queensland Association of Biomedical Students

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ABN: 71 678 895 666

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