Speakers
Vipin Asopa, PhD FRCS(Orth)
Consultant Orthopaedic Surgeon | South West London Elective Orthopaedic Centre (SWLEOC), UK
Vipin Asopa is a consultant hip and knee arthroplasty surgeon at the South West London Elective Orthopaedic Centre (SWLEOC) and one of the United Kingdom's leading clinical voices on artificial intelligence in orthopaedics. He holds a PhD in cartilage biology and serves as Audit and Quality Improvement Lead at SWLEOC, a role that has placed him at the interface of clinical outcomes data and digital transformation.
Asopa is an NHS Topol Digital Fellow—a prestigious national programme that selects clinicians to lead AI and digital health innovation across the NHS. This background positions him not as a theorist but as an active implementer: he runs AI research, works with real patient datasets, and navigates the practical complexities of deploying machine learning tools in a busy tertiary arthroplasty unit.
His research focuses on predictive AI in arthroplasty, including radiograph-based machine learning to detect early aseptic loosening of total hip replacements—work that moves from retrospective detection towards genuine prospective risk stratification. He has co-authored widely used clinical overviews of AI in trauma and orthopaedics, organising the field into accessible domains: computer vision (imaging and fracture detection), predictive analytics (outcomes and failure prediction), and natural language processing (reports and decision support).
Professor Fares S. Haddad BSc MD(Res) MCh(Orth) FRCS(Orth) FFSEM
Professor of Orthopaedic and Sports Surgery, University College Hospital London | Editor-in-Chief, The Bone & Joint Journal
Fares Haddad is one of the most prominent figures in global orthopaedic surgery—a high-volume arthroplasty and sports surgeon at University College Hospital London and Professor of Orthopaedic and Sports Surgery at University College London. He is internationally recognised for his academic leadership, surgical innovation, and extensive contributions to the peer-reviewed literature.
His unique relevance to this meeting stems from his role as Editor-in-Chief of The Bone & Joint Journal, the official journal of the New Zealand Orthopaedic Association and one of the most widely read publications in the specialty worldwide. In this capacity, Haddad is one of a small group of global gatekeepers of orthopaedic knowledge—responsible for what gets published, trusted, and ultimately shapes clinical practice.
Haddad has led the orthopaedic editorial community's response to the challenge of artificial intelligence. He co-authored a landmark multi-journal editorial on AI and orthopaedic publishing alongside editors of Clinical Orthopaedics and Related Research, the Journal of Orthopaedic Research, and JBJS—representing a rare unified statement from the global editorial leadership of the specialty. His concerns are grounded and immediate: AI can now generate manuscripts, abstracts, and letters that are extremely difficult to distinguish from genuine scholarship; hallucinated references enter the literature; authorship frameworks designed for human researchers are inadequate.
Haddad speaks with exceptional authority on the integrity of the scientific literature, the accountability gaps AI creates, the asymmetry between AI-assisted manuscript production and overburdened peer review, and the challenge of distinguishing valid AI-augmented research from synthetic noise. He also engages with the tension between traditional RCT-based evidence hierarchies and the personalised prediction AI promises. His perspective is that of a guardian of evidence—not asking how to build AI models, but whether the evidence those models produce can be trusted.
Simon Longstaff AO PhD
Executive Director, The Ethics Centre, Australia
Dr Simon Longstaff has been Executive Director of The Ethics Centre since 1991, working across business, government and society. He has a PhD in philosophy from Cambridge University, is a Fellow of CPA Australia and of the Royal Society of NSW, and an Adjunct Professor of the AGSM at UNSW. Simon was made an Officer of the Order of Australia (AO) in 2013.
Longstaff's framework for AI ethics centres on what he calls 'ethical infrastructure'—the idea that technical capability, however impressive, must be matched by governance, trust, transparency, and accountability, or it will ultimately fail and cause harm. A central theme of his work is that technical mastery divorced from ethical restraint is at the root of institutional failure. Applied to AI in surgery, this is a provocation worth hearing.
His thinking maps directly onto the known risks of AI in orthopaedics: bias in datasets that produces inequitable clinical outcomes; black-box decision tools that undermine meaningful informed consent; commercial data use that raises privacy concerns; and unclear liability chains when AI-assisted decisions cause harm. He is particularly strong on the idea that patients must remain moral subjects—people with rights, preferences, and dignity—rather than data objects whose outcomes are optimised by an algorithm.
Marcin Czyż MD PhD
Consultant Spine Surgeon
Marcin T. Czyż is a spine surgeon with a PhD-level background in biomechanical modelling, including finite element analysis of cervical spine injury and quantitative analysis of surgical constructs. This engineering-informed clinical profile gives him a distinctive perspective on AI: he understands modelling as a discipline, appreciates the gap between computational prediction and biological reality, and is well placed to interrogate the assumptions that underpin AI tools in surgical practice.
His value in the context of AI is not as an implementation champion but as a sophisticated critical appraiser. From his biomechanics background, he understands that models are approximations of reality, that performance in controlled conditions does not guarantee performance in real patients, and that the assumption of generalisability requires rigorous external validation. These are exactly the limitations that plague current orthopaedic and spinal AI research, where many tools are trained on single-centre datasets, perform impressively within their training environment, and fail to replicate results elsewhere.
Charles M. Lawrie MD
Fellowship-Trained Hip & Knee Arthroplasty Surgeon, Baptist Health Orthopedic Care, USA | President, Anterior Hip Foundation
Charles Lawrie is a fellowship-trained hip and knee arthroplasty surgeon at Baptist Health Orthopedic Care in the United States, with a strong reputation as a technology-forward, research-active clinician operating at the intersection of surgical practice, digital health, and implant innovation. He is President of the Anterior Hip Foundation and a member of the Digital Health Committee of the American Association of Hip and Knee Surgeons—roles that reflect his standing as someone who helps shape how new technology is taught, disseminated, and adopted across the specialty.
Lawrie's practice is built around robotic-assisted and minimally invasive joint replacement, routine use of imaging and planning software, and active involvement in implant and surgical technology development. This combination—clinical volume, digital workflow adoption, tech development, and digital health leadership—places him in the cohort currently driving AI adoption in arthroplasty, and gives him credibility on both the clinical and systems sides of the conversation.
His perspective on AI is framed through a continuum: from mechanical precision (computer-assisted surgery) to algorithmic planning (robotics) to predictive intelligence (AI). He is particularly strong on personalised surgery—patient-specific implant selection, alignment strategy, complication risk prediction, and tailored recovery protocols—and translates these concepts into concrete, outcomes-focused language that resonates with practising surgeons.
At the service and systems level, Lawrie brings a blueprint mentality: how do you design an AI-ready orthopaedic department, integrate data and imaging pipelines with decision support, and scale beyond pilots? He has been involved in developing the FIOS Chat Bot as an example of translating AI into meaningful clinical output, and is comfortable discussing why most AI projects fail to scale—moving from analysis to actionable insight requires not just good algorithms but good data infrastructure and clinical workflow integration.
Stefan Kreuzer MD
Orthopaedic Surgeon, Founder INOV8 Orthopedics, Houston, Texas, USA
Stefan Kreuzer is a high-volume hip and knee arthroplasty surgeon based in Houston, Texas, and the founder of INOV8 Orthopedics—a surgical technology and innovation company. He occupies a distinctive position in the AI conversation as a high-volume, technology-forward private practice surgeon who evaluates every new technology through a single lens: does it actually work in my operating theatre tomorrow?
Kreuzer was an early adopter of computer-assisted surgery and robotic joint replacement, performing significant volumes with active robotic systems including the TSolution One. This is important context: he has already spent years working in an algorithm-augmented surgical environment, navigating the integration of preoperative planning software, intraoperative guidance, and execution algorithms into real clinical workflows. He is not speculating about technology—he has lived through its adoption curve.
His practice design around ambulatory surgery centres, efficiency optimisation, and workflow development gives him a sharply practical perspective on the economics of surgical innovation. He understands throughput, theatre time, capital cost, team training, and the learning curves that new technology demands. He has also developed positioning systems and workflow tools, giving him insight into how devices interact with clinical infrastructure.
Kreuzer is pro-innovation but not naïvely so. He is consistent in acknowledging that no technology is perfect, and his strongest contribution to an AI programme is as a reality check: articulating what actually improves outcomes, what creates workflow friction, what costs are justified by measurable benefit, and where the promise of AI has not yet matched the reality.
Peter Harris
Nick Petrie is an applied field researcher studying how professionals sustain performance as AI reshapes complex fields like medicine. He works with both the organizations developing AI technologies and the professionals whose work they are transforming. Nick holds a Master’s degree from Harvard University and is the author of Burn Bright.