Screening Support, Not Diagnosis
Human experts remain in control. ASDFACE provides structured input for better-informed next steps.
AI STARTUP FOR EARLY SCREENING IMPACT
In Australia, autism can be diagnosed from around 18 months, yet the average diagnosis age is around 8 years. ASDFACE bridges this gap with an explainable computer-vision platform designed for clinicians, families, and social care systems.
SUMMARY
ASDFACE is an AI computer-vision platform and app that uses facial images to support autism screening. It is designed to streamline triage and referral, not replace clinicians or formal diagnosis.
By accelerating early risk identification, we aim to reduce pressure on long specialist waitlists and on disability support pathways, including families seeking NDIS-relevant services.
Human experts remain in control. ASDFACE provides structured input for better-informed next steps.
Workflow supports clinicians, educators, support workers, and parents across real-world service pathways.
Built in Australia with architecture that can adapt across policy, language, and healthcare settings.
PLATFORM WORKFLOW
Guided intake supports quality facial-image data capture through a simple app experience.
AI-enhanced facial biometrics analyze subtle cues while adapting across cameras and environments.
Screening outputs are presented with interpretable confidence to support professional judgement.
Structured reports help teams move families toward timely formal assessment and intervention planning.
COLLABORATION & PARTNERSHIPS
ASDFACE is designed to support faster referral pathways and reduce pressure on long disability and specialist support queues.
Visit NDIS →We acknowledge support from La Trobe University's Olga Tennison Autism Research Centre (OTARC) for translational autism research.
Visit OTARC →We acknowledge support from La Trobe University's Australian Centre for Artificial Intelligence in Medical Innovation (ACAMI).
Visit ACAMI →Collaboration has included La Trobe University, Harvard Medical School, and IBM, connecting research excellence with commercialization pathways.
Read IBM Case Study →Our collaboration with Little Supermen helps extend ASDFACE from screening into family-facing engagement, strengthening the bridge between early risk indication and practical follow-up support.
Visit Little Supermen →Our engagement with CSIRO strengthens ASDFACE's translation pathway from research into national-scale innovation, industry connectivity, and commercialization readiness.
Visit CSIRO →LEADERSHIP TEAM
ASDFACE combines research leadership, enterprise AI experience, product strategy, and commercial operations to move from laboratory breakthroughs to real-world, explainable autism screening.
CEO & Founder
Vision & Strategy
Former Research Scientist at IBM Research and Visiting Scholar at Harvard Medical School, with dual PhDs in Computer Science and international recognition as a G20 Young Global Changer.
Lina leads the corporate overall vision, strategy, executive leadership, and aligns technology, product, commercialisation, and operations around the company's strategic priorities to drive long-term growth and enterprise value.
CTO & Co-Founder
Technology
Distinguished Professor, Winner of the 2026 Financial Review AI Award in Sustainability, founder of two major AI research centres, and a Stanford World's Top 2% Scientist (2020-2025).
Wei leads technology strategy, AI architecture and platform development, bringing world-class expertise in AI, machine learning, computer vision and scalable intelligent systems to advance explainable, reliable and accessible AI-powered autism screening solutions.
CBO & Co-Founder
Business & Commercialisation
Senior international business and strategy expert with extensive experience across government, multinational corporations and major industry sectors, including nearly 25 years with the Australian Trade and Investment Commission (Austrade).
Green leads commercialisation strategy, strategic partnerships, global expansion, and investment engagement, transforming AI innovation into scalable business opportunities, strategic market access, and high-value international partnerships.
CPO
Product
Former AI Lead at IBM, with over a decade of experience translating advanced Data & AI technologies into pioneering, commercially viable enterprise solutions.
At ASDFace, Alessio leads product strategy, AI innovation, and product development, combining deep technical expertise with customer-facing industry experience to transform cutting-edge AI into accessible, user-centred, and scalable autism screening solutions with real-world impact.
COO
Operations & Execution
Commerce Achievement Scholar at the University of Melbourne, with leadership experience at the Social Impact Investment Fund and industry experience through New Aim and Jane Street's WiSE Program.
Yiluo leads business operations and execution, overseeing cross-functional delivery, partner implementation, stakeholder management, and organisational processes to ensure strategic and commercial initiatives translate into measurable outcomes and sustainable growth.
CTA
AI & Technical Advisory
Former faculty member at Harvard Medical School and Purdue University Northwest, with 100+ publications in medical AI, biomedical informatics, multimodal learning, and large AI models. His research bridges advanced AI methodologies with real-world biomedical and healthcare applications.
Haishuai provides strategic technical advice on AI, multimodal learning, medical AI, and advanced model development, supporting ASDFace in building robust, explainable, clinically relevant, and scalable AI-powered autism screening solutions.
PARTNERSHIP ENQUIRIES
We welcome collaboration with hospitals, disability organizations, universities, and policy-aligned technology partners.
SOCIAL BENEFIT FOCUS
Technology outcomes measured by real family and system impact.
Families
Faster screening signals can reduce uncertainty and help families access evidence-based support pathways earlier.
Clinicians and Educators
Structured, explainable outputs strengthen triage decisions and improve coordination across multidisciplinary teams.
Public Systems
Earlier identification supports fairer resource allocation and can reduce pressure on delayed specialist and disability pathways.