Technology Advantages

Techcul is internationally recognized for its ground break- ing contributions in artificial intelligence, machine learning, data mining, computer vision, natural language processing, personalization, recommender systems and health informatics.

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Machine Learning
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Computer Vision
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Data Mining

Completed Projects

With a team of computer scientists, artificial intelligence experts, data scientists, software engineers and profes- sional experts with extensive national and international experience, the team has a strong track record of artificial intelligence research and its translation into real world applications.

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Intelligent Medical Decision Support System

Techcul creates intelligent medical decision support systems by using artificial intelligence technologies including machine learning, computer vision, image processing and data mining. Such systems integrate medical experts’ experience and knowledge embedded in electronic health records including medical images as well as scientific publications, research results and traditional diagnostic guidelines, which provide effective and efficient decision support to medical diagnoses in order to improve diagnostic performance.

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Medical Dynamic Modelling and Outcome Prediction

As a researcher at Australian Institute of Health Innovation, Dr. Xiongcai Cai,Techcul team member, led the research on medical dynamic modelling and outcome prediction. He with the team successfully created the world‘s first simultaneous predictive model for mortality, readmission, and length of stay for non-specific diseases, which achieves the highest prediction accuracy in the world. The research results were published in the top 1 health informatics journal.

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Moving Object Detection, Tracking and Prediction

Techcul team members Dr. Jun Yang and Dr. Xiongcai Cai used to work in both the computer vision and machine learning group at National ICT Australia. As key investigators of a number of intelligent system projects, they designed and developed novel object detection and tracking algorithms, and traffic parameter prediction models, which have been successfully deployed in the systems of the Roads and Traffic Authority of NSW(New South Wales). Some of the algorithms by Dr. Yang have been granted US patents successfully.

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People to People Recommender Systems

From 2008 to 2013, as a senior researcher at Australian Smart Collaborative Research Centre, Techcul team member Dr. Xiongcai Cai, worked with Professor Paul Compton, Dr. Yang Sok Kim and other team members to successfully develop the world's first commercial People to People Recommender System. The research outcomes were published in world's leading scientific conferences including AAAI and ICDM, and reputed journals including AI Magazine. The developed system has been deployed on the Australia's largest dating site, namely RSVP, which effectively improves the success rate of matching and revenue. One of the most well-known Chinese dating site also obtained helpful advices and guidelines from Dr. Cai, which is believed to improve the performance of their recommendation systems.

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Decision Support Tools for Motor Neurone Disease

Dr. Xiongcai Cai, Techcul team member, and his research team developed decision support tools for motor neurone disease (MND) multidisciplinary care after successfully being awarded the MND research grant. This research fills the gaps in decision making of motor neurone disease, whose outcomes were published in high quality journal and conferences.

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Medical Image Segmentation

Techcul team member Dr. Xiongcai Cai and Professor Arcot Sowmya created a novel image segmentation method based on artificial neural networks and active contours, which has been applied on segmentation of lung tumour images with significant improved results. The research results were presented and published at the 2006 International Conference on Neural Information Processing.

Core Team

Our award-winning team is multi-disci- plinary and multi-national with backgrounds in artificial intelligence, machine learning, data mining, knowledge acquisitions, computer vision, personalization, recom- mender systems and health informatics supported by dedicated professional staff.

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Dr. Xiongcai Cai

Founder|CEO|CSO

Dr. Xiongcai Cai is a senior computer scientist, AI expert and doctoral supervisor of the School of Computer Science and Engineering, UNSW Sydney, Australia. Dr. Cai served as a senior researcher in a number of Australian research centres, including Australian Institute of Health Innovations, Smart Service CRC and Australia‘s Information and Communications Technology (ICT) Research Centre of Excellence. He has successfully led teams to develop the world’s first people to people recommender system that has been deployed in RSVP, and a medical outcome prediction system collaborated with St. Vincent Hospital.

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Professor Arcot Somwya

Chief Scientist

Professor Arcot Somwya is a senior computer scientist, AI expert,professor and doctoral supervisor of the School of Computer Science and Engineering, UNSW Sydney, Australia. She teaches and conducts research in learning in vision with applications in medical imaging and remote sensing, heads a team of 10 researchers, and as partner in research networks and centres. During 2006-2007, she was Head of Engineering, Science and Technology Division, UNSW Asia, Singapore, where she headed 30 staff on an annual budget of SGD 6 million. Professor Somwya has published more than 250 articles in journals and conferences.

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Dr. Yang Sok Kim

Scientist

Dr. Yang Sok Kim has overall 15 years research and development experience in machine learning & data mining, knowledge based system and knowledge acquisition, and web/text mining techniques,has 62 published papers and 460 Google Scholar citations. His postdoctoral research at UNSW focused on social recommender (CRC Smart Services Project) and knowledge based systems (ARC Discovery Project), Dr. Yang Sok Kim is currently an assistant professor and supervisor of Ph.D.s and masters at the School of Management Information Systems at Keimyung University, Korea. Dr. Kim has also made significant achievements in commercial research, such as web monitoring and document classification systems.

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Dr. Jun Yang

R&D Lead | Scientist

In the past decade, Dr. Jun Yang has been working in computer vision, machine learning and data mining. Along with rich academic and industrial experience, he has built up a deep understanding of both the fundamental theory and frontier technologies of AI. Dr. Yang used to work in both the computer vision and machine learning group at National ICT Australia. As a key investigator of a number of intelligent system projects, he designed and developed novel object detection and tracking algorithms, and traffic parameter prediction models, which have been successfully deployed in the systems of the Roads and Traffic Authority of NSW. Some of the algorithms have been granted US patents.

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Dr. Weihong Wang

Scientist

Weihong Wang received Ph.D. degree in the area of machine learning at the University of New South Wales, Sydney, Australia. He received M.E. degree in computer science from the University of New South Wales in 2006, and B.S. degree in computer science from the University of Sun Yat-Sen in 2003. His research interests include image processing, pattern recognition, machine learning and deep learning. The projects he took part in include Sydney CBD Mobility Modelling project, PWC cash flow forecasting and gas pipe failure prediction.

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Yanjun Shi

COO

Yanjun Shi, Chief Financial & Marketing Officer, responsible for financial planning and marketing strategy. Shi Yanjun holds a master's degree in business administration (MBA) from University Of Paris-I and is very experienced in business management and mobile internet market development. He was the former mobile business director of LETV Group, and has served in marketing department in several well-known Internet companies such as Orca Digital Music and iqiyi.com.

Advisors

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Professor Zhong Ming

Distinguished Advisor

Professor Zhong Ming is the Discipline Leader of Computer Software and Theory, Pengcheng Scholar Distinguished Professor, Chairman of Shenzhen Computer Society, Director of China Computer Federation, Deputy Director of the Internet of Things Industry-University-Research Institute Alliance. He continues to contribute in research on middleware technology,the Internet of things and cloud computing and has published more than 100 high quality papers in leading conferences and journals.

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E/Professor Paul Compton

Chief Scientific Advisor

Professor Paul Compton is a world‘s top artificial intelligence expert and the inventor of Ripple-down Rules, a famous knowledge acquisition algorithm. The Ripple-down Rules are widely used in healthcare systems world wide. Professor Compton is also invited to serve as board member for a number of high tech companies for his professional contributions in the areas.

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Professor Maurice Pagnucco

Distinguished Advisor

Professor Maurice Pagnucco is a world’s top artificial intelligence and robotic expert. He supervised a robotic team to receive top awards in a series of robotic world cup competitions. Professor Pagnucco is also the president of Australian Council of Deans of ICT.

About Techcul

Founded in 2017,Shenzhen Techcul Co., Ltd. is committed to the research, development and deployment of artificial intelligent (AI) technologies, to help and support businesses and manufactures in industry. Techcul will continue to innovate, meet challenges and contribute to the intelligent industry in China and the world.

OUR TECHNICAL ADVANTAGES

Techcul is internationally recognized for its ground breaking contributions in artificial intelligence, machine learning, data mining, computer vision, natural language processing, personalization, recommender systems and health informatics.

OUR EXPERIENCE

With a team of computer scientists, artificial intelligence experts, data scientists, software engineers and professional experts with extensive national and international experience, the team has a strong track record of artificial intelligence research and its translation into real world applications. Our award-winning team is multi-disciplinary and multi-national with backgrounds in artificial intelligence, machine learning, data mining, knowledge acquisitions, computer vision, personalization, recommender systems and health informatics supported by dedicated professional staff.

JOIN OUR TEAM OR PARNER WITH US

We welcome research scientists with a background as computer scientists, software engineers and students to join our team. We invite industry, universities and research organisations to partner with us to create business opportunities through research and innovation.

Collaborators

Techcul is linked with most major national and international organisations and groups in research and development via project collaborations, shared grants and publications.

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