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Daniel Cao is listed as AI Solution Engineer APAC at Hewlett Packard Enterprise, a company with 208808 employees, based in Melbourne, Victoria, Australia. AeroLeads shows a matched LinkedIn profile for Daniel Cao.
Daniel Cao previously worked as Project Manager at Wood and Data Scientist / Consultant at Wood. Daniel Cao holds Doctor Of Philosophy (Ph.D.), Civil Engineering from Tokyo Institute Of Technology.
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At Hewlett Packard Enterprise (HPE), Daniel is helping customers in APAC, Japan, and India, some of whom are among Top 500 supercomputing powerhouses, drive AI-powered innovations with HPE's AI-at-scale solutions.Previously he worked as a data scientist/solution architect at Wood, a global energy and built environment company, pushing AI-enabled automation for computer vision-based subsea inspection, inventory optimization, and maintenance management using large language models.He was a Manager & Senior AI Engineer working on AI-enabled automation business projects towards smart factory at Skydisc Inc., Tokyo, Japan. At Skydisc, he was the principal AI engineer/AI tech lead/support of various computer vision-based projects for real-time/offline anomaly detection and automated measurement system for commercial product inspection; and time-series data projects such as machine/engine fault diagnosis using vibration or sound. At his position, he also experienced with defining AI technical requirements, planning and delegating engineer resources, facing clients together with the sales team, and collaborating with system/DevOps engineers on AI system integration.Before joining Skydisc, Daniel worked at the Advanced Research Laboratories at Tokyo City University as a research scientist who pioneers smart infrastructure monitoring and inspection using deep learning-based methods. His research focuses on developing autonomous vision-based methods for crack/damage detection and vehicle recognition using deep convolutional neural networks.He received his Ph.D. in 2017 from the Tokyo Institute of Technology. His Ph.D. research contributes to improving the current standard practice of smart vehicular load sensing in steel bridges via the novel application of self-powered piezoelectric sensors and an AI system for automated vehicle weight identification.Besides academic and industry contributions, he is also a co-founder & advisor of the Vietnam Japan AI Community (VJAI) based in Tokyo, Japan, aiming to create a connected community of Vietnamese AI researchers and engineers currently working/studying in Japan.
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Melbourne, Victoria, Australia
HPE World Wide AI Ambassador.Lead AI Solution Engineering activities across APAC, India, and Japan, helping customers to accelerate large-scale DL, LLMs and generative AI development using the HPE AI at scale portfolio, including HPE Machine Learning Development Environment, HPE Machine Learning Data Management, GenAI Studio, HPE Machine Learning Inference.
Highlights:- Invented, managed and delivered the Proof of Concept (PoC) of S.ai, the innovative NLP/deep learning-powered autonomous solution that aims to transform maintenance management on large text-savvy management datasets- Managed and delivered the PoC for a client project that aims to automate trash analytics using computer vision/deep learning and.
Melbourne, Victoria, Australia
Highlights:- Finalists for Wood Inspire Impactful Innovation Award 2021 (teamwork)- Finalists for Wood Inspire Impactful Innovation Award 2020 (teamwork)- Award-winning AI (Machine Vision) Solution at the Australian Subsea Business Awards 2020 presented by Subsea Energy Australia (teamwork)- Product owner/manager of an AI-assisted maintenance management.
Melbourne, Victoria, Australia
Highlights:- Built & developed the augmentation pipeline for images for the Augmented Machine Vision (AMV) solution - Built, trained, and deployed the core deep learning/computer vision model of the AMV solution to Azure Cloud endpoints
Tokyo, Japan
Highlights:- Skydisc's 2019 Most Valuable Person (MVP) for Advanced Technology Solution that significantly improves businesses in 2019Manage a direct-reporting team of 10 international data scientists while being a Tech Lead/Principal Engineer/Tech Advisor of machine vision and signal processing projects
Tokyo, Japan
AI-enabled Automation for Smart FactorySkydisc provides consulting services to clients in the manufacturing industry and develops various AI technologies that are integrated into systems at client factories and manufacturing processes.
Tokyo, Japan
Highlights:- 02 published journal papers on applied computer vision/deep learning for crack/damage detection in civil structuresDeep Learning for Smart Infrastructure Maintenance- Invented and prototyped autonomous vision-based systems using deep learning for crack detection during a bridge inspection (leading to 02 publications)- Invented and prototyped a.
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Umashekar Gn
Colleague at Hewlett Packard EnterpriseBengaluru, Karnataka, India, India
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Manishi Singhai
Colleague at Hewlett Packard EnterpriseIndia, India
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Sudip Sarkar
Colleague at Hewlett Packard EnterpriseBirbhum, West Bengal, India, India
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Sandra Cardona
Colleague at Hewlett Packard EnterpriseUnited States, United States
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Ian Whitehouse
Colleague at Hewlett Packard EnterpriseMilton Keynes, England, United Kingdom, United Kingdom
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Howard Friedman
Colleague at Hewlett Packard EnterprisePhilomath, Oregon, United States, United States
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●๋•Kíńg Őf Dểvíl ●ツ
Colleague at Hewlett Packard EnterpriseUttar Pradesh, India, India
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Januwin Pj
Colleague at Hewlett Packard EnterpriseBengaluru, Karnataka, India, India
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José Mª Pavón
Colleague at Hewlett Packard EnterpriseGreater Marbella Metropolitan Area, Spain
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Lisa Svensson
Colleague at Hewlett Packard EnterpriseStockholm, Stockholm County, Sweden, Sweden
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Quick answers generated from the profile data available on this page.
Daniel Cao works for Hewlett Packard Enterprise.
Daniel Cao is listed as AI Solution Engineer APAC at Hewlett Packard Enterprise.
Daniel Cao is based in Melbourne, Victoria, Australia while working with Hewlett Packard Enterprise.
Daniel Cao has worked for Hewlett Packard Enterprise, Wood, Skydisc, and Tokyo City University.
Daniel Cao's colleagues at Hewlett Packard Enterprise include Umashekar Gn, Manishi Singhai, Sudip Sarkar, Sandra Cardona, and Ian Whitehouse.
You can use AeroLeads to view verified contact signals for Daniel Cao at Hewlett Packard Enterprise, including work email, phone, and LinkedIn data when available.
Daniel Cao holds Doctor Of Philosophy (Ph.D.), Civil Engineering from Tokyo Institute Of Technology.
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