Ran Chen
Ran Chen is a machine learning leader with over a decade of experience driving AI innovation across media, real estate, and legal tech.
About Ran Chen
With deep technical expertise in personalization, computer vision, and natural language processing, Chen has built and scaled end-to-end machine learning systems that power user experiences, optimize engagement, and accelerate business growth. Chen has a proven track record of managing distributed teams, fostering a culture of experimentation, and delivering scalable, data-driven solutions from scratch.
Prior to joining Pure Global, he served as the founding machine learning engineer and later Director of Engineering at Tubi TV, where he led the development of core recommendation engines, experimentation platforms, and international personalization strategies for a platform serving over 100 million users. He holds a Master of Computational Data Science from Carnegie Mellon University and a Bachelor of Software Engineering from Tsinghua University in Beijing.
Latest Articles
Surgical robots do not follow one regulatory class or one reusable filing. This research report maps the public records across eight markets, showing how architecture drives FDA classification, why one platform becomes dozens of registration objects, where clinical evidence controls the schedule, and what government and in-country representation fees actually cost.
ISO 10993-1 changed in 2025, but regulators did not change together. This practical guide maps seven regulatory systems and shows how to build one controlled biological-evaluation core with market-specific overlays.
The EU inverted its IVD regime and the US reverted its own. This report rebuilds what that means for classification, timelines and cost from the registers themselves — including 238 IVDR certificates against 3,343 for devices, and the risk-class split across nine national registers.
The same orthopedic implant can be Class II in the United States and Class III across the European Union, China, Japan and Australia. This report compares pathways, realistic timelines, government fees, reliance limits and mandatory in-country-representative costs across seven major markets.
The same aesthetic device can face a different risk class, evidence burden and registration route in every major market. This research report compares fillers and energy-based platforms across the United States, European Union, China, Korea, Brazil and Japan — including realistic timelines, regulator fees, reliance routes and mandatory in-country-representative costs.
The continuous glucose monitor is the fastest-scaling category in diabetes technology, and in 2024 it broke out of diabetes entirely — onto pharmacy shelves as an over-the-counter wellness product. Yet the same sensor is Class II in the U.S. (now sold OTC), Class IIb in the EU, and Class III in China. This report maps how every major regulator classifies, approves, and reimburses CGM — and why a single FDA clearance or CE mark clears none of the three gates (approval, reimbursement, intellectual property) by itself — with registration costs, timelines, and reliance routes across 30+ markets.
Artificial intelligence is the fastest-growing class of medical device in history — and the most regulation-divergent. The U.S. FDA now lists 1,524 AI-enabled devices; South Korea authorized 153 in a single year. Yet the same software is Class II in the U.S., Class IIa+ and 'high-risk' in the EU, and Class III in China — each with its own evidence, local-holder, and change-control rules. This report maps how every major regulator classifies, approves, and polices AI as a medical device, with registration costs, timelines, and reliance routes across 30+ markets, and the playbook for reaching them without rebuilding the dossier each time.