--- title: "Tianjin's Xu Minpeng Builds a Brain–Computer Link That Learns Back" date: 2026-10-29 category: Builders site: NeuroAI canonical: https://neuroai.site/a/na-people-xu-minpeng-tianjin-bci language: en --- # Tianjin's Xu Minpeng Builds a Brain–Computer Link That Learns Back > Tianjin University researcher Xu Minpeng co-led a non-invasive, two-way adaptive BCI published in Nature Electronics that lets a user steer a drone in four directions with thought alone. A student puts on a soft EEG headband, thinks about moving a drone forward, and the rotorcraft eases ahead — then turns, climbs and rotates, all from continuous intention rather than a single click. No surgery, no implant, just a signal most labs once considered too faint to use. That is the kind of interface Xu Minpeng (许敏鹏) has spent his career making work. ## Key takeaways - Xu Minpeng is a brain–computer interface researcher at Tianjin University and a member of the university's Brain–Computer Interface Haihe Laboratory (脑机海河实验室). - As a PhD student he was first author of an IEEE TBME cover article on a brain speller that decodes EEG signals as weak as about 0.5 microvolts, under corresponding author Ming Dong (明东). - He co-led a "dual-loop" (双环路) memristor-based, two-way adaptive BCI with Ming Dong and Tsinghua University, published in Nature Electronics. - The system gives a user four degrees of freedom of continuous drone control and, over six-hour sessions, improved accuracy by roughly 20% instead of decaying. - The lab frames the work as the world's first non-invasive adaptive BCI of its kind, aimed at wearables, rehab and hands-free control. ## A researcher who stayed with the weak signal Xu earned his PhD in biomedical engineering at Tianjin University in 2015 after a visiting stint in computational neuroscience at the University of California, San Diego. His early signature result was unglamorous: finding order in noise. In an IEEE Transactions on Biomedical Engineering cover article, his team showed a speller that could read the smallest visual-evoked potentials — brain signals around 0.5 microvolts, far below the 2-microvolt floor most systems needed. The point was not a party trick but a principle: non-invasive BCI's limit is signal quality, and signal quality is an engineering problem. That principle now anchors a larger programme at the BCI Haihe Laboratory, where Xu works alongside Ming Dong on interfaces that do not require opening the skull. ## The link that learns back Traditional BCIs are one-way: the brain speaks, the machine decodes, performance drifts as the user tires. Xu's group attacked the drift with a "dual-loop" design built on a memristor neuromorphic chip. One loop updates the decoder as the brain signal shifts; the other sends feedback so the user learns to control the machine better. Over a six-hour session the two adapt together, and accuracy climbed by about 20% rather than falling — the opposite of the usual fatigue curve. The work, done with Tsinghua's integrated-circuit team (Wu Huaqiang and Tang Jianshi), was published in Nature Electronics and demonstrated as four-degree-of-freedom control of a drone: forward–back, left–right, up–down and rotation, all from continuous thought. The lab describes it as the first non-invasive adaptive system of its kind. The promise is practical — firefighters or inspectors with both hands busy, or patients steering assistive devices — because it needs no surgery and can in principle shrink to a wearable. The lab is explicit that the target is not a one-off demo but a category: surgery-free control for rehabilitation, assistive robotics and industrial inspection, where implant risk has kept BCIs off the shop floor. ## Why non-invasive is the Chinese front China's BCI policy explicitly favours non-invasive scale: Ming Dong, Xu's senior colleague, has argued that high-performance non-invasive interfaces reaching ordinary users — not everyone receiving an implant — are what will build the industry. Xu's co-adaptive approach is a direct answer to the field's hardest objection: that scalp signals are too noisy and too unstable for real use. His group's answer is that noise is trainable. For China, where the 15th Five-Year Plan names brain–computer interface (脑机接口) a future industry, non-invasive scale is also a policy preference, not just an engineering one. According to Li An, chief scientist at BrainNet (脑机网), non-invasive co-adaptive interfaces are where Chinese teams are currently most competitive, because the bottleneck is engineering and data density rather than surgical risk or implant durability. ## Honest limitations The performance gains are reported by the research team and a handful of outlets covering the Nature Electronics paper; the ~20% six-hour improvement is the team's measured result, not yet an independently reproduced benchmark across labs. Non-invasive BCI still trails invasive recording on signal richness, and long-term durability, daily-use reliability and clinical rehab efficacy at scale remain unproven. The "world's first" claim is the laboratory's own framing. The work is a research demonstration, not a shipped product, so timelines to any wearable or medical use are uncertain. ## What readers can do now - Clinicians and researchers: read the Nature Electronics paper and the earlier IEEE TBME speller work as the two anchors of Tianjin's non-invasive programme. - Patients and families: track non-invasive rehab and assistive trials from the BCI Haihe Laboratory rather than assuming implants are the only path. - Investors: watch the lab's commercialization partners for wearables and hands-free control, where surgery-free BCI has the widest addressable market. --- Published by NeuroAI (https://neuroai.site/) — https://neuroai.site/a/na-people-xu-minpeng-tianjin-bci Free to quote with attribution and a link to the original.