The Chen IPL & eWEAR-X Symposium

Bao is K.K. Lee Professor of Chemical Engineering, and by courtesy, a Professor of Chemistry and a Professor of Material Science and Engineering at Stanford University. Bao directs the Stanford Wearable Electronics Initiate (eWEAR) and the Taiwan Science and Technology Hub @ Stanford. She is a CZ Biohub investigator since 2022 and an Arc Institute Innovation Investigator since 2023.

Prior to joining Stanford in 2004, she was a Distinguished Member of Technical Staff in Bell Labs, Lucent Technologies from 1995-2004. She received her Ph.D in Chemistry from the University of Chicago in 1995.  She has more than 700 refereed publications and over 80 US patents with a Google Scholar H-Index 206 and is one of the world’s most highly cited scholars in the fields of chemistry and material science. She is one of the Clarivate Citation Laureates in Chemistry for her pioneering work on skin-inspired electronics.

Bao is a member of the National Academy of Engineering, the American Academy of Arts and Sciences and the National Academy of Inventors. She a foreign member of the Chinese Academy of Science. She has been serving on the Board of Directors of the Camille and Henry Dreyfus Foundation and scientific affair committee from 2022. She is an advisor for the Science for America, a solutions incubator to address urgent challenges, driven by an unprecedented alliance of leading philanthropic organizations.

Bao is a recipient of the VinFuture Prize Female Innovator 2022, the ACS Chemistry of Materials Award 2022, MRS Mid-Career Award in 2021, AICHE Alpha Chi Sigma Award 2021, ACS Central Science Disruptor and Innovator Prize in 2020, Gibbs Medal 2020, Wilhelm Exner Medal2018, ACS Award on Applied Polymer Science 2017, L’Oréal-UNESCO For Women in Science Award 2017.

Bao is a co-founder and on the Board of Directors for C3 Nano and PyrAmes, both are silicon-valley venture funded start-ups. Research inventions from her group have been licensed and are foundational technologies of multiple start-ups founded by her students. Bao serves as an advisor for Fusion Venture and Boutique Venture.

Xiang Qian, MD, PhD, is a Pain Management Physician and Clinical Professor of Anesthesiology, Perioperative and Pain Medicine at Stanford University. He is also the inaugural Stanford Medicine Endowed Director.

Dr. Qian is highly respected for his work on developing novel therapies for various chronic pain conditions, and he lectures internationally for those work and topics. Dr. Qian’s clinical interests include the treatment of acute and chronic pain, with special interest in migraine, headache, trigeminal neuralgia, glossopharyngeal neuralgia, hemifacial spasm, atypical facial pain, cancer pain, back pain, joint pain, nerve pain, and others. At Stanford, Dr. Qian developed many advanced surgical and interventional technologies for his patients, and he currently leads the CT-guided interventional pain program and is the recipient of Translational and Clinical Innovation Award at Stanford.

With his deep interest in clinical innovation and translational medicine, Dr. Qian is the faculty professor of Stanford Wearable Electronics Initiative (eWEAR) and has been working with colleagues from engineering school to develop mini implantable nerve stimulator, powered by wireless energy. Similar to a pacemaker for the heart, nerve stimulators are modulators for the nerves.

Due to his passion for global health and leadership experience, Dr. Qian was appointed as the Medical Director of Stanford International Medical Services (IMS) since 2016, where he has been working in collaboration with faculty members from all subspecialties and hospital administrations to help deliver care for international patients and promote international collaborations. His vision is to help Stanford become the leader in international medicine by providing its physicians and faculty the opportunities to expand their practice internationally and spread knowledge globally.

Dr. Qian completed his residency and fellowship training at Stanford. Prior to that, he received his PhD degree in Physiology and Biophysics from University of Miami Miller School of Medicine, and went through Postdoc fellowship training in Neuroscience at UCSF. Outside of the work he does at Stanford, Dr. Qian founded the Chinese American Physicians’ Society to foster his efforts in bringing medical knowledge internationally. Today, the society has more than 600 physician members from 50 states of the US, across over 38 different subspecialties.

In his free time, Dr. Qian enjoys reading, running, hiking and exploring the mountains and beaches of Northern California.

Sleep is an opportunity for data scientists and physiological monitoring.  During sleep, we go through a pre-programed 90 min cycle that is uncontaminated by the activities of the day.   As such, it is an ideal moment for monitoring physiology and looking at the interaction of organ health with each other and with sleep, not to mention evaluate for the presence of sleep disorders.   Sleep is also data rich.   Every night, millions of individuals are recorded either using sophisticated full blown nocturnal Polysomnography (PSG: EEGs, EOG, EMG, ECG, breathing) and hundreds of millions use simpler commercial devices measuring pulse and locomotor activity.   Our increased ability to monitor and to analyze these data also coincide with a biological revolution, notably in genetics, proteomics and metabolomics. At the biological level, sleep is regulated by an endogenous 24 biological clock and is reactive to sleep deprivation.   Whereas much is known regarding the molecular mechanisms regulating the endogenous circadian clock, almost nothing is known regarding sleep homeostasis.   One pathway of entry to these mechanisms is genetics, because it is causal; proteomics and metabolomics may provide better markers, however. We have been assembling large datasets crossing  various modalities, including 500,000 PSGs with health care information, actigraphy datasets, proteomics, and genetic typing.  An important advantage of crossing modalities is the possibility of looking at causality and a reduction of false positive, inherent to any single modality.  Although these modalities are not yet all assembled in a single model, we already created a foundation model for PSG and found that it contains information that is able, notably when using contrastive learning, to predict various health outcomes.  A foundation model for actigraphy was also created and predicts daytime behavior and sleep stages, opening the door to its use in the UK biobank to correlate objective sleep with genetic data.  

Emmanuel Mignot is the Craig Reynolds Professor of Sleep Medicine in the Department of Psychiatry and Behavioral Sciences at Stanford University and the Director of the Stanford Center for Narcolepsy. He is recognized as having discovered the cause of narcolepsy. Dr. Mignot was born In Paris, France, and he is a former student of the Ecole Normale Superieure (Ulm, Paris, France). He received his M.D. and Ph.D. (molecular pharmacology) from Paris V and VI University respectively. He practiced medicine and Psychiatry in France for several years before serving as a visiting scholar at the Stanford Sleep Disorders Clinic and Research Center. He joined as faculty and Director of the Center for Narcolepsy in 1993. He was named Professor of Psychiatry in 2001. He has received numerous awards for his work, including a 2023 Breakthrough prize in Life Sciences and is a member of both the National Academies of Sciences and Medicine.

Dr. Mignot positionally cloned a mutation in the dog causing narcolepsy (hypocretin/orexin receptor 2) and discovered that narcolepsy, affecting 1/2000 people, is caused by an immune-mediated destruction of 70,000 hypocretin/orexin neurons in the hypothalamus, also revealing hypocretins as a novel critical sleep-regulatory pathway. Most of his current research focuses on the neurobiology, genetics and immunology of narcolepsy, with indirect interest in the neuroimmunology of other brain disorders such as autoimmune encephalitis or neurological paraneoplastic syndromes.

His laboratory also uses state of the art human genetics, proteomics and immunology techniques, such as genome-wide association, exome or whole genome sequencing or large scale proteomics in the study of human sleep and sleep disorders, with parallel studies in animal models. His laboratory is lastly interested in web-based assessments of sleep disorders, and conducts deep learning-based processing of polysomnography (PSG), and outcome research.

Modern science advances fastest when thought meets action. LabOS represents the first AI co-scientist that unites computational reasoning with physical experimentation through multimodal perception, self-evolving agents, and XR-enabled human-AI collaboration. By connecting multi-model AI agents, smart glasses, and human-AI collaboration, LabOS allows AI to see what scientists see, understand experimental context, and assist in real-time execution. Across applications—from cancer immunotherapy target discovery to cell engineering— LabOS shows that AI can move beyond computational design to participation, turning the laboratory into an intelligent, collaborative environment where human and machine discovery evolve together.

Dr. Cong’s group is developing technology for large-scale genome editing and gene insertion for gene&cell therapy, integrating advance from metagenomics, computational biology, and high-throughput engineering. In parallel, the group also leverages these gene-editing tools for single-cell functional screening, to probe the molecular mechanisms of innate immunity in cancer and neuro-immune diseases. To accelerate these efforts, Dr. Cong’s team integrates AI and machine learning into genome technologies, to design and evolve gene-editing proteins and RNAs in silico, significantly enhancing the efficiency and capabilities of these therapeutic molecules.

Dr. Cong’s work has led to one of the first CRISPR/Cas9 gene-editing tools for in vivo gene therapy. More recently, his group invented tools for cleavage-free large gene insertion with novel recombination proteins (SSAP editor), and developed machine-learning optimized single-cell methods (DAISY) for studying cancer and immune diseases. Dr. Cong is a recipient of the NHGRI Genomic Innovator Award, Baxter Foundation Faculty Scholar, Genetic Engineering and Biotechnology News (GEN) Top 10 Under 40, Clinical OMICs Pioneers Under 40, and Clarivate Web of Science Highly Cited Researcher.

Achieving human-level robotic dexterity requires systems that can see, reason about, and feel the physical world. In this talk, I will present our recent advances in physically-grounded and contact-aware perception and manipulation. I first introduce a framework that integrates physics simulation with generative video models to synthesize action-conditioned dynamic 3D scenes from a single image across diverse materials. I then discuss a conformable, high-coverage electronic skin that provides the sensitive tactile feedback essential for learning contact-rich manipulation tasks. Together, these works demonstrate how combining physics-based priors with multimodal sensing enables agents to interact with the physical world with unprecedented fidelity and robustness.

Jiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University, working on computer vision, machine learning, robotics, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu’s research has been recognized through the Young Investigator Programs (YIP) by ONR and by AFOSR, the NSF CAREER award, the Okawa research grant, the AI’s 10 to Watch by IEEE Intelligent Systems, paper awards and finalists at ICCV, CVPR, SIGGRAPH Asia, ICRA, CoRL, and IROS, dissertation awards from ACM, AAAI, and MIT, the 2020 Samsung AI Researcher of the Year, and faculty research awards from Google, J.P. Morgan, Samsung, Amazon, and Meta.