“Nano- and Micromagnetics and Spintronics for Biomedical and Life Science Applications
n this talk, I will overview my group effort on biomagnetic research including detection of diseases. Then I will focus reporting our team’s recent magnetic biomedical brain related research: 1) micromagnetic neural stimulation (μMS) [1]; 2) spintronic neural sensing [2]. First, designing, fabrication and testing of two micromagnetic implants – the Magnetic Pen (MagPen), a solenoid-shaped single µcoil prototype and the Magnetic Patch (MagPatch), a rectangular helix shaped planar µcoil array prototype, will be reported. The efficacy of micromagnetic activation using MagPen has been tested over the following rodent models [3,4,5]: on the rat hippocampal CA3-CA1 synaptic pathway in vitro; on the medial forebrain bundle (MFB) of rodents for the study of striatal dopamine release in vivo; on the rat sciatic nerve to demonstrate the dose-response relationship for µMS in vivo; and, on the vagus nerve to demonstrate fiber-specific activation of the nerve in vivo. The MagPen prototype had its own caveat in terms of mm-size, lack of multidimensional spatial control and activation at the cellular-level. To bridge this research gap, the MagPatch array was designed and fabricated with the goal to study μMS at the single cell resolution. Second, we used FEM exemplary models and open-source computational libraries and calculated the magnetic fields generated by individual neurons and neuronal networks at micrometer distances [2]. Our results show that the magnetic field generated by a single-neuron action potential can be detected by ultra-high sensitivity sub-pT magnetic field sensors, which opens the door to future in vivo decoding of neuronal activities through neural networks. Room temperature, high endurance, small volume and low power make spintronic sensors one of the promising candidates for neural sensing. On this aspect, I will review recent experimental progress for the spintronic sensors for neural sensing, with a specific discussion on our effort on spintronic stack design, device fabrication and detection. 1. R. Saha, et al, and JP Wang, Nanotechnology 33 (2022) 182004, 2. D. Tonini, et al, and JP Wang, Ann Biomed Sci Eng. 6 (2022) 019-029; 3. R. Saha, et al, and JP Wang, Journal of Neural Engineering 19 (2022) 016018, 4. R. Saha, et al, and JP Wang, J. Neural Eng. 20 (2023) 036022. 5. R, Saha, et al, and JP Wang, Biomedical Physics and Engineering Express (2024)
This talk reviews our biomagnetic research, emphasizing brain-related biomedical applications. We developed and tested two micromagnetic neural stimulation devices: the MagPen, a solenoid-shaped microcoil implant validated in rodent models for hippocampal, dopamine, sciatic, and vagus nerve stimulation, and the MagPatch, a microcoil array designed for single-cell-resolution stimulation.
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Beyond empirical risk minimization: performance guarantees, distribution shifts, and noise robustness
22/04/2026
The empirical risk minimization (ERM) approach for supervised learning chooses prediction rules that fit training samples and are “simple” (generalize). This approach has been the workhorse of machine learning methods and has enabled a myriad of applications. However, ERM methods strongly rely on the specific training samples available and cannot easily address scenarios affected by distribution shifts or corrupted samples. Robust risk minimization (RRM) is an alternative approach that does not aim to fit training examples and instead chooses prediction rules minimizing the maximum expected loss (risk). This talk presents a learning framework based on the generalized maximum entropy principle that leads to minimax risk classifiers (MRCs). In particular, MRCs can minimize worst-case expected 0-1 loss while providing performance guarantees, and are strongly universally consistent using feature mappings given by characteristic kernels. In addition, the methods presented can provide techniques that are effective in practical situations that defy conventional assumptions, such as scenarios affected by distribution shifts and corrupted samples.
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TOWARDS SECURE AND SUSTAINABLE NON-TERRESTRIAL NETWORKS
20/4/2026
The satellite networks, emerging as megaconstellations, promise significant advancements to eliminating the digital divide, especially with the deployment of direct-to-cell connections on a mass scale. However, deploying such networks remains challenging, requiring innovation in architecture, interoperability, and security. This keynote will provide an accessible overview of the development of non-terrestrial networks (NTNs), emphasizing how they can be seamlessly integrated with terrestrial systems through approaches such as Open Radio Access Networks (O-RAN). The discussion will explore how resource allocation can be configured to ensure efficient operation in heterogeneous networks, while addressing the pressing issues of resilience and security in a highly interconnected space-terrestrial ecosystem. The talk will conclude by highlighting open research directions and long-term opportunities, pointing to how NTNs can evolve into secure, intelligent, and sustainable infrastructures that support inclusive global connectivity..
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