Saurav Maji is a PhD candidate whose research is focused on security challenges, and solutions, for Internet of Things (IoT) devices. His past achievements include projects to enhance the security of implantable medical devices, while his current work addresses the need for improved security in machine-learning and agricultural applications. As a MathWorks Fellow, Saurav will advance two projects concerning side-channel security issues for embedded neural network hardware and software implementations, with the goals of implementing robust neural networks and providing end-to-end security. In the first project, Saurav has demonstrated the potential for significant information leaks on neural networks through timing-based attacks and devised a simple, cost-effective neural network accelerator with low-overhead error detection features. His second project addresses security challenges in agriculture applications, such as the increased circulation of counterfeit seeds and other products that threaten both smallholder farms and sustainable food production. Saurav’s research has yielded innovative, hardware security and materials solutions to stem these threats. MATLAB is an indispensable tool in Saurav’s research, advancing high-impact research with the potential to offer improved, low-cost security for a wide range of IoT devices and applications.