Spotlight on Our Summer Intern: Asad Ahmad 

Summer Intern Spotlight: This summer, we were delighted to welcome Asad Ahmad to Neuranics as an intern supporting our sensor and ASIC teams. Currently studying for a BSc in Physics at Imperial College London, Asad joined with a strong interest in TMR sensing, electronic instrumentation and signal analysis and a clear enthusiasm for applying his academic learning to real-world technology. 

During his internship, Asad contributed to a wide range of testing and development activities. He automated instruments including oscilloscopes, source measurement units, function generators, power supplies, and audio precision analysers. He also designed control code, built a comprehensive testbench for our first ASIC design, and supported data acquisition and signal interpretation workflows. Beyond automation, he took on practical lab challenges such as soldering, refining connections, and ensuring clean interfaces between instruments and test chips. 

Asad brought analytical thinking and a calm, thoughtful approach to his work. He carried out DC and AC characterisation including noise, transfer-function, and gain testing, while applying his skills in Python to create automated routines that improved efficiency and consistency. His curiosity and interest in modelling and measuring physical signals strengthened the impact of his contributions. 

Reflecting on his time at Neuranics, Asad shared: 

“During my internship I focused on building a reliable measurement pipeline for our first test chips. I carried out DC and AC characterisation including noise, transfer-function, and gain, then fed those results back into our system-level verification. A big part of my contribution was instrument automation. After digging into the user manuals and existing control code, I wrote Python scripts to automate repeatable test routines, which improved consistency and sped up data collection. This work strengthened my interest in modelling and measuring physical signals and gave me hands-on experience turning experimental requirements into robust, automated strategies.” 

Asad also reflected on the highlights of his work: 

“I am proud of building a Python-based automation suite that reduced several manual steps into a single, repeatable routine, speeding up measurements while improving consistency. My favourite part was linking careful lab work, such as soldering and cable setup with the clean datasets that strengthened verification. A challenge I especially enjoyed was tracking down intermittent noise and gain anomalies by refining grounding and cabling, then validating the fixes through automation. I’m also grateful to Neuranics for the opportunity to work alongside a leading-edge ASIC and sensor team, and especially to my mentor Farman, whose guidance was invaluable during my internship.” 

We appreciated the perspective that an early-career physicist brought to our work, and Asad’s interest in real-time signal analysis and physical system modelling was a great fit for our environment. His contribution helped inform some of our internal validation processes and test planning, and we look forward to seeing how his studies and future projects develop. 

The Neuranics team would like to thank Asad for his time and contributions this summer. It was a pleasure having him with us, and we wish him all the best as he continues his studies and future career.