Amitabh Yadav

amitabh[dot]yadav[at]epfl[dot]ch

I am a Ph.D. Candidate at Neuro-X Institute/EPFL working with Prof. Mahsa Shoaran at the Integrated Neurotechnologies Laboratory. My research focuses on designing low-power digital/mixed-signal integrated circuits for closed-loop brain-computer interfaces.

Research Interests

Low-Power Digital Design · Mixed-Signal Circuits · AI Accelerators
Hardware-Software Co-Design · Deep Learning

Alex, D., Yadav, A., Joo, J., Shin, U., Afzal, A., Liu, J., Diehl, G., Widge, A.S. and Shoaran, M., 2025. "A 32-Channel 196-μW Logarithmic SoC for Brain Network Connectivity Extraction and Adaptive Psychiatric Symptom Classification". In 2025 Symposium on VLSI Technology and Circuits, VLSI Technology and Circuits 2025. IEEE.
Shaeri, M., Shin, U., Yadav, A., Caramellino, R., Rainer, G. and Shoaran, M., 2024. "A 2.46-mm² Miniaturized Brain-Machine Interface (MiBMI) Enabling 31-Class Brain-to-Text Decoding". IEEE Journal of Solid-State Circuits, 59(11), pp.3566-3579.
Shaeri, M.A., Shin, U., Yadav, A., Caramellino, R., Rainer, G. and Shoaran, M., 2024, February. "33.3 MiBMI: A 192/512-channel 2.46 mm² miniaturized brain-machine interface chipset enabling 31-class brain-to-text conversion through distinctive neural codes". In 2024 IEEE International Solid-State Circuits Conference (ISSCC) (Vol. 67, pp. 546-548). IEEE.
Yadav, A., Ceesay-Seitz, K., Boukabache, H., Perrin, D. and Gerber, N., 2022. "ROMULUSLib: An autonomous, TCP/IP-based, multi-architecture C networking library for DAQ and control applications". JACoW, pp.69-76.
Bertels, K., Sarkar, A., Hubregtsen, T., Serrao, M., Mouedenne, A.A., Yadav, A., Krol, A., Ashraf, I. and Almudever, C.G., 2020. "Quantum computer architecture toward full-stack quantum accelerators". IEEE Transactions on Quantum Engineering, 1, pp.1-17.
Yadav, A., Khammassi, N. and Bertels, K., "CC-Spin: A Microarchitecture design for Control of Spin-Qubit Quantum Accelerator", ResearchGate Preprint.
Yadav, A., Kaundal, V., Sharma, A., Sharma, P., Kumar, D. and Badoni, P., 2016, September. "Wireless sensor network based patient health monitoring and tracking system". In Proceeding of International Conference on Intelligent Communication, Control and Devices: ICICCD 2016 (pp. 903-917). Singapore: Springer Singapore.

Featured in the News

[EPFL News] An entire brain-machine interface on a chip

Brain-machine interfaces (BMIs) have emerged as a promising solution for restoring communication and control to individuals with severe motor impairments. Traditionally, these systems have been bulky, power-intensive, and limited in their practical applications. Researchers at EPFL have developed the first high-performance, Miniaturized Brain-Machine Interface (MiBMI), offering an extremely small, low-power, highly accurate, and versatile solution. [Read More]

[LBNL News] Connecting the Dots: Researcher Works to Adapt Image-Recognition Technique Into the Quantum Realm

The planned 2026 upgrade of CERN laboratory’s Large Hadron Collider, the largest particle collider in the world, will produce a higher volume of particle collisions that will necessitate new ways to quickly and efficiently sort through the data using advanced computer algorithms. Researchers are now exploring quantum computing as a possible way to manage this extremely high volume of data. [Read More]

[UC Berkeley News] Particle Physics Turns to Quantum Computing for Solutions to Tomorrow’s Big-Data Problems

Giant-scale physics experiments are increasingly reliant on big data and complex algorithms fed into powerful computers, and managing this multiplying mass of data presents its own unique challenges. To better prepare for this data deluge posed by next-generation upgrades and new experiments, physicists are turning to the fledgling field of quantum computing to find faster ways to analyze the incoming info. [Read More]

[CERN Alumni News] A Great Career Starter

I came to CERN as a summer student in 2017 and I joined the ATLAS Inner Detector team to work on the development of back-end FPGA readout firmware for FE-I4 silicon pixel chip. Upon the phase-II upgrade, the pixel chip will be located in the Inner Tracker of the ATLAS Detector and will detect charged particles originating during every collision event at the High Luminosity LHC. The firmware is responsible for the routing of services and improving the data quality for HL-LHC. [Read More]

[The Tribune] UPES team wins aerospace contest

The UPES team Tesseract, beat IIT Delhi, IIT Madras and BITS Pilani, to emerge the national winner of the Lockheed Martin C130J Super Hercules Aircraft Roll On/ Roll Off University Design Challenge. They were awarded a grant of US $40,000 to develop a prototype of the module. Now, Lockheed Martin will work with the UPES team to explore options with the government and the industry for a mature prototype for global markets. [Read More]

[The Times of India] Indian students win global aerospace competition

Students from Uttarakhand's University of Petroleum and Energy Studies (UPES) have made India proud by winning the first position at the global aerospace competition CanSat held in Texas, US, this year. Team Astral, Indian team, has been participating in CanSat competition since 2013 and this year they left behind 39 teams from across the world to secure no. 1 ranking in the competition. [Read More]