Leadership (Startup)

As CTO and co-founder of EdgeRON, I drive the company's mission to revolutionize AI hardware performance using FPGA and ASIC technologies. EdgeRON develops high-performance, energy-efficient AI accelerators that enable edge devices to perform sophisticated machine learning tasks previously possible only in data centers.

Key Innovations

  • Customizable FPGA/ASIC platforms that balance power efficiency and computational performance.

  • Scalable solutions for diverse industries including agriculture, autonomous robotics, IoT, and smart infrastructure.

  • Collaborative R&D ecosystem combining deep research expertise with agile product development.

Entrepreneurial Vision

By harnessing advanced hardware technologies, EdgeRON aims to democratize AI deployment, enabling organizations of all sizes to harness real-time intelligence at the edge—ushering in a new era of autonomous systems and smart devices.

Technical Program Committee Member/Reviewer

  • IET Circuits, Devices and Systems, 2025.

  • International Journal of Communication Systems, Wiley, 2025.

  • 33rd Asian Test Symposium (ATS), IEEE, India, 2024.

  • 6th Intl Conference on Soft Computing and its Engineering Applications, Springer, Thailand, 2024.

  • Intl Conference on Smart Cyber Physical Systems (ICSCPS), Springer, Delhi, India, 2024. (Invited)

  • 3rd Intl IEEE Conference on Computer Vision and Machine Intelligence (CVMI), IIIT Allahbad, 2024.

  • 28th International Symposium on VLSI Design and Test (VDAT), IEEE, VIT Vellore, India, 2024.

  • Scientific Reports, Nature Portfolio, 2022.

  • International Symposium on Smart Electronic Systems (iSES), IEEE, NIT Warangal, India, 2022.

  • 2nd Intl Conference on Computing Methodologies and Communication (ICCMC), IEEE, India, 2018.

  • Intl Conference on Inventive Computing and Informatics (ICICI), IEEE, India, 2017.

Talks/Presentations

  1. Fixed Point Deep Reinforcement Learning with Quantization Aware Training and Adaptive Parallelism,

    58th Design Automation Conference, ACM/IEEE, DACYF, San Francisco, USA, 2021.

  2. FPGA based Hardware for Machine Learning, Bangalore Tech Summit, 2022.

  3. Autonomous robotic control with RL - FPGA, DAAD Germany Delegation, IIIT Bangalore, 2022.

  4. FPGA based Hardware for Machine learning – RISE (In House Research), IIIT Bangalore, 2021.

  5. New approaches to architecting hardware for machine learning – Samvaad Talk – IIIT Bangalore, 2020.

© 2025-2026 Shaik Mohammed Waseem. All rights reserved.