LATEST IN THE NEWS

April 7, 2026

Vellex Exhibits Highly Efficient AI Training at National Laboratory of the Rockies

Vedant Wakchaware
Vellex Computing was selected to pitch at the 2026 Industry Growth Forum in Denver, presenting its vision for the next generation of AI to investors and corporate leaders. Co-founders Dr. Palak Jain and Jason showcased Vellex’s highly efficient, physics-based computing architecture that enables true self-learning intelligence.
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November 20, 2025

Vellex Showcases Analog Intelligence at Tough Tech Week Demo Day in Boston

Meghesh Saini
Vellex Computing participated in Tough Tech Week 2025 Demo Day in Cambridge, showcasing its Analog Intelligence Platform to investors and deep-tech leaders. CEO Palak Jain presented Vellex’s low-power, high-speed analog AI capabilities and engaged with partners across the tough-tech ecosystem.
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September 16, 2025

Vellex awarded Competitive Grant from the U.S. National Science Foundation

Meghesh Saini
We are proud to announce that we have been awarded the highly competitive National Science Foundation (NSF) Small Business Innovation Research (SBIR) Phase I grant. This milestone marks a significant recognition of our pioneering work in developing physics-inspired computing solutions that transform the way complex control and optimization problems are solved.
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OUR BLOGS

September 12, 2025

6 Things for Business Leaders about the AI chip market

Meghesh Saini
The AI chip market is experiencing explosive growth, projected to exceed $200 billion by 2032. This boom is fueled by specialized processors like GPUs and ASICs, which vastly outperform traditional CPUs for AI tasks. While manufacturing is a high-stakes game, the critical business driver is energy efficiency to manage costs and maximize ROI. These powerful chips are transforming industries from automotive to healthcare. Innovators like Vellex Computing are now pioneering physics-inspired platforms, aiming to deliver a 100X improvement in compute performance per dollar.
September 11, 2025

Solving the Hardest Business Problems with Ising Machines

Meghesh Saini
Oscillator-based Ising machines are revolutionizing how businesses solve complex optimization problems. Unlike traditional computers, they leverage physics to find optimal solutions in microseconds, consuming far less power. Real-world applications include UPS’s route optimization (saving hundreds of millions annually) and real-time energy grid balancing that reduces outages and costs. With speed, scalability, and energy efficiency, these machines are poised to become essential accelerators and drive efficiency, resilience, and competitiveness.
September 9, 2025

Simplifying businesses with Combinatorial Optimization

Meghesh Saini
Combinatorial optimization is becoming a boardroom strategy, not just a technical tool. From robotics to energy and IoT, it transforms complexity into efficiency, resilience, and growth. Verified industry data shows warehouse automation hitting $55B by 2030, IoT scaling to 40B devices, and global energy demand rising 47% by 2050. Businesses that embrace optimization unlock faster fulfillment, lower costs, and greener operations. At Vellex Computing, we help enterprises optimize in split seconds, making systems autonomous, efficient, and future-ready.

OUR PUBLICATIONS

December, 2024

A hybrid-computing solution to nonlinear optimization problems

Kamlesh Sawant; Dillon Nguyen; Alex Liu; Jason Poon; Sairaj Dhople
Published in IEEE Transactions on Circuits and Systems I - Regular Papers, vol. 71, no. 12, pp. 6555-6568, Dec. 2024
May, 2022

Real-time selective harmonic minimization using a hybrid analog/digital computing method

Jason Poon; Mohit Sinha; Sairaj V. Dhople; Juan Rivas-Davila
Published in IEEE Transactions on Power Electronics, vol. 37, no. 5, pp. 5078-5088, May 2022
December, 2021

Decentralized Carrier Phase Shifting for Optimal Harmonic Minimization in Asymmetric Parallel-Connected Inverters

Jason Poon; Brian Johnson; Sairaj V. Dhople; Juan Rivas-Davila
Published in IEEE Transactions on Power Electronics ( Volume: 36, Issue: 5, May 2021)