Sharat Batra, PhD

Sharat Batra is a senior technologist and systems architect with over four decades of experience designing, scaling, and delivering complex hardware and data-driven systems in high-reliability environments. His career spans foundational work in magnetic and semiconductor materials, large-scale data storage architectures, AI-driven manufacturing optimization, and emerging quantum computing systems—bridging first-principles physics with real-world product execution.

Sharat is widely recognized for his ability to translate deep technical research into manufacturable, field-ready technologies. At Western Digital and Seagate Technology, he led nanofabrication-intensive R&D and product programs that shaped industry roadmaps, including Shingled Magnetic Recording (SMR), Microwave-Assisted Magnetic Recording (MAMR), and Heat-Assisted Magnetic Recording (HAMR)—technologies that underpin today's AI-driven data infrastructure. His work has resulted in 50+ issued patents and trade secrets and 40+ refereed journal publications in magnetism, recording physics, and semiconductor growth.

A defining theme of Sharat's work is the responsible application of AI and machine learning in physics-constrained systems. As NAND Product Program Manager, he applied ML-driven test optimization and predictive failure analysis to manufacturing, achieving over $30M in cost savings while improving yield and reliability. His approach emphasizes interpretability, robustness, and manufacturability—recognizing that ML in hardware systems must withstand process variation, material uncertainty, and regulatory constraints.

In parallel with his industry leadership, Sharat is deeply engaged in quantum computing systems awareness and benchmarking. Through his entrepreneurial venture, Coherent Quantum, he advises organizations on quantum readiness, optimization methods, and the integration challenges that lie between laboratory demonstrations and deployable systems. His interests include physics-informed neural networks (PINNs) and quantum-adjacent optimization techniques that combine physical insight with data-driven performance.

Sharat currently serves as an Adjunct Professor in Electrical and Computer Engineering at the University of Minnesota, where he teaches circuits, semiconductor materials, and senior design. His teaching philosophy mirrors his industry practice: systems thinking, ethical engineering, and an end-to-end understanding of how technologies move from concept to product. He is particularly committed to mentoring students from underrepresented backgrounds and preparing engineers to work across hardware, AI, and emerging quantum technologies.

How others describe their work

• Recognized as a senior technologist translating deep physics into scalable hardware systems.
• Expert in AI/ML applied to high-reliability manufacturing and qualification processes.
• Architect of industry-defining data storage technologies (SMR, MAMR, HAMR).
• Trusted advisor on quantum computing systems and benchmarking.
• Valued as a mentor and educator shaping systems-level engineering leaders.