My PhD Journey: Exploring Neuromorphic Computing and Bio-Inspired AI
As I progress through my PhD journey in Electrical Engineering at Pennsylvania State University, I wanted to share some reflections on the fascinating world of neuromorphic computing and bio-inspired artificial intelligence that has captivated my research focus.
The Beginning: From Bangladesh to Penn State
My journey into neuromorphic computing began during my undergraduate studies at Bangladesh University of Engineering & Technology (BUET), where I first encountered the intricate relationships between electronics, signal processing, and computational systems. The transition from theoretical coursework to cutting-edge research has been both challenging and incredibly rewarding.
Starting my PhD program in August 2022 under the supervision of Dr. Abhronil Sengupta opened up an entirely new perspective on how we can design computing systems that mimic the efficiency and adaptability of biological neural networks.
Research Focus: Where Biology Meets Technology
Neuromorphic Computing
One of the most exciting aspects of my research is working on neuromorphic devices that can process information in ways similar to the human brain. Unlike traditional digital computers that separate memory and processing, neuromorphic systems integrate these functions, leading to:
- Energy Efficiency: Dramatically reduced power consumption compared to conventional systems
- Adaptive Learning: Ability to learn and adapt in real-time
- Fault Tolerance: Graceful degradation rather than catastrophic failure
Device-Circuit Co-design
My work involves developing novel approaches to device-circuit co-design, focusing on:
- Spintronic Devices: Exploring spin-based electronics for next-generation computing
- Ferroelectric Materials: Investigating memory devices with non-volatile characteristics
- Spiking Neural Networks (SNNs): Implementing brain-inspired communication protocols
Recent Achievements
I’m particularly proud of some recent milestones in my research journey:
Publications and Recognition
- IEEE TCDS Publication (2025): “Delving deeper into astromorphic transformers” - exploring bio-inspired transformer architectures
- Matter Collaboration (2024): Contributing to groundbreaking work on neuromorphic devices with adaptive hydrogen gradients
- Accessibility Innovation: Developing ultra-low-cost electronic Braille devices, presented at iCACCESS 2024
Industry Experience
My internship at Intel Corporation has provided invaluable hands-on experience with:
- Thin film processes for advanced memory and logic
- ML hardware development for edge AI applications
- Industrial-scale neuromorphic computing implementations
Challenges and Learning
Technical Challenges
Working at the intersection of materials science, electrical engineering, and computer science presents unique challenges:
- Multi-scale Design: Balancing device physics with system-level performance
- Fabrication Constraints: Translating theoretical designs into practical implementations
- Performance Metrics: Developing appropriate benchmarks for bio-inspired systems
Personal Growth
The PhD journey has taught me:
- Patience and Persistence: Research breakthroughs often come after months of incremental progress
- Interdisciplinary Thinking: Drawing insights from neuroscience, materials science, and computer engineering
- Collaboration: Working with researchers across different fields and institutions
Future Directions
As I look toward the completion of my PhD, I’m excited about several emerging research directions:
Emerging Technologies
- Quantum-Neuromorphic Interfaces: Exploring hybrid quantum-neuromorphic computing paradigms
- Bio-Hybrid Systems: Integrating biological and artificial neural networks
- Edge AI Applications: Deploying neuromorphic systems for real-world applications
Broader Impact
Beyond technical innovations, I’m passionate about:
- Accessibility Technology: Continuing work on assistive devices for persons with disabilities
- Educational Outreach: Sharing knowledge through teaching and mentoring
- Global Collaboration: Building bridges between research communities worldwide
Teaching and Mentoring
My role as a Graduate Teaching Assistant has been equally rewarding, working with:
- Cadence Virtuoso: Teaching advanced EDA tools and design methodologies
- Circuit Design: Mentoring students in schematic and layout design
- Lab Supervision: Guiding hands-on learning experiences
Looking Ahead
As I continue this journey, I’m constantly amazed by the potential of neuromorphic computing to revolutionize how we approach artificial intelligence and computing in general. The field is rapidly evolving, and I feel privileged to contribute to this transformation.
The support from my advisor Dr. Abhronil Sengupta, collaborators, and the broader Penn State community has been instrumental in this journey. I look forward to sharing more updates as my research progresses and new discoveries emerge.
Connect and Collaborate
I’m always interested in discussing research, sharing ideas, and exploring potential collaborations. Feel free to reach out if you’re working on related topics or if you’d like to learn more about neuromorphic computing!
What aspects of neuromorphic computing or my research journey would you like to know more about? I’d love to hear your thoughts and questions in the comments below.