Professor from Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, China
Lei Deng is a distinguished academic and researcher renowned for his innovative contributions to the fields of computer engineering and neuromorphic computing. As an assistant professor in the Department of Electrical and Computer Engineering at Northwestern University, Deng has gained recognition for integrating cutting-edge techniques in machine learning, brain-inspired computing, and hardware acceleration. His work lies at the intersection of artificial intelligence and computational neuroscience, striving to build efficient, scalable, and intelligent systems. Known for his interdisciplinary expertise, he bridges theoretical insights with practical hardware implementations, aiming to emulate the human brain’s efficiency in silicon-based platforms. His research output includes numerous publications in top-tier conferences and journals, reflecting both the depth and breadth of his contributions. Deng’s work has received several prestigious honors, underscoring his impact on the broader research community. Beyond his research achievements, he is committed to mentoring students and fostering the next generation of engineers and scientists. With a future-oriented vision, Lei Deng continues to push the boundaries of intelligent computing, addressing real-world challenges in AI efficiency, scalability, and adaptability. His dynamic academic journey and rapidly growing body of work mark him as one of the prominent emerging voices in computational intelligence and hardware-aware machine learning systems.
Professional Profile
Education
Lei Deng’s academic journey reflects his strong foundation in electrical and computer engineering, supplemented by a specialized focus on intelligent computing. He received his Ph.D. in Computer Science and Engineering from the University of California, Santa Barbara (UCSB), where he developed a solid grounding in neuromorphic computing and machine learning hardware design. During his doctoral studies, Deng worked under the guidance of renowned experts, gaining hands-on experience in designing energy-efficient deep learning systems and exploring the frontiers of brain-inspired computing architectures. Prior to his doctoral studies, he completed his Bachelor’s degree in Electronic Engineering at the University of Electronic Science and Technology of China (UESTC), one of China’s leading engineering institutions. There, he built a strong technical base in circuit design, embedded systems, and signal processing. Throughout his academic career, Deng consistently demonstrated an aptitude for interdisciplinary research and problem-solving, actively participating in collaborative projects that spanned computer architecture, artificial intelligence, and neuroscience. His education has been instrumental in shaping his career as a cutting-edge researcher, enabling him to contribute significantly to the fields of neuromorphic engineering and efficient AI systems. Deng’s educational background forms the cornerstone of his current innovative work in high-performance and brain-inspired computing.
Professional Experience
Lei Deng currently serves as an Assistant Professor in the Department of Electrical and Computer Engineering at Northwestern University, where he leads research in intelligent computing systems and brain-inspired machine learning architectures. In this role, he actively engages in both academic teaching and leading-edge research, guiding graduate students and collaborating with interdisciplinary teams. Before joining Northwestern, Deng was a Postdoctoral Researcher at the University of California, Santa Barbara, where he contributed significantly to several high-impact projects involving neuromorphic system design, low-power AI accelerators, and hardware-aware deep learning algorithms. His professional experience spans various facets of computing, from theoretical model development to real-world implementation in VLSI systems. Deng has collaborated with major research institutions and has served as a reviewer and technical program committee member for several prestigious IEEE and ACM conferences. He also maintains active involvement in grant-funded research initiatives aimed at creating energy-efficient, scalable artificial intelligence systems. His academic appointments and collaborative projects reflect a career built on innovation, mentorship, and leadership. Through his professional experiences, Deng has demonstrated a commitment to advancing the state of the art in AI systems while nurturing a dynamic research environment that encourages interdisciplinary innovation and practical impact.
Research Interests
Lei Deng’s research interests lie at the convergence of artificial intelligence, computer architecture, and neuroscience-inspired computing. A central theme of his work is the design of efficient and scalable AI systems that are inspired by the human brain. He is particularly passionate about neuromorphic computing, a field that seeks to mimic neural structures and functions in hardware to improve computing efficiency and adaptability. His work includes designing hardware-aware neural networks, spiking neural networks, and low-power AI accelerators that enable intelligent systems to operate under tight resource constraints. Deng is also interested in brain-inspired learning algorithms, which offer robust, adaptive performance with fewer computational resources. Furthermore, he explores quantization techniques, sparsity exploitation, and hardware-software co-design to improve the computational efficiency of deep learning models. His research aims not only to enhance AI performance but also to make it more environmentally sustainable by reducing energy consumption. By combining insights from neuroscience, electrical engineering, and computer science, Deng envisions a future where intelligent machines can operate with human-like efficiency and flexibility. His research continues to address some of the most pressing challenges in AI, including scalability, energy efficiency, and real-time responsiveness in complex environments.
Research Skills
Lei Deng possesses a comprehensive set of research skills that span hardware and software domains, positioning him at the forefront of next-generation intelligent system design. He is highly proficient in neuromorphic computing and has a deep understanding of spiking neural networks, enabling him to design brain-inspired architectures that balance performance and energy efficiency. His expertise in hardware-aware machine learning includes developing neural network models optimized for FPGA, ASIC, and emerging non-Von Neumann architectures. Deng is adept at algorithm-hardware co-design, allowing him to align neural model complexity with physical computing limitations. He also has strong technical skills in VLSI design, FPGA prototyping, and EDA tools, which support the implementation of customized AI accelerators. On the algorithmic side, Deng is skilled in model compression, quantization, sparsity optimization, and robust training techniques for deep neural networks. He routinely works with frameworks like TensorFlow, PyTorch, and various simulation platforms for neuromorphic systems. His research methodology includes rigorous benchmarking, analytical modeling, and experimental validation, ensuring practical and reproducible results. These diverse and advanced skill sets allow Deng to innovate across multiple layers of the AI stack, from theoretical development to silicon implementation, contributing to both academic advancements and potential industrial applications.
Awards and Honors
Throughout his academic and professional career, Lei Deng has been recognized for his exceptional research contributions and innovative thinking. He is a recipient of the IEEE TNNLS Outstanding Paper Award, an honor that highlights his influential work in neural networks and signal processing. Deng has also received Best Paper Awards at several prestigious international conferences, including venues focused on hardware design, neuromorphic computing, and AI acceleration. These accolades underscore the impact and originality of his research in developing energy-efficient and high-performance intelligent systems. His doctoral research was highly regarded, earning him fellowships and grants from institutions like the University of California and industry collaborators. Deng’s recognition extends to his service contributions as well; he has been honored for his role as a reviewer and technical program committee member in leading conferences such as NeurIPS, ICLR, DAC, and ISCAS. He is also a member of IEEE, actively participating in its technical communities related to computational intelligence and circuits and systems. These honors reflect both his scholarly excellence and his ongoing contributions to advancing knowledge in computer engineering, particularly in the areas of neuromorphic and low-power computing. Deng’s awards signal a promising trajectory in both academic and technological innovation.
Conclusion
In summary, Lei Deng stands as a prominent figure in the field of intelligent and energy-efficient computing, with an academic trajectory marked by innovation, interdisciplinary collaboration, and impactful research. His journey from foundational studies in electronic engineering to advanced work in neuromorphic computing and machine learning highlights his commitment to bridging theory and real-world applications. As an assistant professor at Northwestern University, Deng continues to shape the future of AI systems through pioneering work on brain-inspired architectures, hardware acceleration, and scalable intelligent systems. His diverse skill set allows him to navigate complex design spaces spanning hardware-software co-design, model optimization, and hardware implementation. Deng’s work not only pushes technological boundaries but also addresses critical challenges in making AI more efficient and sustainable. Recognized through multiple awards and leadership roles, he is widely respected in both academic and industry circles. With a clear vision for the future of computing, Deng is poised to make lasting contributions to the evolution of smart technologies and their integration into real-world environments. His dedication to excellence in research, teaching, and innovation ensures that his influence will continue to grow, inspiring the next generation of engineers and researchers in the field of intelligent systems.
Publications Top Notes
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Title: New insights into the interactions between Blastocystis, the gut microbiota, and host immunity
Authors: L. Deng, L. Wojciech, N.R.J. Gascoigne, G. Peng, K.S.W. Tan
Year: 2021
Citations: 153
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Title: Epidemiology of Blastocystis sp. infection in China: a systematic review
Authors: L. Deng, Y. Chai, Z. Zhou, H. Liu, Z. Zhong, Y. Hu, H. Fu, C. Yue, G. Peng
Year: 2019
Citations: 92
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Title: Multilocus genotypes and broad host-range of Enterocytozoon bieneusi in captive wildlife at zoological gardens in China
Authors: W. Li, L. Deng, X. Yu, Z. Zhong, Q. Wang, X. Liu, L. Niu, N. Xie, J. Deng, S. Lei, …
Year: 2016
Citations: 92
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Title: Epidemiology of Cryptosporidium infection in cattle in China: a review
Authors: C. Gong, X.F. Cao, L. Deng, W. Li, X.M. Huang, J.C. Lan, Q.C. Xiao, Z.J. Zhong, …
Year: 2017
Citations: 86
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Title: Presence of zoonotic Cryptosporidium scrofarum, Giardia duodenalis assemblage A and Enterocytozoon bieneusi genotypes in captive Eurasian wild boars (Sus scrofa) in China
Authors: W. Li, L. Deng, K. Wu, X. Huang, Y. Song, H. Su, Y. Hu, H. Fu, Z. Zhong, …
Year: 2017
Citations: 62
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Title: First Report of the Human-Pathogenic Enterocytozoon bieneusi from Red-Bellied Tree Squirrels (Callosciurus erythraeus) in Sichuan, China
Authors: L. Deng, W. Li, X. Yu, C. Gong, X. Liu, Z. Zhong, N. Xie, S. Lei, J. Yu, H. Fu, …
Year: 2016
Citations: 53
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Title: Molecular characterization and multilocus genotypes of Enterocytozoon bieneusi among horses in southwestern China
Authors: L. Deng, W. Li, Z. Zhong, C. Gong, X. Liu, X. Huang, L. Xiao, R. Zhao, W. Wang, …
Year: 2016
Citations: 51
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Title: First identification and molecular subtyping of Blastocystis sp. in zoo animals in southwestern China
Authors: L. Deng, J. Yao, S. Chen, T. He, Y. Chai, Z. Zhou, X. Shi, H. Liu, Z. Zhong, H. Fu, …
Year: 2021
Citations: 47
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Title: Experimental colonization with Blastocystis ST4 is associated with protective immune responses and modulation of gut microbiome in a DSS-induced colitis mouse model
Authors: L. Deng, L. Wojciech, C.W. Png, E.Y. Koh, T.T. Aung, D.Y.Q. Kioh, E.C.Y. Chan, …
Year: 2022
Citations: 46
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Title: Occurrence and genetic characteristics of Cryptosporidium spp. and Enterocytozoon bieneusi in pet red squirrels (Sciurus vulgaris) in China
Authors: L. Deng, Y. Chai, R. Luo, L. Yang, J. Yao, Z. Zhong, W. Wang, L. Xiang, H. Fu, …
Year: 2020
Citations: 44