About Me

Mohsen Imani

I am an Assistant Professor in the Department of Computer Science at UC Irvine. I am also a director of Bio-Inspired Architecture and Systems (BIASLab). My group is working on a wide range of practical problems in the area of bio-inspired computing, machine learning, computer architecture, and embedded systems. Our research goal is to design real-time, robust, and programmable computing platforms that cover a wide range of learning, cognitive, and genomics tasks. We also design secure and scalable learning framework for distributed learning/computing over swarm of edge devices in IoT systems.

I received my Ph.D. from the Department of Computer Science and Engineering at the UC San Diego. I have a stellar record of publication with over 80 papers in top conferences/journals (publication list). My contribution has led to a new direction on brain-inspired hyperdimensional computing that enables ultra-efficient and real-time learning and cognitive support. My research was also the main initiative in opening up multiple industrial and governmental research programs. My research has been recognized with several awards, including the Bernard and Sophia Gordon Engineering Leadership Award, the Outstanding Researcher Award, and the Powell Fellowship Award. I also received the Best Doctorate Research from UCSD and several best paper nomination awards at multiple top conferences including Design Automation Conference in 2019 and 2020, and Design Automation and Test in Europe in 2020.

I'm looking for motivated Ph.D. students for Fall 2020!

Please contact me if you are interested!


With the emergence of the Internet of Things (IoT), sensory and embedded devices are generating massive data streams. Running big data processing algorithms, e.g., machine learning, on embedded devices poses substantial technical challenges due to limited device resources. The goal of our research in BIASLab is to dramatically increase the computing efficiency as well as learning capability of the today’s computers. Our work identifies opportunities for designing future learning and computing systems, which are intelligent, fast, efficient, and reliable. Our solution provides real-time data analysis for many challenging big data applications including: machine learning, security, genomics and bioinformatics, graph processing, and database systems.


The outputs of our research have been published in over 100 top conferences/journals of computer architecture, embedded systems, and machine learning venues.

Conference Papers
Submitted Patents


Mentorship and Diversity

During my PhD, I have closely mentored more than 22 undergraduate and 20 graduate students, including 8 PhD students. I was honored to mentor about 14 female students and have my small contribution to increase diversity in engineering and computing fields. I have published more than 27 papers in the top venue conferences/journals with undergraduates where more than 18 are with minorities. I have also volunteered to participated in ERSP (2018, 2019) and ENLACE (2017, 2018) programs which aim to support undergraduate and the research of Latino students. More information about my Mentorship and contribution to Diversity can be fount below:

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Mentored several Ph.D., Master, and undergraduate students.

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Volunteered as mentor in ELANCE and ERSP programs.

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Please refer to BIASLab Github page.


Donald Bren Hall, Room 3084, Irvine, CA 92617