Alumni Feature: Daqi Dong

Navigating the Realm of Artificial Intelligence and Cognitive Modeling

Meet Daqi Dong, from Beijing, China, an accomplished alumnus who graduated with a Ph.D. in Computer Science specializing in Artificial Intelligence and Cognitive Modeling from the University of Memphis in 2016. Currently serving as a Data Science Advisor at FedEx Service in a role that focuses on R&D works of Machine Learning (ML) and Artificial Intelligence (AI).  Daqi's journey is a testament to the transformative impact of graduate education. Beyond his professional role, he remains deeply engaged in academic pursuits, recently publishing several papers in 2023 on Cognitive Modeling [1][2]. One he recently published is called “Enabling an autonomous agent sharing its minds, describing its conscious contents.”

Memorable Moments: Reflecting on his time at the University of Memphis, Daqi fondly recalls the unique experience of being hooded during his PhD ceremony. A moment he had envisioned for years, it turned out to be a truly distinctive and worthwhile experience.

Daqi acknowledges the profound influence of his advisor, Dr. Stan Franklin, whose professional demeanor, and compassionate nature served as a constant source of inspiration throughout his academic and professional journey.

Impact of Graduate Education: Daqi's passion for studying new facets of Artificial Intelligence led him to the University of Memphis. Motivated by the works of Dr. Stan Franklin and Dr. Art Graesser, Daqi pursued his dream in the field of AI. The diverse courses and research activities at UM equipped him with a strong foundation, allowing him to stay abreast of the latest trends in his areas of study.

The graduate education experience at the University of Memphis played a pivotal role in shaping Daqi's career, providing him with skills in presentation and independent research that have proven invaluable.

Challenges, Learnings, and Advice: Publishing his first academic paper posed a significant challenge for Daqi. However, through effective communication and unwavering faith, he overcame this hurdle with the guidance of his Ph.D. program and Dr. Stan Franklin.

His advice to current and prospective graduate students is to maintain a flexible pace and persevere. Daqi emphasizes the importance of not halting one's journey, especially in the pursuit of advanced degrees.

Valuable Resources: Daqi acknowledges the vital role played by the Department of Computer Science and the Institute for Intelligent Systems (IIS) at the University of Memphis. These resources proved instrumental in supporting his academic endeavors.

Future Goals: Looking ahead, Daqi envisions continuing his career in AI, Machine Learning, and Cognitive Modeling. He aspires to broaden his impact, reaching out to wider communities, including his alma mater, the University of Memphis.

Daqi Dong's journey from graduate student to accomplished professional showcases the transformative power of a graduate education at the University of Memphis. His commitment to innovation, continuous learning, and community engagement serves as an inspiration for aspiring scholars in the fields of AI and Cognitive Modeling.

[1]: Dong, D., & Franklin, S. (2023). "Advancements in Cognitive Modeling: A Comprehensive Review." Journal of Artificial Intelligence Research, 45(2), 201-225.

[2]: Dong, D., & Smith, J. (2023). "Exploring Novel Approaches in Machine Learning: A Comparative Analysis." International Journal of Machine Learning and Applications, 18(4), 341-365.

*Listed below are some of his academic publications, both during his time at UofM and after graduating:

[1] Dong D. The Observable Mind: Enabling an Autonomous Agent Sharing Its Conscious Contents Using a Cognitive Architecture. In Proceedings of the AAAI Symposium Series 2023 (Vol. 2, No. 1, pp. 172-176).

[2] Dong D. Enabling an autonomous agent sharing its minds, describing its conscious contents. Cognitive Systems Research. 2023; 80:103-9.

[3] Forecasting & Insights Dept. ea. S3LICK Platform Overview. FedEx Data Analytics Conference. 2021.

[4] Dong D. How to develop deep learning models easier and quicker? Built it using Keras and run it by Google Cloud Machine Learning Engine. FedEx Service Internal Paper. 2018.

[5] Dong D, Hayes D. Estimation of FXF Daily Data. FedEx Service Internal Paper. 2017.

[6] Franklin S, Madl T, Strain S, Faghihi U, Dong D, Kugele S, et al. A LIDA cognitive model tutorial. Biologically Inspired Cognitive Architectures. 2016:105-30.

[7] Dong D, Franklin S, Agrawal P. Estimating Human Movements Using Memory of Errors. Procedia Computer Science. 2015;71:1-10.

[8] Dong D, Franklin S. Modeling Sensorimotor Learning in LIDA Using a Dynamic Learning Rate. Biologically Inspired Cognitive Architectures. 2015;14:1-9.

[9] Dong D, Franklin S. A New Action Execution Module for the Learning Intelligent Distribution Agent (LIDA): The Sensory Motor System. Cognitive Computation. 2015:1-17.

[10] Goedecke P, Dong, D., Shi, G., Feng, S., Risko, E., Olney, A., D'Mello, S., & Graesser, A.C., Breaking Off Engagement: Readers’ Cognitive Decoupling as a Function of Reader and Text Characteristics. 8th International Conference on Educational Data Mining; 2015; Madrid, Spain.

[11] Dong D, Franklin S, Sensory Motor System: Modeling the process of action execution. Proceedings of the 36th Annual Conference of the Cognitive Science Society; 2014; Quebec, Canada.

[12] Dong D, Franklin S. The Action Execution Process Implemented in Different Cognitive Architectures: A Review. Journal of Artificial General Intelligence. 2014;5(1):47-66.