Jingyi Gao | Engineering | Best Researcher Award

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Ms. Jingyi Gao | University of Virginia | United States

Ms. Jingyi Gao | University of Virginia | United States

Jingyi Gao is a Ph.D. candidate in Systems and Information Engineering at the University of Virginia with a 3.75 GPA, focusing on time series prediction, Bayesian probabilistic modeling, and federated learning. She holds an M.S. in Applied Mathematics and Statistics from the Johns Hopkins University (GPA 3.9) and dual bachelor’s degrees in Mathematics–Computer Science and Economics from the University of California, San Diego. Jingyi has extensive teaching experience, serving as a teaching assistant at UVA where she has instructed over 1,000 students across multiple courses in statistical modeling, data mining, AI, and big data systems, and previously supported courses at Johns Hopkins and UC San Diego. She has mentored underrepresented students through the Data Justice Academy and completed research internships at the University of Pittsburgh and Tencent, developing machine learning models for stress detection, healthcare data analysis, and cloud resource forecasting. Jingyi has authored several publications, including work accepted by Pattern Recognition and under review at AAAI and IISE Transactions. Her recent projects involve designing deep latent variable models for ergonomic risk assessment, developing real-time adaptive prediction frameworks for occupational health monitoring, creating federated learning approaches for multi-output Gaussian processes, and modeling behavioral regularity and predictability from multidimensional sensing signals. Combining expertise in machine learning, statistical modeling, and data-driven decision systems, Jingyi aims to advance human-centered intelligent systems through interpretable and privacy-preserving predictive modeling.

Profile: Scopus | Google Scholar

Featured Publications 

Gao, J., Rahman, A., Lim, S., & Chung, S. TimeSets: A real-time adaptive prediction framework for multivariate time series (Manuscript under review at the Association for the Advancement of Artificial Intelligence).

Gao, J., Lim, S., & Chung, S. Gait-based hand load estimation via deep latent variable models with auxiliary information (Manuscript under review at IISE Transactions).

Gao, J., & Chung, S. Federated automatic latent variable selection in multi-output Gaussian processes (Accepted for publication in Pattern Recognition)*.

Gao, J., Yan, R., & Doryab, A. Modeling regularity and predictability in human behavior from multidimensional sensing signals and personal characteristics. Proceedings of the International Conference on Machine Learning and Applications (ICMLA). Institute of Electrical and Electronics Engineers.

Chen, T., Chen, Y., Gao, J., Gao, P., Moon, J. H., Ren, J., … & Woolf, T. B. Machine learning to summarize and provide context for sleep and eating schedules. bioRxiv.

Mohsen Hatami | Electrical and Computer | Best Researcher Award

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Mohsen Hatami | Electrical and Computer | Best Researcher Award

PhD candidate at Binghamton University, United states

Mohsen Hatami is a highly motivated and accomplished Ph.D. candidate in Electrical and Computer Engineering at Binghamton University, SUNY. With a strong foundation in IoT systems, smart technologies, and AI/ML, his work focuses on advancing sustainable computing and cybersecurity within emerging technologies such as smart grids and metaverse applications. Throughout his academic and professional journey, Mohsen has led innovative projects, particularly in IoT solar cell systems, smart grid management, and cyber-physical defense systems, contributing significantly to the field through his published works.

Profile:

Google scholar

Education:

Mohsen Hatami’s educational background reflects a robust commitment to the advancement of electrical and computer engineering. He is currently pursuing a Ph.D. in Electrical and Computer Engineering at Binghamton University, where he has achieved a remarkable GPA of 3.94/4.0. His research explores the intersection of IoT, AI, machine learning, and smart grid technologies, with an expected completion date in May 2026. Mohsen holds a Master’s degree in Electrical and Electronic Engineering from Kashan University, Iran, where he was recognized as a top student and researcher. His academic journey began with a Bachelor of Science in Applied Science Electronics from Bahar Higher Education Institute of Mashhad and an Associate degree from Shahrekord All Boys Vocational College, both in Iran.

Experience:

Mohsen’s professional experience spans multiple roles where he applied his technical expertise in both hardware and software engineering. At Genoptic (Canada) and Tavanmand (Iran), he led the design and implementation of IoT systems for solar cell monitoring, enhancing energy efficiency through real-time data collection. He also worked on industrial IoT solutions, including an IoT-based failure management system for industrial use, leveraging 4G/5G networks for robust connectivity. Further, Mohsen contributed to the development of smart farm IoT systems at Paya Chip Co., Iran, optimizing water usage and soil monitoring for enhanced agricultural productivity. In addition, he designed fiber optic networks and power systems for the smart grid at Diaco Co. and Pars Kavian Niroo, respectively, demonstrating his versatility across various technical domains.

Research Interests:

Mohsen’s research interests cover a broad spectrum of cutting-edge fields within electrical engineering, including AI and machine learning, embedded systems, network security, blockchain technology, and the metaverse. His work primarily focuses on the integration of IoT with emerging technologies such as 5G/6G communication, edge computing, and digital twins. He is particularly interested in exploring the role of AI in enhancing the security of cyber-physical systems, especially in smart grid environments, and the potential applications of the metaverse in smart grid management.

Awards:

Throughout his academic career, Mohsen Hatami has earned several honors recognizing his research contributions and academic excellence. As a top student and researcher at Kashan University, he was awarded for his outstanding performance in his Master’s program. Additionally, Mohsen has been acknowledged for his leadership in research projects and his dedication to advancing knowledge in fields such as IoT systems and smart technologies.

Publications:

Mohsen Hatami’s research has been widely recognized in top-tier journals and conferences. Some of his key publications include:

  1. Hatami, M., Nasab, M. A., Chen, Y., Mohammadi, J., Ardiles-Cruz, E., & Blasch, E. (2024). ELOCESS: An ESS Management Framework for Improved Smart Grid Stability and Flexibility. IEEE Transactions on Consumer Electronics.

  2. Hatami, M., Qu, Q., Chen, Y., Kholidy, H., Blasch, E., & Ardiles-Cruz, E. (2024). A Survey of the Real-Time Metaverse: Challenges and Opportunities. Future Internet, 16(10), 379.

  3. Hatami, M., Nasab, M. A., Zand, M., Padmanaban, S. (2024). Demand Side Management Programs in Smart Grid Through Cloud Computing. Renewable Energy Focus, 51, 100639.

  4. Hatami, M., Khan, M., Zhao, W., Chen, Y. (2024). A Novel Trusted Hardware-Based Scalable Security Framework for IoT Edge Devices. Discover Internet of Things, 4(1), 4.

  5. Hatami, M., Qu, Q., Chen, Y., Mohammadi, J., Blasch, E., Ardiles-Cruz, E. (2024). ANCHOR-Grid: Authenticating Smart Grid Digital Twins Using Real World Anchors.

  6. Hatami, M., Qu, Q., Xu, R., Nagothu, D., Chen, Y., Li, X., Blasch, E., Ardiles-Cruz, E. (2024). The Microverse: A Task-Oriented Edge-Scale Metaverse. Future Internet, 16(2), 60.

  7. Hatami, M., Nikoufard, M. (2018). Analysis of Ultra-Compact TE to TM Polarization Rotator in InGaAsP and SOI Technologies. Optik-International Journal for Light and Electron Optics, 153, 9-15.

Conclusion:

Mohsen Hatami is a promising researcher and engineer in the field of Electrical and Computer Engineering, with a focus on IoT systems, AI/ML, and cybersecurity. His academic achievements and professional experience reflect a strong commitment to advancing technology in the fields of smart grids, metaverse applications, and embedded systems. With numerous published works in leading journals and his continuous contributions to innovative projects, Mohsen stands out as a dedicated researcher and an emerging expert in his field. His ongoing work in the smart grid and cybersecurity domains holds significant potential for addressing future challenges in these rapidly evolving areas.