Zhang Xiaochen, Class of 2027 in Electrical Engineering at the Zhejiang University–University of Illinois Urbana-Champaign Institute (ZJUI), has turned his classroom knowledge of mathematics and programming into research that addresses real-world engineering challenges. From power system optimization with renewable energy integration to efficient constraint-solving methods that combine machine learning and mathematical optimization, his work focuses on developing reliable and computationally efficient solutions to complex problems. His efforts have resulted in multiple first- and co-first-author publications, including a paper accepted at NeurIPS and research published in leading international journals such as Applied Energy and Expert Systems with Applications.
Zhang's research journey began in the second semester of his freshman year, when he joined a Student Research Training Program (SRTP) project under the guidance of ZJUI Assistant Professor Qiu Lin. Focusing on optimal power flow (OPF) with renewable energy integration, he explored how to optimize power generation and dispatch while satisfying grid operating constraints and addressing uncertainties associated with renewable energy. Though he initially lacked specialized knowledge and research experience, he gradually built skills in literature review, mathematical modeling, and experimental analysis through close collaboration with his advisor and senior students. As his experience grew, he progressed from completing assigned tasks to taking greater responsibility for algorithm design and manuscript preparation, ultimately leading his SRTP team to an Excellent Project evaluation. His subsequent work on electric vehicle charging loads resulted in three co-first-author journal papers.
Encouraged by ZJUI's interdisciplinary research environment, Zhang later expanded his focus from power system optimization to the intersection of machine learning and mathematical optimization. Inspired by a lecture by ZJUI Assistant Professor Hou Qingchun, he began exploring how learning-based methods could improve computational efficiency while ensuring strict constraint satisfaction. To strengthen his foundations, he independently studied courses in parallel programming, data structures, and deep learning. In subsequent research, he helped incorporate power grid topology into heterogeneous graph neural networks (HGNNs), improving prediction accuracy and demonstrating the value of combining advanced computational techniques with domain-specific knowledge.
Building on these experiences, Zhang explored efficient optimization methods for dynamic networks. In the AT-SKM-Net project, he and his team developed a framework that integrates learning-based constraint selection with efficient computational updates, reducing redundant calculations while maintaining constraint feasibility. The resulting paper, "AT-SKM-Net: An Accelerated Trainable Sampling Kaczmarz-Motzkin Framework for Linear Hard-Constraint Feasibility on Dynamic Graphs," with Zhang as first author, was accepted at NeurIPS, one of the premier international conferences in machine learning. Looking ahead, he hopes to further integrate machine learning with mathematical optimization to develop efficient, reliable, and practical solutions for complex engineering problems.
Beyond academic research, Zhang has actively embraced interdisciplinary collaboration and campus engagement. As a member of the BioElectro Glove innovation team, he contributed to a cross-disciplinary project on mental health screening that won a Gold Award at the Singapore Regional Competition of the China International College Students' Innovation Competition (2025). He has also served as a teaching assistant for courses in rhetorical writing, programming, and differential equations, dedicating over 400 hours to peer tutoring. Through initiatives such as the ZJUI Learning Station, the XinHai Learning Hub, and experience-sharing sessions, he has supported fellow students in their coursework, research, and academic development.
As a student leader in the Residential College Student Committee (RCSC), Zhang has also enriched the International Campus's multicultural community. From organizing Indonesia Culture Sharing activities to supporting High Table Dinners, and other campus events, he has helped foster cross-cultural understanding while strengthening his communication and leadership skills.
Reflecting on his undergraduate journey, Zhang recognizes that research has taught him to think independently and embrace challenges, while teamwork, teaching, and cultural exchange have broadened his perspective. Having been admitted to the doctoral program at the College of Electrical Engineering, Zhejiang University, he is ready to carry his curiosity, dedication, and collaborative spirit into the next chapter of his academic journey.
