Xin (Jennifer) Chen Delivers Student Commencement Address
“To me, IEOR is not just an academic discipline; it’s fundamentally an art of thinking. Industrial Engineers articulate real-world problems through a diverse array of stylized mathematical models—whether it’s a queueing model, a stochastic optimization model, or a fluid dynamics model. Then, we develop and apply techniques in optimization, stochastics, and simulation to devise solutions.”
—Xin (Jennifer) Chen, BS IEOR ’24
On Tuesday, May 14, Jennifer Chen delivered the following speech to IEOR graduates during the Berkeley IEOR Commencement Reception:
I want to extend my gratitude to all the faculty, staff, family, and friends gathered here today. Your unwavering support has played a crucial role in guiding us to this significant moment, and we deeply value your presence here today.
I’m Xin Chen, also known as Jennifer, and it is my immense honor to deliver the commencement address for the IEOR department today.
First and foremost, congratulations to all my fellow graduates! You have persevered through countless challenges to reach this day, so take a moment—take all the moments you need—to celebrate your hard work and remarkable achievements!
Often, I’m asked about the essence of IEOR, and I believe many of you have also received the same question. It took me years to grasp just the surface of what this field encompasses. To me, IEOR is not just an academic discipline; it’s fundamentally an art of thinking. Industrial Engineers articulate real-world problems through a diverse array of stylized mathematical models—whether it’s a queueing model, a stochastic optimization model, or a fluid dynamics model. Then, we develop and apply techniques in optimization, stochastics, and simulation to devise solutions.
The adaptable nature of IEOR techniques allows us to tackle problems across virtually any domain. Methodologically, we push the boundaries in optimization, causal inference, data science, and many more theoretical fields. Practically, we are pivotal in managing and optimizing systems in healthcare, service industries, manufacturing, among others. This adaptability was evident in our senior projects, which addressed a diverse set of challenges in inventory planning, healthcare, and marketing, to name a few.
In an era marked by rapid technological advancements, we IEOR graduates are uniquely prepared to drive change. This preparation involves a blend of interdisciplinary skills and diverse perspectives. While we might not specialize in developing large language models like computer scientists, our foundation in optimization enables us to tackle highly relevant issues like algorithmic fairness, differential privacy, and human-ai interaction. Even if we aren’t medical professionals, our skills in stochastic modeling and matching algorithms, in addition to new data sources arising from the digitization of healthcare, can revolutionize patient flow, organ transplantation, and other healthcare operations. And though we are not environmental scientists, our proficiency in mathematical modeling and incentive design can foster environmentally sustainable practices.
Collaborating with domain experts, we formulate representative models and derive optimal strategies or insights tailored to specific challenges. I am excited to see how each of you will apply your distinctive skills and perspectives to make a positive impact on the world.
IEOR is a also field defined by inclusion and diversity, which I believe many of us have experienced during our time at Berkeley IEOR. I am profoundly thankful for the research and teaching opportunities provided here, which have significantly shaped my career aspirations. A huge thanks to our faculty, staff, and my classmates—your contributions have greatly enriched our journey.
Finally, congratulations once again to my fellow graduates. I wish you all the best in your future endeavors.