Balancing intelligent computing with sustainable energy solutions will be a crucial challenge — and an enormous opportunity — for impactful interdisciplinary research across academia and industry. CEEE is at the forefront of this.
It seems almost magical. Just a few clicks online to order an item — be it allergy medication to get you through the day or a last-minute birthday present — and it arrives at your doorstep in as little as an hour. Behind that “magic” are complex algorithms and artificial intelligence (AI) that forecast product supply and demand, optimize routing and driver dispatching, and predict an estimated time of arrival. At Walmart, CEEE alumnus Tao Cao, Ph.D. ’16, helps lead the retail giant’s applied AI, tackling real-word challenges that drive business success — and ensuring that all those birthday gifts arrive on time.
After earning his Ph.D. in mechanical engineering in 2016 from the University of Maryland, Cao worked at Daikin Comfort as a lead engineer and machine learning consultant before returning to CEEE as postdoctoral associate in 2018, specializing in machine learning-enabled research. Since 2022, he’s worked in applied AI for Walmart Global Tech in San Francisco. We checked in with Cao to find out about his career, his thoughts on the future of AI and his memories of his time at CEEE.
Tell us about your job in applied AI at Walmart. How have you helped Walmart incorporate AI and machine learning into its operations?
As a tech lead for applied AI at Walmart, I lead several core pillars that power Walmart’s online pickup and delivery platform. Our team builds AI-driven systems that make it possible for millions of customers to receive their orders quickly and reliably — sometimes within just an hour. When you open the Walmart app, place an order, and see an estimated delivery time, or when your order is seamlessly assigned to a nearby gig driver, our work sits behind that experience. We design and deploy scalable solutions for delivery-time estimation, driver search and dispatch optimization — leveraging techniques from machine learning, optimization, simulation and emerging agentic AI to bring intelligent decision-making to Walmart’s scale.
How did you make the switch from HVAC-related research to AI development for a large retailer?
As a CEEE postdoc, I contributed to and led several projects using machine learning to solve real-world challenges in the HVAC field, including forecasting, machine learning assisted system design and fault detection. I had a good run in these projects, and built more interests in machine learning over time. That passion continued to grow, and ultimately, I chose to build my career around AI more broadly, leading me to my current role.
How did your experience at CEEE translate to your work at Walmart?
CEEE taught me how to communicate ideas clearly and persuasively — a skill I first developed through consortium meetings, sponsor presentations and conference discussions. That ability to explain complex concepts to diverse audiences is now central to my role as a tech lead, where aligning scientists, engineers and business stakeholders is key to turning ideas into real products. Those early experiences at CEEE built the foundation for how I lead teams and drive impact today — through clear communication, structured problem-solving and collaboration across disciplines.
How else did your time at CEEE prepare you for your career?
Time management and open collaboration were two lasting lessons. I learned from CEEE faculty members how to manage multiple projects efficiently while staying focused on core objectives. I also remember countless brainstorming sessions where we turned rough ideas into tangible outcomes through teamwork and iteration. That mindset — structured prioritization and open, creative collaboration — still guides how I lead complex projects and teams in industry today.
Do you have any predictions on how AI might affect engineering research in the future?
AI is rapidly lowering the barriers to knowledge and reproducibility. Tasks that once took weeks can now be explored in hours, transforming the pace of innovation. The incoming trends are using AI to turn creative ideas into tangible deliverables — prototypes, proposals or papers — faster than ever.
I also see AI and energy becoming deeply intertwined. As AI capabilities expand, so do their energy demands. Balancing intelligent computing with sustainable energy solutions will be a crucial challenge — and an enormous opportunity — for impactful interdisciplinary research across academia and industry. CEEE is at the forefront of this.
Are you referring partly to the increased need for data center cooling?
Yes, the investment in AI infrastructure, such as data centers, also means significant demands on thermal management. When scales increase that much, it calls for better solutions to bring down the cost and environmental impacts.
What is your proudest professional accomplishment?
I’m most proud of leading large-scale AI initiatives that create real-world impact at enterprise level, while also contributing back to the AI research community. One highlight was having our work accepted and presented at KDD 2024, one of the world’s top conferences in applied AI. That achievement reflects a balance I deeply value — building robust, production-scale AI systems that deliver measurable business results, while distilling our learnings into research that advances the field.
What is your favorite memory from your time at CEEE?
Our Friday group lunches remain my fondest memory — lively conversations about research, life and everything in between. We built lasting friendships and a sense of community that I still treasure today. Many of my closest friends around the world trace back to those CEEE days.
How do you spend your leisure time?
I recharge through outdoor activities — playing pickleball, tennis, badminton, rock climbing, biking, and hiking with my wife and our dog. I also cherish family time, including calls and visits to my parents and family members in China that always bring back the best memories.
What is one piece of advice you would pass along to current CEEE students?
Never stop learning, and stay open to learning from anyone — not just in technical areas, but in communication, leadership and teamwork. Every interaction is an opportunity to grow. The habits you develop at CEEE — curiosity, rigor and collaboration — will stay with you far beyond graduation and shape your success in any career path.
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