Throughout Climate Week, Baskin Engineering faculty integrated climate science-focused lectures into their courses, demonstrating how a range of disciplines contribute to real-world climate solutions. Students learned about topics including energy efficiency in data science, renewable energy technologies, the application of statistics in global warming research, and AI-driven weather and climate predictions.
Nicholas Brummel, Professor of Applied Mathematics
AM250: An Introduction to High Performance Computing
AM107: Introduction to Fluid Dynamics
As part of the motivation for his current high-performance computing course, AM 250 “Introduction to High-Performance Computing,” Brummel highlights major examples of how HPC helps solve complex problems. He often uses climate models to demonstrate how faster computing at higher resolution leads to more accurate simulations, such as the separation of the Gulf Stream at Cape Hatteras and the identification of hurricanes in the tropics.
Papri Dey, Visiting Assistant Profesor of Applied Mathematics
AM30: Multivariate Calculus for Engineers
Dey covered topics such as multivariable functions, level curves, and level surfaces. She also discussed partial derivatives, gradient vectors, and their geometric interpretation. As an application of gradient vectors, she revisited an example from the first lecture of the AM 30 Spring 2025 course, which explored temperature variation over space and time. In this example, temperature is represented as a function T(x, y, z, t), where x, y and z are spatial coordinates and t is time. Partial derivatives such as ∂T/∂t represent the rate of temperature change over time—such as global warming trends—while the gradient ∇T indicates the direction and rate of the greatest temperature increase.
Rebecca DuBois, Professor of Biomolecular Engineering
BME 281D: Seminar on Protein Engineering
DuBois discussed ways in which protein engineering is used to address climate change issues. In one example, the class discussed how engineered protein vaccines have the potential to reduce disease and death in agricultural animals, making these farms more efficient and reducing overall CO2 emissions. In another example, they discussed how plastic-degrading proteins have been engineered to increase their activity, holding the potential for “green” solutions to plastic recycling. Finally, the class discussed how engineered proteins are being used in the development of carbon capture technologies.
Jason Eshraghian, Assistant Professor of Electrical and Computer Engineering
ECE 173: High Speed Digital Design
Eshraghian and his class discussed how data centers and electronic systems drive a growing share of global energy use, which means that optimizing signal integrity and PCB design is critical for building more sustainable, climate-conscious technology infrastructure. PCB design directly impacts energy efficiency by minimizing signal loss, reducing unnecessary power consumption and enabling faster, lower-power electronics.
Javier Gonzalez-Rocha, Assistant Professor of Applied Mathematics
AM213: Numerical Solutions of Differential Equations
Gonzalez-Rocha focused on how numerical solvers can be applied to improve our understanding of greenhouse gas transport, highlighting their role in modeling atmospheric processes.
Beth Ann Hockey, NLP Instructor
Natural Language Processing
Hockey discussed the issues of climate change and sustainability in her NLP course: NLP203: Natural Language Processing III. She mentors students as a member of the program’s Industry Advisory Board.
Rebecca Killick, Professor of Statistics
Stat 5: Statistics
Killick discussed different ways that statistics can be used to assess, monitor, and aid decision making in the environmental and climate sectors. She drew on examples from her own research and asked students to discuss in small groups other examples they could think of.
Ian Lane, Associate Professor of Computer Science and Engineering
NLP 280: Seminar in Natural Language Processing
Lane invited Assistant Professor of Applied Mathematics Ashesh Chattopadhyay to come to the UC Santa Cruz Silicon Valley Campus to give a talk about the work he has been doing on modeling climate systems. Specifically, AI-based autoregressive models of our coupled climate system. Chattopadhyay and his collaborators have been building models for climate modeling at the global scale, some of which is deployed on NVidia’s Earth 2 Simulator.
Dejan Milutinovic, Professor of Electrical and Computer and Engineering
ECE10: Fundamentals of Robot Kinematics and Dynamics
ECE243: System Identification
In ECE10: Fundamentals of Robot Kinematics and Dynamics, Milutinovic played videos about autonomous electric tractor solutions for organic farming, which included agriculture practices that address negative climate trends. The videos were from his previous Farm Robotics Challenges and a recent inspiring short video “Farm-ng: Where’s the AI” produced by The Tech Interactive museum in which there are segments showing our work and “Banana Slugs” logo (1:10). He also described the steps in deriving the robotic kinematics that navigates the wedding implants.
In ECE243 when covering stochastic processes, he pointed students to his paper on intrinsic immune system noise. The noise offers an explanation for variations in cell amounts, or viral loads, among infected individuals, something we saw in the recent covid pandemic. However, the goal of his lecture was to explain that the variance of the sum of two processes is the sum of their individual variances, even when the processes cancel each other in the mean value. The conclusion is that even when the mean value trend in global temperatures did not show an increase, a negative climate trend could be concluded from an increased variation of temperatures.
Katia Obraczka, Professor of Computer Science and Engineering
CSE 157: Internet of Things
Obraczka presented a couple of Internet of Things (IoT) solutions and systems that her team has been developing at i-NRG in collaboration with faculty colleagues across divisions and campuses that focus on climate resilience. She presented on EUREKA, an IoT for environmental monitoring focusing on wildfire prevention and Greener Greenhouse, a visible-light based IoT for energy efficient greenhouses and protected agriculture environments.
Alex Pang, Professor of Computer Science and Engineering
CSE 101: Introduction to Data Structures and Algorithms
Students will be working on visualizing shoreline data using dictionary abstract data type. This data can potentially be used for 3d reconstruction of intertidal bathymetry especially.
Ricardo Sanfelice, Professor of Electrical and Computer Engineering
ECE 246: Hybrid Dynamical Systems
Sanfelice discussed temperature control systems in his ECE 246 course: Hybrid Dynamical Systems. This course examines the modeling and analysis of hybrid dynamical systems, including the modeling of hybrid systems, the concept of solutions, Zeno behavior, equilibrium sets, stability, convergence, Lyapunov-based conditions, robustness, and simulation. Students are guided on methods for simulation and encouraged to apply them to several applications.
Ram Sundara Raman, Assistant Professor of Computer Science and Engineering
CSE156: Network Programming
Sundara Raman discussed sustainable networking—specifically the role that energy consumption plays in today’s networks, and discussed the carbon footprint caused by today’s large data centers. The class also discussed some of the tradeoffs in making networks more sustainable, specifically regarding balancing carbon footprint, energy cost, and network performance (in particular, latency). Most of this discussion was informed by this SIGCOMM 2012 research paper.
Sundara Raman also highlighted research that he is currently doing on sustainable security. One of his master’s students, Rohit Nagubandi, who is working with Sundara Ram and Professor Abel Souza, has been awarded a SeekCommons fellowship to work with the Tor Project on advancing sustainability in the popular Tor Network. Nagubandi is currently working on measuring the power consumption and carbon footprint of the Tor network, and hopes to help build more sustainable solutions by the end of his research project.
Julie Simons, Associate Professor of Teaching of Applied Mathematics
Stat5: Statistics
AM11A: Mathematical Methods for Economists I
Students learned about the field of environmental economics in AM 11A. In small groups, students worked through a worksheet focused on fisheries management and carbon caps, followed by an individual reflection activity and whole class discussion. This used concepts of linear approximation, derivatives, average versus instantaneous rates of change, models and their limitations, and marginal costs which are all key concepts in AM 11A, applied to the field of environmental economic policy.
Paul Vroomen, Adjunct Professor of Electrical and Computer Engineering
CRWN 100: Fundamentals of Starting and Scaling an Organization
Vroomen challenged students to create a startup company that can meaningfully address climate change. Vroomen illustrated the urgency of the issue and how it will directly impacts the quality of life of the students in his class. This is also the introduction to the class I created for ECE in conjunction with Carson College, ECE 80G: Creating and Financing a Sustainable Startup in the Global Economy.
Yu Zhang, Assistant Professor of Electrical and Computer Engineering
ECE 180J Advanced Renewable Energy Sources, Storage, and Smart Grids
Zhang encouraged students to engage with Climate Week events. He hosted a short in-class brainstorming session to help students connect their group project ideas with themes from the talks in Climate Week, such as AI-driven data centers and renewable-powered AgTech. The discussions were energizing and well-received.
His Ph.D. student Shourya Bose presented their project “Foundation AI Models for Catalyst Discovery” at the UC Climate Tech Showcase in San Francisco. Zhang is grateful for the support from the CITRIS I2P program (co-funded by Climate Action Solutions grant) and the Frontier Fellowship that made this work possible.
