Summary
Wilka Carvalho is a Research Fellow at Harvard with 11 years of experience applying machine learning and reinforcement learning to real-world and scientific problems. Her work spans top research labs including DeepMind, Microsoft, IBM, and USC, where she has driven advances in generalization of RL agents, medical-signal prediction, and domain-adaptive time-series models that led to publications and a patent. She has a strong experimental and engineering background—building simulators and data pipelines in C++ and TensorFlow and improving algorithmic performance from prototype to production-grade accuracy. Trained in physics (B.S.), computer science (M.S.), and currently a PhD candidate in machine learning, she blends rigorous quantitative thinking with hands-on systems implementation. Beyond research, she mentors underrepresented youth and has communicated technical work to both academic and executive audiences. Motivated by building human-empowering AI, she focuses on methods that generalize robustly to new situations and measurably improve downstream impact.
11 years of coding experience
4 years of employment as a software developer
Master of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at University of Southern California
Doctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at University of Michigan
Bachelor of Science (B.S.), Physics, Bachelor of Science (B.S.), Physics at Stony Brook University
Spanish