
Vedang Lad
I'm a PhD student at Stanford University, fortunate to be working with Surya Ganguli and Christopher Potts. I'm particularly interested in uncovering the mechanisms and structures that give rise to intelligence and using that understanding to build smarter and safer AI systems.
I previously worked as a researcher at Metamorphic Labs and the Enigma Project at Stanford University with Andreas Tolias and Sophia Sanborn. I received my MEng in EECS from MIT, where I worked on mechanistic interpretability with Max Tegmark. Before that, I studied computer science and physics at MIT, where I worked on data-centric methods in ML. Outside of research, I competed in NCAA cross country and track and field at MIT. I currently run competitively for Peninsula Distance Club.
Papers
Letting the Neural Code Speak: Automated Characterization of Monkey Visual Neurons Through Human Language
Vedang Lad, Katrin Franke, Tamar Rott Shaham, Surya Ganguli, Andreas S. Tolias, Sophia Sanborn, Nikos Karantzas
The Remarkable Robustness of LLMs: Stages of Inference?
Vedang Lad, Jin Hwa Lee, Wes Gurnee, Max Tegmark
Exploring the Integration of AI into Physics Education: Leveraging ChatGPT for Problem Generation
Vedang Lad, Isaac Liao, Mohamed Abdelhafez, Peter Dourmashkin, Saif El-Adawy
Opening the AI Black Box: Distilling Machine-Learned Algorithms into Code
Eric J. Michaud, Isaac Liao, Vedang Lad, Ziming Liu, Anish Mudide, Chloe Loughridge, Zifan Carl Guo, Tara Rezaei Kheirkhah, Mateja Vukelić, Max Tegmark
Estimating label quality and errors in semantic segmentation data via any model
Vedang Lad, Jonas Mueller