Satvik Golechha
UK AISI
UK AISI
In the Summer 2024 cohort, Satvik worked on neural network modularity in the interpretability stream of Nandi Schoots. Satvik is an independent AI safety researcher interested in neural network interpretability, alignment/safety, unsupervised learning, and deep learning theory. In the past, he has worked on fundamental AI research at Microsoft Research and applied ML research for healthcare at Wadhwani AI. On the side, he enjoys writing fiction and poetry. For more, here's his website: https://7vik.io.
The Summer 2024 cohort marked a significant expansion, supporting approximately 90 scholars with 40 mentors—the broadest mentor selection in MATS history. This cohort incorporated MATS as a 501(c)(3) nonprofit organization, formalizing its institutional structure. The program expanded its research portfolio to include at least four governance mentors alongside technical research streams, reflecting growing interest in AI policy and technical governance work. The 10-week research phase continued in Berkeley, with scholars conducting work across mechanistic interpretability, evaluations, scalable oversight, and governance research.Notable outputs from this cohort include research on targeted manipulation and deception in LLMs trained on user feedback, which was accepted to NeurIPS workshops, and contributions to an AI safety via debate paper that won best paper at ICML 2024. One scholar co-founded Decode Research, a new AI safety organization focused on building interpretability tools.
Satvik Golechha
