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Author: callmespring

index.md

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 I was honoured to receive the [Institute of Mathematical Statistics (IMS) Tweedie Award](https://imstat.org/2024/03/05/chengchun-shi-receives-2024-ims-tweedie-new-researcher-award/) and the [Royal Statistical Society (RSS) Research Prize](https://rss.org.uk/news-publication/news-publications/2021/general-news/announcing-our-honours-recipients-for-2021/). 
 
-I am looking for PhD students interested in reinforcement learning; see my lecture [slides](https://github.com/callmespring/RL-short-course) on RL, our tutorial ([Youtube](https://www.youtube.com/watch?v=LwShOYaRFqM&list=PLA_E7IjY9cw4aC4T8pnV3vl9wSA1461KV), [Bilibili](https://www.bilibili.com/video/BV1ZS9NYpEHg/?spm_id_from=333.788.recommend_more_video.-1&vd_source=0ff25cf8645aa63231bec2428b94bf6f
+I am looking for PhD students interested in reinforcement learning and large language modelling (LLMs); see my lecture [slides](https://github.com/callmespring/RL-short-course) on RL, our tutorial ([Youtube](https://www.youtube.com/watch?v=LwShOYaRFqM&list=PLA_E7IjY9cw4aC4T8pnV3vl9wSA1461KV), [Bilibili](https://www.bilibili.com/video/BV1ZS9NYpEHg/?spm_id_from=333.788.recommend_more_video.-1&vd_source=0ff25cf8645aa63231bec2428b94bf6f
 )) on RL for two-sided marketplaces, my [slides](https://github.com/callmespring/RL-short-course/blob/main/Lecture%205/OPEslides.pdf) on off-policy evaluation and our review [paper](https://arxiv.org/pdf/2212.06355.pdf). 
 
 My email <c.shi7@lse.ac.uk>. My [GitHub](https://github.com/callmespring). 
 
 ### Research
 
-My research is motivated from the applications in precision medicine (a simulated [STARD](https://cran.r-project.org/web/packages/ITRSelect/index.html) data example), mobile health (some simulated environments for [Diabetes](https://github.com/RunzheStat/TestMDP) and [Intern Health](https://github.com/limengbinggz/cusum-rl)), ridesharing (simulated environments for [Order Dispatch](https://github.com/callmespring/MDPOD) and [Spatio-temporal Policy Evaluation](https://github.com/RunzheStat/CausalMARL); see also my [talk](https://www.bilibili.com/video/BV1yo4y1j7FU/?spm_id_from=333.337.search-card.all.click&vd_source=0ff25cf8645aa63231bec2428b94bf6f)), neuroscience and video-sharing platforms (see our KDD [paper](https://dl.acm.org/doi/pdf/10.1145/3580305.3599809) for details about our proposal successfully deployed in a widely used mobile app with millions of daily active users).
+My research is motivated from the applications in LLMs (see our recent [paper](https://arxiv.org/pdf/2504.03784) on fine-tuning) precision medicine (a simulated [STARD](https://cran.r-project.org/web/packages/ITRSelect/index.html) data example), mobile health (some simulated environments for [Diabetes](https://github.com/RunzheStat/TestMDP) and [Intern Health](https://github.com/limengbinggz/cusum-rl)), ridesharing (simulated environments for [Order Dispatch](https://github.com/callmespring/MDPOD) and [Spatio-temporal Policy Evaluation](https://github.com/RunzheStat/CausalMARL); see also my [talk](https://www.bilibili.com/video/BV1yo4y1j7FU/?spm_id_from=333.337.search-card.all.click&vd_source=0ff25cf8645aa63231bec2428b94bf6f)), neuroscience and video-sharing platforms (see our KDD [paper](https://dl.acm.org/doi/pdf/10.1145/3580305.3599809) for details about our proposal successfully deployed in a widely used mobile app with millions of daily active users).
 
 Some of my recent **talks** and **slides** on statistical inference, RL, causal inference, data integration, time series and experimental design: 
 * **StatRL** [Bilibili](https://www.bilibili.com/video/BV1ZP4y1r7DC/?spm_id_from=333.337.search-card.all.click&vd_source=0ff25cf8645aa63231bec2428b94bf6f), [Youtube](https://www.youtube.com/watch?v=-SW9PevZThs&t=982s); Chinese versions: [Bilibili](https://www.bilibili.com/video/BV1kP411f7dA/?spm_id_from=333.337.search-card.all.click), [Youtube](https://www.youtube.com/watch?v=7NWBLuok8nk&t=3048s); [slides](https://callmespring.github.io/slides/StatRL.pdf); the accompanying [paper](https://arxiv.org/abs/2502.16195)