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xiaolong luo harvard ph d student homepage homepage about me news publications invited talks education technical skills teaching philosophy contact blog xiaolong luo ph d student in engineering science at harvard university cambridge massachusetts harvard university curriculum vitae email linkedin github wechat google scholar welcome to my homepage i am a ph d candidate in engineering science at harvard school of engineering and applied sciences fortunate to be advised by prof michael lingzhi li prior to that i obtained my bachelor s degree in statistics from the university of science and technology of china ustc where i had the privilege of being advised by prof yanran wang and the opportunity to work with prof atlas wang i was honored to receive the 41st guo moruo scholarship the highest honor for ustc undergraduates my research focuses on developing the foundations of next generation artificial intelligence techniques to enhance its effectiveness and practical applications in healthcare i am particularly interested in developing flexible diagnostic models with multi task and multi modal learning aiming to improve medical assessments through the integration of various types of medical data you can reach me via email at xiaolongluo g harvard edu i am actively seeking collaborations in healthcare related domains if you re interested in ai applications in healthcare medical imaging clinical data analysis or any related fields feel free to reach out note i am currently looking for summer 2026 internships if you know of any suitable positions i d love your recommendations also always happy to chat over coffee research interests flexible diagnostic models with multi task and multi modal learning i work on developing advanced ai models that can simultaneously handle multiple diagnostic tasks while effectively integrating various types of medical data imaging clinical notes lab results to provide more comprehensive and accurate medical assessments evaluating and enhancing llm reasoning in real world medical settings i work on developing evaluation frameworks and benchmarks to assess and improve how large language models reason over complex temporally extended medical data my goal is to enhance their fidelity calibration and robustness ultimately enabling trustworthy and generalizable clinical ai systems long term vision i aspire to become a compound talent who deeply understands large scale medical data multi modal learning and end to end clinical applications my long term goal is to bridge the gap between cutting edge ai research and real world healthcare impact driving both technical innovation and product commercialization ultimately i hope to promote a more equitable distribution of medical resources enabling better healthcare access and outcomes for all and bringing broader benefits to society news 2025 11 our paper the critical records integrated standardization pipeline crisp accepted by ml4h 2024 as spotlight will also hold a poster session at time series for health ts4h workshop see you in december in san diego 2025 11 great experience presenting towards interpretable sequential multiple instance learning an application to clinical imaging at amia 2025 in atlanta the conference was fantastic 2025 10 successfully passed my qualification exam and officially became a ph d candidate 2025 09 new paper on arxiv the critical records integrated standardization pipeline crisp check it out open to collaboration 2025 06 our paper accepted by amia 2025 see you in atlanta this november 2025 05 successfully completed all phd coursework and earned cs master s degree en route to phd publications authors with contributed equally journal articles ai transformers for radiation dose reduction in serial whole body pet scans yr wang l qu nd sheybani x luo j wang ke hawk aj theruvath et al radiology artificial intelligence if 22 5 apr 2023 link conference papers towards interpretable sequential multiple instance learning an application to clinical imaging xiaolong luo hsin hsiao scott wang michael lingzhi li american medical informatics association amia nov 2025 learning pruning friendly networks via frank wolfe one shot any sparsity and no retraining miao lu xiaolong luo tianlong chen wuyang chen dong liu zhangyang wang international conference on learning representations iclr spotlight presentation mar 2022 paper code working projects healthcare ai safety and reliability research working with the critical dataset on exciting healthcare applications also exploring llm reasoning traces and addressing a fundamental challenge when ai models are used in healthcare applications either through single llm calls or an agentic system there is a strong need to fully understand when and how ai models fail and how to fix those issues to prevent catastrophic consequences invited talks towards interpretable sequential multiple instance learning an application to clinical imaging informs annual meeting seattle 2024 professional service reviewer cvpr 2026 conference on computer vision and pattern recognition iclr 2026 international conference on learning representations neurips 2025 workshop imageomics imageomics workshop neurips 2025 workshop genai4health generative ai for health workshop ml4h 2025 machine learning for health symposium iclr 2025 international conference on learning representations education harvard university cambridge massachusetts 2022 present ph d in engineering science harvard university cambridge massachusetts 2022 2025 s m in computer science university of science and technology of china anhui china 2018 2022 bachelor of technology in statistics honors and awards academic awards the 41st guo moruo scholarship top 1 highest honor at ustc 2021 national scholarship top 1 from ministry of education of china 2019 outstanding student scholarship golden award top 5 2020 chinese mathematics competitions anhui the second prize 2019 leadership entrepreneurship co director harvard gsas entrepreneur club ai community 2022 2023 second prize h innopitch competition with futurex 2022 technical skills programming languages c python r html react javascript typescript frameworks pytorch tensorflow pyg tools mathematica latex git check out my github profile for code and projects teaching head teaching fellow am101 statistical inference for scientists and engineers spring 2024 instructor prof rob howe class size 55 students teaching fellow eng sci 139 innovation in science and engineering conference course fall 2025 instructor prof david ricketts class size 67 students jointly offered with graduate school of design as sci 6272 compsci 1090b data science 2 advanced topics in data science spring 2025 instructor prof pavlos protopapas seas natesh pillai statistics class size 277 students neuro 240 biological and artificial intelligence spring 2025 instructor prof gabriel kreiman class size 142 students course website cs 182 artificial intelligence fall 2023 instructors prof stephanie gil prof milind tambe harvard seas class size 138 students stat 139 introduction to linear models fall 2023 instructor prof james xenakis harvard gsas class size 83 students probability theory and mathematical statistics fall 2021 instructor prof canwen hong applied math ustc class size 97 students differential equation i fall 2020 instructor prof wuqing ning applied math ustc class size 156 students contact email xiaolongluo g harvard edu schedule meeting book a 30 min slot address harvard school of engineering and applied sciences cambridge ma usa last updated feb 2026