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Murat Kocaoglu
@murat_kocaoglu_
Asst. Prof. at Johns Hopkins CS. Research on causal inference, causal discovery, generative AI, info theory, online learning.
Joined September 2017
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    I am pleased to announce that I will be joining Johns Hopkins University's Computer Science Department @JHUCompSci as an Assistant Professor in Fall 2025. I am grateful to my mentors for their unwavering support and to my exceptional PhD students for advancing our lab's vision.
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    I am so very excited to share that I have received the @NSF CAREER award on causal reasoning with information-theoretic methods! This would not have been possible without my mentors' guidance, and my collaborators' endless effort on our papers together. nsf.gov/awardsearch/sh…
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    If you are a grad student applying for Ph.D., here are some suggestions based on my reading of several applications in the last two years: 1. Do not be hyper-specific. Some students only write one faculty member's name because they interacted with them a priori.
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    Causal effect of X on Y cannot be identified when X, Y are confounded by a latent variable Z. From p(x, y), one can bound p(y|do(x)) thanks to Tian and Pearl (2000). But what if we know that the confounding is "weak"? #ICML2023
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    I will be looking for motivated Ph.D. students to work on fundamental problems in causal inference and machine learning @PurdueECE starting Fall'21. Please share with those who may be interested.
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    After two and a half great years at the MIT-IBM AI Lab, I will be starting as an assistant professor @PurdueECE in January to continue working on causal inference, machine learning and information theory.
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    If you are reviewing for ICML, please pay attention to the rebuttals of papers you gave low scores to and engage with the authors. It takes 5 min of your time to correct a misunderstanding that will save someone else's 1-year worth of work. #ICML2023
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    The day after submitting your rebuttals #NeurIPS2023
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    If you are a graduate student working in AI/ML and are anxious and overwhelmed by all the recent hype, get off Twitter. It's your advisor's job to filter out all the hype and keep you focused on what really matters.
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    Applying for a Ph.D. in ML/AI? Consider Purdue ECE! We have a dynamic and collaborative list of faculty working on different components of ML/AI who are looking for new students to start in the Fall. For info on my group, see muratkocaoglu.com
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    I will be teaching Artificial Intelligence @PurdueECE starting next week. Getting to (finally) study these books as part of your job is a privilege you will only be given in academia. #AcademicChatter
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    Senior Ph.D. student getting into NLP in 2024.
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    Excited to share the AAAI-22 Workshop on Information-Theoretic Methods for Causal Inference/Discovery. If you work on causal inference with ML applications and info theory connections, consider submitting your work. Deadline Nov. 12th. bit.ly/3tfA9r2 RTs appreciated!
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    This fall, I will be teaching Probabilistic Causal Inference @PurdueECE at the graduate level, covering both causal inference and causal discovery. Open to students from other departments as well. Comments about the course content are welcome! muratkocaoglu.com/ece695