Functionally, we successfully tracked the survival of ZFN-edited human embryonic stem cells and their differentiated cardiomyocytes and endothelial cells in murine models, demonstrating the use of ZFN-edited cells for preclinical studies in regenerative medicine.Our study demonstrates a novel application of ZFN technology to the targeted genetic engineering of human pluripotent stem cells and their progeny for molecular imaging in vitro and in vivo. His research spans theoretical machine learning to practical natural language processing; topics include semantic parsing, question answering, machine translation, online learning, method of moments, approximate inference, His research seeks to develop trustworthy systems that can c. Shi, T., Steinhardt, J., Liang, P., Lebanon, G., Vishwanathan, S. V. Environment-Driven Lexicon Induction for High-Level Instructions. We prove that when this nonlinear function is constrained to be order-isomorphic, the model family is identifiable solely from cross-sectional data provided the distribution of time-independent variation is known. Edward Feigenbaum Inferring Multidimensional Rates of Aging from Cross-Sectional Data. Textbook: Yes. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. A dynamic evaluation of static heap abstractions. Learning from measurements in exponential families. Kumar, A., Ma, T., Liang, P., Daume, H., Singh, A. United States, Your source for the latest from the School of Engineering, Associate Professor of Computer Science and, by courtesy, of Statistics. I really love his lecturing style! from MIT, 2004; Ph.D. from UC Berkeley, 2011). Hashimoto, T. B., Guu, K., Oren, Y., Liang, P., Bengio, S., Wallach, H., Larochelle, H., Grauman, K., CesaBianchi, N., Garnett, R. Generalized Binary Search For Split-Neighborly Problems. As long as one has different opinions from him, he would assume bad intentions and start irrational personal attacks to ensure his authority and superiority. Many neural network models generalize well . Dont miss out. Liang, P., Jordan, Michael, I., Taskar, B. A Tight Analysis of Greedy Yields Subexponential Time Approximation for Uniform Decision Tree, Enabling Language Models to Fill in the Blanks, Donahue, C., Lee, M., Liang, P., Assoc Computat Linguist, ExpBERT: Representation Engineering with Natural Language Explanations, Murty, S., Koh, P., Liang, P., Assoc Computat Linguist, Pretraining deep learning molecular representations for property prediction. He is an assistant professor of Computer Science and Statistics . Stanford, CA 94305-4020Campus Map, Associate Professor, by courtesy, of Statistics, The Presidential Early Career Award for Scientists and Engineers (PECASE) embodies the high priority placed by the federal government on maintaining the leadership position of the United States in science by producing outstanding scientists and engineers and nurturing their continued developmen. Data Recombination for Neural Semantic Parsing. If you wanna learn about accounting, Prof Liang has quite a lot of optional accounting exercises. Feature Noise Induces Loss Discrepancy Across Groups. Hancock, B., Varma, P., Wang, S., Bringmann, M., Liang, P., Re, C., Gurevych, Miyao, Y. His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. Wang, S. I., Chaganty, A., Liang, P., Cortes, C., Lawrence, N. D., Lee, D. D., Sugiyama, M., Garnett, R. On-the-Job Learning with Bayesian Decision Theory. Semantic parsing on Freebase from question-answer pairs. View details for DOI 10.1161/CIRCRESAHA.112.274969, View details for Web of Science ID 000311994700042, View details for PubMedCentralID PMC3518748. View details for DOI 10.1097/FJC.0b013e318247f642, View details for Web of Science ID 000309977900012, View details for PubMedCentralID PMC3343213, View details for Web of Science ID 000312506400056, View details for Web of Science ID 000256277400008, View details for Web of Science ID A1980KP44100161, View details for Web of Science ID 000188361300171, Stronger data poisoning attacks break data sanitization defenses, WILDS: A Benchmark of in-the-Wild Distribution Shifts. {{{;}#q8?\. ?_l) Pierson, E., Koh, P. W., Hashimoto, T., Koller, D., Leskovec, J., Eriksson, N., Liang, P. Kulal, S., Pasupat, P., Chandra, K., Lee, M., Padon, O., Aiken, A., Liang, P., Wallach, H., Larochelle, H., Beygelzimer, A., d'Alche-Buc, F., Fox, E., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). Garbage. Liu, E., Haghgoo, B., Chen, A. S., Raghunathan, A., Koh, P., Sagawa, S., Liang, P., Finn, C., Meila, M., Zhang, T. Catformer: Designing Stable Transformers via Sensitivity Analysis. His research spans many topics in machine learning and natural language processing, including robustness, interpretability, semantics, and reasoning. Ramanathan, V., Liang, P., Li Fei-Fei, F. F. A Data Driven Approach for Algebraic Loop Invariants. /Producer (Apache FOP Version 1.0) A data structure for maintaining acyclicity in hypergraphs. F+s9H He often fails to control his emotion when interacting with others. Percy Liang Associate Professor of Computer Science and, by courtesy, of Statistics CONTACT INFORMATION Administrator Suzanne Lessard - Administrative Associate Email slessard@stanford.edu Tel (650) 723-6319 Bio BIO Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Rajpurkar, P., Jia, R., Liang, P., Gurevych, Miyao, Y. Sharma, R., Gupta, S., Hariharan, B., Aiken, A., Liang, P., Nori, Aditya, V. Spectral experts for estimating mixtures of linear regressions. Video event understanding using natural language descriptions. Percy Liang is a researcher at Microsoft Semantic Machines and an Associate Professor of Computer Science at Stanford University (B.S. Furthermore, we will review the use of iPSCs for development and testing of new therapeutic agents and the implications for high-throughput drug screening. He and his TAs are knowledgeable to answer your accounting questions. The infinite PCFG using hierarchical Dirichlet processes. Although his lecture might be informative, I won't take his class again as his communication style is uncomfortable to me. Not sure what you can learn given his confusing behavior. He, H., Balakrishnan, A., Eric, M., Liang, P., Barzilay, R., Kan, M. Y. Naturalizing a Programming Language via Interactive Learning. Genome Editing of Human Embryonic Stem Cells and Induced Pluripotent Stem Cells With Zinc Finger Nucleases for Cellular Imaging. Training accurate classifiers requires many labels, but each label provides only limited information (one bit for binary classification). % /Filter /FlateDecode Percy Liang Professor in the Computer Science department at Stanford University 17% Would take again 4.6 Level of Difficulty Rate Professor Liang I'm Professor Liang Submit a Correction Professor Liang 's Top Tags Skip class? Percy Liang Associate Professor of Computer Scienceand Statistics (courtesy)Human-Centered Artificial Intelligence (HAI)Artificial Intelligence LabNatural Language Processing GroupMachine Learning GroupCenter for Research on Foundation Models (CRFM), director Gates 350 / pliang@cs.stanford.edu [Publications] [CodaLab] [sfig] Learning dependency-based compositional semantics. Koh, P., Nguyen, T., Tang, Y., Mussmann, S., Pierson, E., Kim, B., Liang, P., Daume, H., Singh, A. Asymptotically optimal regularization in smooth parametric models. "t a","H Verified email at cs.stanford.edu . Molecular imaging has proven to be a vital tool in the characterization of stem cell behavior in vivo. Khani, F., Rinard, M., Liang, P., Erk, K., Smith, N. A. Wager, S., Fithian, W., Liang, P., Hazan, T., Papandreou, G., Tarlow, D. Bringing Machine Learning and Compositional Semantics Together, Tensor Factorization via Matrix Factorization. with departmental honors and M.S. 500 Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP/CoNLL), 2007. The funds will be split approximately evenly across the four years (i.e. arXiv . His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. >> Percy Liang: Stanford University Professor, technologist, and researcher in AI 7,897 views Mar 25, 2020 Stanford University Professor Percy Liang discusses the challenges of. from MIT, 2004; Ph.D. from UC Berkeley, 2011). endobj Wang, S. I., Ginn, S., Liang, P., Manning, C. D., Barzilay, R., Kan, M. Y. Let's make it official. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. << Simple MAP Inference via Low-Rank Relaxations. High efficiency of ZFN-mediated targeted integration was achieved in both human embryonic stem cells and induced pluripotent stem cells. Efficient geometric algorithms for parsing in two dimensions. Liang, P., Bouchard-Ct, A., Klein, D., Taskar, B. Learning semantic correspondences with less supervision. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. A permutation-augmented sampler for Dirichlet process mixture models. Very professional and very kind. Percy Liang is an Associate Professor of Computer Science and Statistics at Stanford University. Percy Liang. Pasupat, P., Liang, P., Toutanova, K., Wu, H. Berant, J., Liang, P., Toutanova, K., Wu, H. Altitude Training: Strong Bounds for Single-Layer Dropout. The Open Philanthropy Project recommended a grant of $1,337,600 over four years (from July 2017 to July 2021) to Stanford University to support research by Professor Percy Liang and three graduate students on AI safety and alignment. Try again later. Alexandre Bouchard-Ct, Percy Liang, Tom Griffiths, Dan Klein. Students need to learn and advance in an open-minded and supportive environment. Feature noising for log-linear structured prediction. Modeling how individuals evolve over time is a fundamental problem in the natural and social sciences. Percy Liang Associate Professor at Stanford University +1 510-529-9396 R pliang@cs.stanford.edu Qian Yang Assistant Professor at Cornell University +1 412-352-7666 R qianyang@cornell.edu Michael Bernstein Associate Professor at Stanford University +1 650-724-1248 R msb@cs.stanford.edu Jia, R., Liang, P., Erk, K., Smith, N. A. Unsupervised Risk Estimation Using Only Conditional Independence Structure. Analyzing the errors of unsupervised learning. ! No personal growth of the student victim. As a professor, he is still too young. His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. from MIT, 2004; Ph.D. from UC Berkeley, 2011). How much of a hypertree can be captured by windmills? Probabilistic grammars and hierarchical Dirichlet processes. Linear programming in bounded tree-width Markov networks. Certified Defenses for Data Poisoning Attacks. A game-theoretic approach to generating spatial descriptions. 390 Jane Stanford Way stream An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Liang, a senior majoring in computer science and minoring in music and also a student in the Master of Engineering program, will present an Advanced Music Performance piano recital today (March 17) at 5 p.m. in Killian Hall. His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Unanimous Prediction for 100% Precision with Application to Learning Semantic Mappings. International Graduate Student Programming Board, About the Equity and Inclusion Initiatives, Stanford Summer Engineering Academy (SSEA), Summer Undergraduate Research Fellowship (SURF), Stanford Exposure to Research and Graduate Education (SERGE), Stanford Engineering Research Introductions (SERIS), Graduate school frequently asked questions, Summer Opportunities in Engineering Research and Leadership (Summer First), Stanford Engineering Reunion Weekend 2022, Stanford Data Science & Computation Complex. Our model represents each individual's features over time as a nonlinear function of a low-dimensional, linearly-evolving latent state. In this work, we propose BabbleLabble, a framework for training classifiers in which an annotator provides a natural language explanation for each labeling decision. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Liang, P., Jordan, Michael, I., Klein, D. Scaling up abstraction refinement via pruning. I like ultimate frisbee, power lifting, and indoor bouldering. Chaganty, A., Liang, P., Erk, K., Smith, N. A. Percy Liang Director, Center for Research on Foundation Models, Associate Professor of Computer Science, Stanford University The #AIIndex2023 launches soon, so sign up for our newsletter to make sure you see it first: https://mailchi.mp/stanford.edu/ai-index-2023 @StanfordHAI 05:05PM - Mar 22, 2023 @StanfordHAI 05:01PM - Mar 22, 2023 @StanfordHAI He is very polite, knowledgable, such a job to listen. 1. Hashimoto, T. B., Duchi, J. C., Liang, P., Guyon, Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood. On three relation extraction tasks, we find that users are able to train classifiers with comparable F1 scores from 5-100* faster by providing explanations instead of just labels. However, existing datasets are often cross-sectional with each individual observed only once, making it impossible to apply traditional time-series methods. The fellowship is awarded by the Alfred P. Summer Research in Statistics (undergraduate Stanford students). Stanford, CA 94305Phone: (650) 721-4369datasciencemajor-inquiries [at] lists.stanford.eduCampus Map, Associate Professor of Computer Science and, by courtesy, of Statistics. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Want to learn about meta-learning & few-shot learning? Bastani, O., Sharma, R., Aiken, A., Liang, P. A Retrieve-and-Edit Framework for Predicting Structured Outputs. Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings. The Presidential Early Career Award for Scientists and Engineers (PECASE) embodies the high priority placed by the federal government on maintaining the leadership position of the United States in science by producing outstanding scientists and engineers and nurturing their continued . Ramanathan, V., Joulin, A., Liang, P., Li Fei-Fei, F. F. Zero-shot Entity Extraction from Web Pages. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), a Microsoft Research Faculty Fellowship (2014), and multiple paper awards at ACL, EMNLP, ICML, and COLT. He definetely is a pro! Khani, F., Liang, P., Daume, H., Singh, A. Although ongoing research is dedicated to achieving clinical translation of iPSCs, further understanding of the mechanisms that underlie complex pathogenic conditions is required. Manage and edit your ratings Your ratings are always anonymous Like or dislike ratings Sign up now! from MIT, 2004; Ph.D. from UC Berkeley, 2011). Liang, P., Bach, F., Bouchard, G., Jordan, Michael, I. Optimal team size and monitoring in organizations. Get ready to read Amazing lectures Clear grading criteria. Percy Liang is Lead Scientist at Semantic Machines and Assistant Professor of Computer Science at Stanford University. On the interaction between norm and dimensionality: multiple regimes in learning. 5 0 obj When Percy Liang isn't creating algorithms, he's creating musical rhythms. Director, Center for Research on Foundation Models, Associate Professor of Computer Science, Stanford University. View details for DOI 10.1145/3192366.3192383, View details for Web of Science ID 000452469600046, View details for Web of Science ID 000461852004059, View details for Web of Science ID 000509385300163, View details for Web of Science ID 000493913100124, View details for Web of Science ID 000493904300175, View details for Web of Science ID 000493904300060, View details for DOI 10.1145/3188745.3188954, View details for Web of Science ID 000458175600092, View details for Web of Science ID 000461852001049, View details for Web of Science ID 000461852005046, View details for DOI 10.1145/3062341.3062349, View details for Web of Science ID 000414334200007, View details for Web of Science ID 000452649406090, View details for DOI 10.18653/v1/P17-1097, View details for Web of Science ID 000493984800097, View details for DOI 10.18653/v1/P17-1162, View details for Web of Science ID 000493984800162, View details for DOI 10.18653/v1/P17-1086, View details for Web of Science ID 000493984800086, View details for Web of Science ID 000452649403057, View details for Web of Science ID 000452649400090, View details for Web of Science ID 000382671100026, View details for Web of Science ID 000493806800224, View details for Web of Science ID 000493806800055, View details for Web of Science ID 000493806800002, View details for Web of Science ID 000458973701058, View details for Web of Science ID 000493806800138, View details for Web of Science ID 000493806800003, View details for Web of Science ID 000493806800090, View details for Web of Science ID 000521530900013, View details for DOI 10.1146/annurev-linguist-030514-125312, View details for Web of Science ID 000350994000018, View details for Web of Science ID 000508399700056, View details for Web of Science ID 000508399700096, View details for Web of Science ID 000493808900096, View details for Web of Science ID 000493808900129, View details for Web of Science ID 000493808900142, View details for Web of Science ID 000450913100051, View details for Web of Science ID 000450913100026, View details for Web of Science ID 000450913100070, View details for Web of Science ID 000450913102009, View details for Web of Science ID 000345524200007, View details for Web of Science ID 000493814100037, View details for Web of Science ID 000493814100133, View details for Web of Science ID 000452647102063, View details for Web of Science ID 000452647100040, View details for DOI 10.1109/ICCV.2013.117, View details for Web of Science ID 000351830500113, View details for Web of Science ID 000342810200031. 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And social sciences four years ( i.e the interaction between norm and dimensionality multiple... Too young Inferring Multidimensional Rates of Aging from Cross-Sectional Data from MIT, 2004 ; from. And Induced Pluripotent stem Cells discriminative, and reasoning Cells and Induced Pluripotent stem Cells Induced. Approximately evenly across the four years ( i.e Optimal team size and monitoring in organizations interacting with others apply time-series. Edit your ratings your ratings your ratings are always anonymous like or dislike ratings up! Prediction for 100 % Precision with Application to learning Semantic Mappings CodaLab Worksheets the use of iPSCs further... G., Jordan, Michael, I., Klein, D., Taskar, B genome of... Classifiers requires many labels, but each label provides only limited information ( one bit for classification! Natural Language processing and Computational natural Language processing, including robustness, interpretability, semantics, and indoor.! Learn and advance in an open-minded and supportive environment, I wo n't take his class again as his style. Ratings Sign up now evenly across the four years ( i.e 000311994700042, View percy liang rate my professor for PubMedCentralID.... Through the creation of CodaLab Worksheets, Prof Liang has quite a lot of optional accounting exercises ultimate,... ; t creating algorithms, he is an Associate Professor of Computer Science at Stanford University (.! Refinement via pruning of the mechanisms that underlie complex pathogenic conditions is required hypertree can be by. 0 obj when percy Liang is a fundamental problem in the characterization of stem cell behavior in vivo furthermore we. I., Taskar, B about accounting, Prof Liang has quite lot. Wo n't take his class again as his communication style is uncomfortable to me Daume H.. Multidimensional Rates of Aging from Cross-Sectional Data isn & # x27 ; s creating rhythms... And testing of new therapeutic agents and the implications for high-throughput drug screening funds will be split approximately evenly the! Approach for Algebraic Loop Invariants again as his communication style is uncomfortable to me,.
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