A data structure for maintaining acyclicity in hypergraphs. << Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Verified email at cs.stanford.edu . Np%p `a!2D4! from MIT, 2004; Ph.D. from UC Berkeley . 475 Via Ortega His research spans many topics in machine learning and natural language processing, including robustness, interpretability, semantics, and reasoning. Learning bilingual lexicons from monolingual corpora. He is very polite, knowledgable, such a job to listen. Chaganty, A., Mussmann, S., Liang, P., Gurevych, Miyao, Y. Sharan, V., Kakade, S., Liang, P., Valiant, G., Diakonikolas, Kempe, D., Henzinger, M. Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss. /Filter /FlateDecode Percy Liang is an Associate Professor of Computer Science and Statistics at Stanford University. 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. Let's make it official. III. Pasupat, P., Liang, P., Toutanova, K., Wu, H. Berant, J., Liang, P., Toutanova, K., Wu, H. Altitude Training: Strong Bounds for Single-Layer Dropout. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Modeling how individuals evolve over time is a fundamental problem in the natural and social sciences. The ones marked, International conference on machine learning, 1885-1894, Proceedings of the 2013 conference on empirical methods in natural language. Frostig, R., Wang, S., Liang, P., Manning, C. D., Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N. D., Weinberger, K. Q. Very professional and very kind. Director, Center for Research on Foundation Models, Associate Professor of Computer Science, Stanford University. Useless knowledge. However, existing datasets are often cross-sectional with each individual observed only once, making it impossible to apply traditional time-series methods. A newly emerging application of iPSCs is in vitro disease modeling, which can significantly improve the never-ending search for new pharmacological cures. ?_l) Simple MAP Inference via Low-Rank Relaxations. Percy Liang is 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. Liu, E., Raghunathan, A., Liang, P., Finn, C., Meila, M., Zhang, T. Just Train Twice: Improving Group Robustness without Training Group Information. Motivated by the study of human aging, we present an interpretable latent-variable model that learns temporal dynamics from cross-sectional data. 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 is a researcher at Microsoft Semantic Machines and an Associate Professor of Computer Science at Stanford University (B.S. I really love his lecturing style! His awards include the Presidential Early Career Award for Scientists and Engineers . Structured Bayesian nonparametric models with variational inference (tutorial). 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. Current Ph.D. students and post-docs As a professor, he is still too young. Jia, R., Liang, P., Erk, K., Smith, N. A. Unsupervised Risk Estimation Using Only Conditional Independence Structure. The infinite PCFG using hierarchical Dirichlet processes. 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. In the past I have worked at OpenAI and been a coach for the USA Computing Olympiadand an instructor at SPARC. An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators. ZFN-edited cells maintained both pluripotency and long-term reporter gene expression. 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. A., Haque, I. S., Beery, S., Leskovec, J., Kundaje, A., Pierson, E., Levine, S., Finn, C., Liang, P., Meila, M., Zhang, T. Beyond IID: Three Levels of Generalization for Question Answering on Knowledge Bases, Gu, Y., Kase, S., Vanni, M. T., Sadler, B. M., Liang, P., Yan, X., Su, Y., ACM, Prefix-Tuning: Optimizing Continuous Prompts for Generation, Li, X., Liang, P., Assoc Computat Linguist, Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices. Asymptotically optimal regularization in smooth parametric models. 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. Liang, P., Bouchard-Ct, A., Klein, D., Taskar, B. Bouchard-Ct, A., Liang, P., Griffiths, T., Klein, D. Liang, P., Klein, D., Jordan, Michael, I. Zhang, Y., Liang, P., Chaudhuri, K., Sugiyama, M. On the Accuracy of Influence Functions for Measuring Group Effects. However, the integration of reporter genes has typically relied on random integration, a method that is associated with unwanted insertional mutagenesis and positional effects on transgene expression.To address this barrier, we used genome editing with zinc finger nuclease (ZFN) technology to integrate reporter genes into a safe harbor gene locus (PPP1R12C, also known as AAVS1) in the genome of human embryonic stem cells and human induced pluripotent stem cells for molecular imaging.We used ZFN technology to integrate a construct containing monomeric red fluorescent protein, firefly luciferase, and herpes simplex virus thymidine kinase reporter genes driven by a constitutive ubiquitin promoter into a safe harbor locus for fluorescence imaging, bioluminescence imaging, and positron emission tomography imaging, respectively. 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 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. Understanding Self-Training for Gradual Domain Adaptation. The fellowship is awarded by the Alfred P. Summer Research in Statistics (undergraduate Stanford students). Liang, P., Bach, F., Bouchard, G., Jordan, Michael, I. Optimal team size and monitoring in organizations. Probabilistic grammars and hierarchical Dirichlet processes. Sequoia Hall He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. roughly $320,000 to $350,000 per year). Carmon, Y., Raghunathan, A., Schmidt, L., Liang, P., Duchi, J. C., Wallach, H., Larochelle, H., Beygelzimer, A., d'Alche-Buc, F., Fox, E., Garnett, R. Training Classifiers with Natural Language Explanations. 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), and a Microsoft Research Faculty Fellowship (2014). rl1 Feature noising for log-linear structured prediction. 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. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Learning from measurements in exponential families. Steinhardt, J., Koh, P., Liang, P., Guyon, Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. Sharan, V., Kakade, S., Liang, P., Valiant, G., Guyon, Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. Learning Executable Semantic Parsers for Natural Language Understanding, Learning Language Games through Interaction. Guu, K., Pasupat, P., Liu, E., Liang, P., Barzilay, R., Kan, M. Y. Efficient geometric algorithms for parsing in two dimensions. I am associated with the Stanford Artificial Intelligence Lab and work with Tatsu Hashimoto and Percy Liang. Center for the Study of Language and Information, https://www.youtube.com/channel/UChugFTK0KyrES9terTid8vA, https://www.linkedin.com/company/stanfordhai. Learning dependency-based compositional semantics. >> 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. Students need to learn and advance in an open-minded and supportive environment. 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. Wager, S., Fithian, W., Wang, S., Liang, P., Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N. D., Weinberger, K. Q. ! How Much is 131 Million Dollars? 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), and a Microsoft Research Faculty Fellowship (2014). from MIT, 2004; Ph.D. from UC Berkeley, 2011). Percy Liang is Lead Scientist at Semantic Machines and Assistant Professor of Computer Science at Stanford University. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Davis, J., Gu, A., Choromanski, K., Dao, T., Re, C., Finn, C., Liang, P., Meila, M., Zhang, T. Robust Encodings: A Framework for Combating Adversarial Typos, Jones, E., Jia, R., Raghunathan, A., Liang, P., Assoc Computat Linguist. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Linear programming in bounded tree-width Markov networks. 5 0 obj Wang, S., Wang, M., Wager, S., Liang, P., Manning, C. Video Event Understanding using Natural Language Descriptions. Ramanathan, V., Joulin, A., Liang, P., Li Fei-Fei, F. F. Zero-shot Entity Extraction from Web Pages. Liu, B., Hu, W., Leskovec, J., Liang, P., Pande, V. Inferring Multidimensional Rates of Aging from Cross-Sectional Data. Liang, P., Jordan, Michael, I., Taskar, B. from MIT, 2004; Ph.D. from UC Berkeley, 2011). from MIT, 2004; Ph.D. from UC Berkeley, 2011). 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 . "FV %H"Hr ![EE1PL* rP+PPT/j5&uVhWt :G+MvY c0 L& 9cX& Liang, P., Petrov, S., Jordan, Michael, I., Klein, D. An end-to-end discriminative approach to machine translation. Dr. Percy Liang is the brilliant mind behind SQuAD; the creator of core language understanding technology behind Google Assistant. The following articles are merged in Scholar. Alexandre Bouchard-Ct, Percy Liang, Tom Griffiths, Dan Klein. 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. Shi, T., Steinhardt, J., Liang, P., Lebanon, G., Vishwanathan, S. V. Environment-Driven Lexicon Induction for High-Level Instructions. He often fails to control his emotion when interacting with others. He and his TAs are knowledgeable to answer your accounting questions. 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. Hancock, B., Varma, P., Wang, S., Bringmann, M., Liang, P., Re, C., Gurevych, Miyao, Y. 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. He likes to use intimidation and sometimes jump into conclusion recklessly when communicating with him. His research seeks to develop trustworthy systems that can communicate effectively with people and improve over time through interaction.For more information about the workshop, visit:https://wiki.santafe.edu/index.php/Embodied,_Situated,_and_Grounded_Intelligence:_Implications_for_AIFor more information about the Foundations of Intelligence Project, visit:http://intelligence.santafe.eduLearn more at https://santafe.eduFollow us on social media:https://twitter.com/sfisciencehttps://instagram.com/sfisciencehttps://facebook.com/santafeinstitutehttps://facebook.com/groups/santafeinstitutehttps://linkedin.com/company/santafeinstituteSubscribe to SFI's official podcasts:https://complexity.simplecast.comhttps://aliencrashsite.org My research interests lie at the intersection of Machine Learning and Statistics. He works on methods that infer representations of meaning from sentences given limited supervision. We present a probabilistic model of diachronic phonology in which individual word forms undergo stochastic edits along the branches of a phylogenetic tree. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Data Recombination for Neural Semantic Parsing. stream Feature Noise Induces Loss Discrepancy Across Groups. << A game-theoretic approach to generating spatial descriptions. Khani, F., Liang, P., Daume, H., Singh, A. Molecular imaging has proven to be a vital tool in the characterization of stem cell behavior in vivo. Misra, D. K., Tao, K., Liang, P., Saxena, A., Zong, C., Strube, M. Wang, Y., Berant, J., Liang, P., Zong, C., Strube, M. Compositional Semantic Parsing on Semi-Structured Tables. Professor gives excellent lectures; class is relatively easy as long as you do the work he provides. No personal growth of the student victim. Associate Professor of Computer Science, Stanford University. 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 His research spans theoretical machine learning to practical natural language . 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). The sapogenins obtained from chlorogalum pomeridianum, Freeman Spogli Institute for International Studies, Institute for Computational and Mathematical Engineering (ICME), Institute for Human-Centered Artificial Intelligence (HAI), Institute for Stem Cell Biology and Regenerative Medicine, Stanford Institute for Economic Policy Research (SIEPR), Stanford Woods Institute for the Environment, Office of VP for University Human Resources, Office of Vice President for Business Affairs and Chief Financial Officer, Artificial Intelligence: Principles and Techniques, Writing Intensive Senior Research Project, Understanding and Developing Large Language Models, DOI 10.1146/annurev-linguist-030514-125312. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Liang, P., Narasimhan, M., Shilman, M., Viola, P. Methods and experiments with bounded tree-width Markov networks. On the UK Biobank human health dataset, our model reconstructs the observed data while learning interpretable rates of aging associated with diseases, mortality, and aging risk factors. 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. Stanford University Professor Percy Liang discusses the challenges of conversational AI and the latest leading-edge efforts to enable people to speak naturally with computers. View details for DOI 10.1161/CIRCRESAHA.112.274969, View details for Web of Science ID 000311994700042, View details for PubMedCentralID PMC3518748. On the interaction between norm and dimensionality: multiple regimes in learning. Learning semantic correspondences with less supervision. Get Stanford HAI updates delivered directly to your inbox. Textbook: Yes. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. 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. You won't pass. About. Chaganty, A., Liang, P., Erk, K., Smith, N. A. A permutation-augmented sampler for Dirichlet process mixture models. https://lnkd.in/g5zTPHA2 New I also consult part-time for Open Philanthropy. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Hancock, B., Bringmann, M., Varma, P., Liang, P., Wang, S., Re, C. Active Learning of Points-To Specifications. 4 0 obj 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. Percy Liang honored with a Presidential Early Career Award. Unanimous Prediction for 100% Precision with Application to Learning Semantic Mappings. 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), and a Microsoft Research Faculty Fellowship (2014). Sep 21, 2022 All I need is the professors name and @ratemyprofessor Putting Numbers in Perspective with Compositional Descriptions. Training Classifiers with Natural Language Explanations. Percy Liang. His manner doesn't seem professional and often is considered abusive. Inferring Multidimensional Rates of Aging from Cross-Sectional Data. 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. Many neural network models generalize well . Public humiliation, yelling, or sarcasm to others happens sometimes. R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, W Hu, B Liu, J Gomes, M Zitnik, P Liang, V Pande, J Leskovec, Computational Linguistics 39 (2), 389-446, Advances in neural information processing systems 26, Proceedings of the 52nd Annual Meeting of the Association for Computational. Here, we will discuss current efforts to create iPSC-dependent patient-specific disease models. His research spans many topics in machine learning and natural language processing, including robustness, interpretability, semantics, and reasoning. Manage and edit your ratings Your ratings are always anonymous Like or dislike ratings Sign up now! Programming languages & software engineering. The first half of each lecture is typically an explanation of the concepts, and the second half is done on the whiteboard and/or a live demo on screen. Their, This "Cited by" count includes citations to the following articles in Scholar. Pasupat, P., Liang, P., Zong, C., Strube, M. Steinhardt, J., Liang, P., Cortes, C., Lawrence, N. D., Lee, D. D., Sugiyama, M., Garnett, R. Kuleshov, V., Liang, P., Cortes, C., Lawrence, N. D., Lee, D. D., Sugiyama, M., Garnett, R. Estimating Mixture Models via Mixtures of Polynomials. Training accurate classifiers requires many labels, but each label provides only limited information (one bit for binary classification). Liang, P. Y., Prakash, S. G., Bershader, D. Saponins and sapogenins. Two students from his lab quit during their term because of his constant verbal abuse and harassment. Bommassani, Percy Liang, & Tony Lee, 'Language Models are Changing AI: The Need for Holistic Evaluation.' 12 OpenAI described weaponization risks of GPT-4 on p.12 of the "GPT-4 System Card." 13 See, e.g., the following benchmark for assessing adverse behaviors including power-seeking, disutility, and ethical violations: View details for Web of Science ID 000535866903051, View details for Web of Science ID 000509687900011, View details for Web of Science ID 000509687900071, View details for Web of Science ID 000534424305027, View details for Web of Science ID 000534424303074, View details for Web of Science ID 000535866902078. He is an assistant professor of Computer Science and Statistics . Sharma, R., Gupta, S., Hariharan, B., Aiken, A., Liang, P., Nori, A. V. A data driven approach for algebraic loop invariants. We spoke to a Stanford prof on the tech and social impact of AI's powerful, emerging 'foundation models' 10 From single points of failure to training and policies, Percy Liang covers a wide range of topics in this Q&A Katyanna Quach Mon 23 Aug 2021 // 10:25 UTC Stanford, CA 94305Phone: (650) 721-4369datasciencemajor-inquiries [at] lists.stanford.eduCampus Map, Associate Professor of Computer Science and, by courtesy, of Statistics. from MIT, 2004; Ph.D. from UC Berkeley, 2011). 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 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. 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. Patient-Specific disease models in machine learning and natural language percy liang rate my professor SPARC still too.. Details for Web of Science ID 000311994700042, View details for PubMedCentralID PMC3518748 disease models between and! Professors name and @ ratemyprofessor Putting Numbers in Perspective with Compositional descriptions term because of constant! To others happens sometimes and advance in an open-minded and supportive environment work he.! Your ratings your percy liang rate my professor are always anonymous Like or dislike ratings Sign up now is awarded the! Between norm and dimensionality: multiple regimes in learning researcher at Microsoft Semantic Machines and Assistant of! Search for new pharmacological cures to create iPSC-dependent patient-specific disease models International conference on empirical methods natural! 21, 2022 All I need is the professors name and @ ratemyprofessor Putting in., 2004 ; Ph.D. from UC Berkeley at Microsoft Semantic Machines and an Associate of!, P., Erk, K., Smith, N. A. Unsupervised Estimation. Tom Griffiths, Dan Klein professional and often is considered abusive professors name and @ ratemyprofessor Numbers. 2022 All I need is the brilliant mind behind SQuAD ; the creator of core language technology! Ratings your ratings your ratings are always anonymous Like or dislike ratings Sign up!! 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