Caltech natural language processing

Caltech natural language processing

Predictive materials modeling can provide properties of real and virtual compounds and will be available on demand, thereby enabling rapid iteration time in materials design. However, the allure and necessity of accelerated discovery that motivates computational materials design is diminished by the prevalent heuristic approaches to materials synthesis and optimization.

caltech natural language processing

I will describe our work to extract information from peer reviewed academic literature across a range of inorganic solid state materials synthesis approaches. We have demonstrated not only the potential of the natural language processing NLP approach to assemble materials data from the literature, but we have also shown that one can develop hypotheses for what synthesis conditions drive a particular target material outcome using learning approaches.

Her research focuses on improving the environmental and economic sustainability of materials using methods informed by materials economics, machine learning, and techno-economic analysis.

She has received the NSF Career award for her experimental research focused on beneficial use of industrial waste materials. Olivetti received her B. Her Ph. Friday, February 28, Elsa A. OlivettiMassachusetts Institute of Technology.

Abstract: Predictive materials modeling can provide properties of real and virtual compounds and will be available on demand, thereby enabling rapid iteration time in materials design. For more information, please contact Elizabeth Rodriguez by phone at or by email at elizabeth caltech.

Event Series. Event Sponsors. Materials Science More Events from this Sponsor.Business, Economics, and Management. Frontiers in Social Sciences. Weekly seminar by a member of the Caltech Social Sciences faculty to discuss a topic of their current research or teaching at an introductory level. The course can be used to learn more about different areas of study and about undergraduate courses within the Social Sciences.

Natural Language Processing: Crash Course Computer Science #36

Instructor: Cvitanic. BEM Undergraduate Research. Units to be arranged; any term.

caltech natural language processing

Prerequisites: advanced BEM and instructor's permission. This course offers advanced undergraduates the opportunity to pursue research on a business problem individually or in a small group.

Selected Topics in Business Economics and Management. Units to be determined by arrangement with the instructor; offered by announcement. Topics determined by instructor. Instructors: Staff, visiting lecturers.

Introduction to Accounting. This course provides the knowledge and skills necessary for the student to understand financial statements and financial records and to make use of the information for management and investment decisions. Topics include: an overview of financial statements and business decisions; the balance sheet, the income statement, and the cash flow statement; sales revenue, receivables, and cash; cost of goods sold and inventory; long-lived assets and depreciation, and amortization; current and long-term liabilities; owners' equity; investments in other corporations and an introduction to financial statement analysis.

Instructor: Ewens. Introduction to Finance. Prerequisites: Ec 11 required; Ma 1 abc recommended to be familiar with calculus and linear algebra. Finance, or financial economics, covers two main areas: asset pricing and corporate finance. For asset pricing, a field that studies how investors value securities and make investment decisions, we will discuss topics like prices, risk, and return, portfolio choice, CAPM, market efficiency and bubbles, interest rates and bonds, and futures and options.

For corporate finance, a field that studies how firms make financing decisions, we will discuss topics like security issuance, capital structure, and firm investment decisions the net present value approach, and mergers and acquisitions.

In addition, if time permits, we will cover some topics in behavioral finance and household finance such as limits to arbitrage and investor behavior.

Instructor: Jin. Prerequisites: Ec 11, BEMsome familiarity with statistics. Examines the theory of financial decision making and statistical techniques useful in analyzing financial data.The new interface for Reaxys was made permanent on April 30, The old interface is no longer available.

Instructions on this site will be updated in the very near future. From the main new Reaxys start page, the default "Quick search" page displays a simple text search box that can be used in conjunction with a chemical structure or reaction drawing. The Quick search uses natural language processing to search all three core Reaxys databases: Documents literatureSubstances chemical entitiesand Reactions. The "Query builder" allows for the construction of a more advanced search using different fields, and one can specify what kind of results one is interested in - literature, chemical substances, or reaction schemes.

Boolean operators can be used in all fields for multi-word searches. The list of recognized Boolean operators are:. The list of citations in the result set are displayed by default in descending order of Publication Year, but can also be sorted by Journal Title, Author, and Document Type. You can view the articles which cite a selected article, but there is no way to sort by that criterion at present.

The left side displays fields by which to Filter the result set, including Document Type, Author, etc. Clicking on a field will display "by Group" by default, which gives you a summary of how many documents fall into various categories under that field - i. Authors will display the list of authors in the results set, and you can Limit to Include or Exclude certain authors to form a new results set.

Choosing "by Value" allows you to search within the results set for a term of your choosing in the selected field. From Reaxys: Select "Output". In the popup window, next to "Output", select "Citations Table". Next to "to", select Literature Management Systems e. ReferenceManager, EndNote etc. Next to Output Range, select the citation range desired. Next to "Output contains" check whether abstracts are to be included along with citation data.

Click "OK". Click "Download" and the. Select the file saved from Step 6 above. Click "Import". References should be imported into EndNote.Submit Your Note. At Google I am building algorithms that analyze text from the web and assign topics to it. This is useful in contextual advertising, when we are trying to show an ad relevant to the web content that a user is currently browsing and is interested in. Earlier I worked as a quantitative trader at a hedge fund, trading stocks and stock options.

I'm currently a postdoctoral fellow at UC Riverside and visiting fellow at UC Irvine studying active black holes and measuring their masses via an extensive monitoring campaign at the Lick Observatory. I am currently looking for jobs and will hopefully land a permanent position within the next couple years. My husband and I are residing in southern California with our two boys, Caspian and Altair.

January 01, By: Elizabeth Emerald.

caltech natural language processing

Category:,,,,,,,,,AveryBlackerDabneyFlemingRickettsLloydPageRuddockThroop. Class Notes. Select Class Year July 16, By: Elizabeth Emerald. Read More…. January 14, By: Elizabeth Emerald.

September 11, By: Elizabeth Emerald.The program aims to support cutting-edge research in the broad field of machine learning, including specific areas such as natural language processing, information retrieval, machine-translation and deep neural networks. The goal of dynamically interpretable models is to make predictions that are interpretable, rather than have the model itself be explicitly interpretable.

Yisong Yue CMS honors. TechFest A day-long event focused on providing startups and companies with a chance for meaningful interactions with undergraduate and graduate students, providing students with an opportunity to find out more about the breadth of applications for computing and mathematical sciences across industries.

Sincethis Fund has championed exceptional projects in their earliest stage of development — too early to attract industry or government support. We highlighted some of the adventurous research that has been explored by grants made possible by this initiative with you.

IST Meeting of the Minds A day-long research conference featuring talks, laboratory open houses, and poster presentations by distinguished faculty, graduate students, undergraduates, and researchers from JPL showcasing the latest and most exciting work that is underway in CMS.

Hacktech Caltech's premier interdisciplinary hackathon.

Professor Yue Receives Bloomberg Data Science Grant

CS 25th Anniversary Computer Science celebrated 25 years of innovative, ground-breaking research.We will schedule individual meetings between PM so you can discuss your workload with Dr. It will give a brief outline of studies using predictive analytics including detailed overview of methods such as Machine Learning and Deep Learning using AWS. Deep learning frameworks associated with image, text and natural language processing will be outlined. With recent collaboration with the national funding agencies, these cloud-related services will provide researchers access to cutting-edge technology in order to accelerate science.

Speaker Bio : Dr. Padhi has more than 15 years of experience in large-scale distributed computing, Data Analytics and Machine Learning. He is the co-creator Workload Management System, currently used for all the data processing and simulations activities by CMS, one of the largest experiments in the world at CERN, consisting of more than institutions across 40 countries. Sanjay obtained his Ph.

Contact: Heather Matson matsonh amazon. Subscribe to thisweek cms to receive weekly email announcements during the academic year only summarizing all seminars and events in the CMS department. Location: Beckman Institute Auditorium.Previous years Chen Graduate Fellows: - - Skip to main content. Tianqiao and Chrissy Chen Institute for Neuroscience. Home About.

Social and Decision Neuroscience. Sharon Chen Sharon's research interest is in the neurological basis of social behavior, emotion, learning, and decision-making, and its changes in psychiatric disorders.

IST Lunch Bunch

She has a background in machine learning and artificial intelligence, robotics, and natural language processing. Her past research experience includes developing neural network models of learning at the Parallel Distributed Processing Laboratory at Stanford University with Jay McClelland. Brenden Eum Brenden's research interests are in neuroeconomics, behavioral economics, decision theory, economics of information, and experimental economics.

He is particularly interested in models of perception and choice under limited attention and cognition. He received a Bacholer in Economics with a minor in Mathematics from New York University, completed a Masters in Economics at Columbia University, and has been working as an applied micro research assistant at Columbia Business School for the past two years.

Sabera Talukder Sabera seeks to understand how the brain relies on various electrical and chemical feedback signals to influence learning and memory. She was most recently at the Chan Zuckerberg Biohub where she established the neuroengineering research initiatives and conceived the Biohub's first Neuroengineering Symposium. Sabera graduated from Stanford with two Bachelors of Science with Honors in electrical engineering and biochemistry. Outside of research, Sabera also enjoys making systems to help people in third world countries.

For example, she created, built and deployed water purification systems in daycares for street children in Dhaka, Bangladesh. She has spent the past year as a research assistant in two different labs at Columbia. The Zucker lab research is focused on elucidating mechanisms used for signal transduction and information processing in sensory systems. Research in the Laboratory for Intelligent Imaging and Neural Computing, under Paul Sajda, uses principles of reverse engineering to characterize the cortical networks underlying perceptual and cognitive processes, such as rapid decision making, in the human brain.

Computational and Neural Systems. He was an undergraduate research associate in the lab of Dr. Shaowen Bao where the research goal is to understand sensory processing. For the past two years she has been an undergraduate researcher in the Systems Neural Engineering Lab where research centers on understanding how large populations of neurons in the brain perform computations and represent intention.

These insights are used to develop high-performance, robust, and practical assistive devices for people with disabilities and neurological disorders. She investigated the connections between scene statistics and neuronal codes at the individual level and at the population level.


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