雷吉娜-巴齐莱 计算机科学家

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Regina Barzilay
Computer Scientist | Class of 2017
Developing machine learning methods that enable computers to process and analyze vast amounts of human language data.


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Title
Computer Scientist
Affiliation
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology
Location
Cambridge, Massachusetts
Age
46 at time of award
Area of Focus
Computer Science and Electrical Engineering, Linguistics
Website
MIT: Regina Barzilay
Published October 11, 2017
ABOUT REGINA'S WORK
Regina Barzilay is a computational linguist developing machine learning methods that enable computers to interpret unstructured document content and perform real-world tasks with the promise for significant societal impact.

Barzilay has made significant contributions to a wide range of problems in computational linguistics, including both interpretation and generation of human language. Much of her work is focused on designing machine learning models that do not require large amounts of annotations for training since such resources are not available for most languages and tasks. In the multilingual context, Barzilay created algorithms that leverage annotations from high-resource languages (i.e., such as English) to analyze languages that lack such annotations; this includes the vast majority of world languages. For example, she and a student deciphered the ancient semitic language Ugaritic by mapping cognates and related morphological structures onto the related Hebrew language. This work not only democratizes natural language processing (NLP) by extending its potential benefits to a wider range of languages, it also yields insights for theories of language universals. Jointly with her students, Barzilay also pioneered the development of reinforcement learning methods for language grounding—that is, mapping language to entities and actions in the world. Through a feedback loop, the program learns in an unsupervised, coordinated way, allowing it to interact with the environment based on its understanding, continuously refine its semantic model, and turn the instructions into executable actions. This technique has been demonstrated to work with a high degree of accuracy in tasks such as configuring computer software using text manuals and in improving computer performance in the strategy game Civilization.

Currently, Barzilay is focused on bringing the power of machine learning to oncology. In collaboration with physicians and her students, she is devising deep learning models that utilize imaging, free text, and structured data to identify trends that affect early diagnosis, treatment, and disease prevention. Barzilay is poised to play a leading role in creating new models that advance the capacity of computers to harness the power of human language data.

BIOGRAPHY
Regina Barzilay received B.A. (1993) and M.S. (1998) degrees from Ben-Gurion University of the Negev and a Ph.D. (2003) from Columbia University. She has been affiliated with the Massachusetts Institute of Technology since 2003 and is currently Delta Electronics Professor of Electrical Engineering and Computer Science. Her scientific papers have appeared in such journals as Computational Linguistics, Transactions of the Association for Computational Linguistics, and Journal of Artificial Intelligence Research and in conference proceedings of the Association for Computational Linguistics (ACL) and Empirical Methods for Natural Language Processing (EMNLP).



雷吉娜-巴齐莱
计算机科学家 | 2017级
开发机器学习方法，使计算机能够处理和分析大量的人类语言数据。


雷吉娜-巴齐莱的肖像
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标题
计算机科学家
工作单位
麻省理工学院电子工程和计算机科学系
工作地点
马萨诸塞州剑桥市
年龄
获奖时46岁
重点领域
计算机科学和电气工程，语言学
网站
麻省理工学院。Regina Barzilay
发表于2017年10月11日
关于Regina的工作
Regina Barzilay是一名计算语言学家，他开发的机器学习方法使计算机能够解释非结构化的文件内容并执行现实世界的任务，并有望产生重大的社会影响。

巴齐莱对计算语言学的广泛问题做出了重大贡献，包括人类语言的解释和生成。她的大部分工作集中在设计机器学习模型，这些模型不需要大量的注释进行训练，因为大多数语言和任务都没有这种资源。在多语言背景下，Barzilay创造了一些算法，利用高资源语言（即，如英语）的注释来分析缺乏这种注释的语言；这包括世界上绝大多数的语言。例如，她和一个学生通过将同源词和相关的形态结构映射到相关的希伯来语上，破译了古老的符号语言Ugaritic。这项工作不仅使自然语言处理（NLP）民主化，将其潜在的好处扩展到更多的语言，而且还为语言普遍性理论带来了启示。巴齐莱与她的学生一起，还率先开发了语言基础的强化学习方法，即把语言映射到世界上的实体和行动。通过反馈回路，程序以一种无监督的、协调的方式进行学习，使其能够根据自己的理解与环境互动，不断完善其语义模型，并将指令变成可执行的行动。这种技术已被证明在使用文本手册配置计算机软件和提高计算机在战略游戏《文明》中的性能等任务中具有高度的准确性。

目前，巴齐莱正专注于将机器学习的力量引入肿瘤学。在与医生和学生的合作中，她正在设计深度学习模型，利用成像、自由文本和结构化数据来识别影响早期诊断、治疗和疾病预防的趋势。巴齐莱准备在创建新模型方面发挥领导作用，以推进计算机利用人类语言数据的能力。

个人简历
Regina Barzilay在内盖夫本古里安大学获得学士（1993年）和硕士（1998年）学位，并在哥伦比亚大学获得博士学位（2003年）。自2003年以来，她一直隶属于麻省理工学院，目前是电气工程和计算机科学的三角洲电子学教授。她的科学论文发表在《计算语言学》、《计算语言学协会论文集》和《人工智能研究杂志》等杂志上，并发表在计算语言学协会（ACL）和自然语言处理经验方法（EMNLP）的会议记录中。