<dfn id="w48us"></dfn><ul id="w48us"></ul>
  • <ul id="w48us"></ul>
  • <del id="w48us"></del>
    <ul id="w48us"></ul>
  • 外籍人才求職英文簡(jiǎn)歷

    時(shí)間:2024-10-25 12:10:48 英文簡(jiǎn)歷模板 我要投稿
    • 相關(guān)推薦

    外籍人才求職英文簡(jiǎn)歷模板

    Stanford University, Stanford, CA
    M.S. degree in Engineering Economic Systems and Operations Research in June 2000.
    Ph.D. degree in Management Science and Engineering June 2004.
    Dissertation title: "Multi-agent learning and coordination algorithms for distributed dynamic resource allocation."
    Dissertation advisor: Nicholas Bambos 

    外籍人才求職英文簡(jiǎn)歷模板

    Massachusetts Institute of Technology, Cambridge, MA
    B.S. degree in Mathematics in June 1997.
    M.S. degree in Systems Science and Control Engineering from the department of Electrical Engineering and Computer Science in June 1998. Master's thesis topic: Context-sensitive planning for autonomous vehicles operating in complex, uncertain, and nonstationary environments.

     

    EXPERIENCE
    Sun Microsystems Laboratories,  Menlo Park, CA
    April 2003 – Present:

    http://research.sun.com/people/vengerov/resume_vengerov.doc

    Conceiving, developing and implementing self-managing and self-optimizing capabilities in computer systems, covering domains such as: cache-aware thread scheduling and CPU power management, dynamic sharing of CPU/memory/bandwidth, dynamic data migration in distributed storage systems, dynamic job scheduling and job pricing in cloud computing, dynamic user migration in distributed virtual environments, etc.
    Principal investigator for the Adaptive Optimization project since 2006.
    Multiple patent applications filed, conference/journal papers published, multiple successful adaptive learning systems designed and implemented. The publicly available case studies are in the “technical reports” section of http://research.sun.com/people/vengerov/publications.html. 

    Intelligent Inference Systems Corp., Sunnyvale, CA Research Scientist
    April 2002 – April 2003: Started a new research initiative in applying the ACFRL algorithm and the previously developed multi-agent coordination algorithms to power control in wireless networks. Published several conference papers on this topic. Results demonstrate an improvement by more than a factor of 2 in comparison with the algorithms used in IS-95 and CDMA2000 standards.
    April 2002 – April 2003: Wrote a Phase I STTR proposal to the Office of Naval Research and received funding for the topic of “Perception-based co-evolutionary reinforcement learning for UAV sensor allocation.” Developed theoretical algorithms and designed a practical implementation strategy, which demonstrated excellent results in a high-fidelity robotic simulator. Published a conference paper.
    October 1998 – April 2002: Wrote a proposal to the NASA Program in Thinking Systems and received multi-year funding for the topic of cooperation and coordination in multi-agent systems. Developed, evaluated, and published new Reinforcement Learning algorithms for dynamic resource allocation among distributed agents operating jointly in complex, uncertain, and nonstationary environments.
    Fall 2000: Developed a new algorithm for single-agent learning in noisy dynamic environments with delayed rewards: Actor-Critic Fuzzy Reinforcement Learning (ACFRL). Published a conference and a journal paper with a convergence proof for ACFRL. US patent (number 6,917,925) was granted for the ACFRL algorithm on July 12, 2005.

    ChainCast Inc., San Jose, CA
    Aug 2000 – Oct 2000:  Conducted a survey of techniques for dynamic updating of multicasting trees and suggested a novel approach based on using multi-agent learning.

    NASA Ames Research Center, Moffet Field, CA Summer 1998:  Designed a framework for multiple agents operating in a complex, uncertain, and nonstationary environment. Agents learn to improve their policies using fuzzy reinforcement learning.

    SRI International, Artificial Intelligence Center, Menlo Park, CA
    Summer 1998: Developed a methodology for representing a replanning problem in the space of plans as a reinforcement learning problem.

    Bear, Stearns & Co., Inc. - Proprietory Trading Department, New York, NY
    Summer 1996, 1997:  Conducted a comprehensive study of time series forecasting models with neural networks. Recommended a hybrid model combining best features of the existing models and implemented it in C++.

    Summer 1995:  Developed a stock forecasting system based on conventional econometric techniques and implemented it in SAS language. Gained exposure to various proprietary trading models.

    Alphatech, Inc., Burlington, MA
    Feb 1997 - May 1997:  Developed an algorithm for optimal control of macroeconomic systems described by simultaneous-time equations and implemented it in MATLAB.

    Arthur Andersen, Inc., Boston, MA
    Feb 1996 - May 1996:  Developed an internal System Dynamics cashflow model of startup businesses. Gained experience in management level client interactions and in project presentation skills.

    Summer 1996:  Independently designed a game theoretic bid forecasting system in procurement auctions for a large construction company. The project involved extensive on-site client interactions during model development as well as a final presentation to the top level management.

    Property & Portfolio Research, Inc., Boston, MA
    Feb 1994 - May 1995:  Designed a mortgage portfolio analysis model and implemented it in Visual Basic for Excel. Developed a methodology for grouping real estate time series using cluster and factor analyses in SPSS. Designed an optimal investment strategy for a class of mortgage backed securities based on the efficient frontier characteristics. Gained broad exposure to real estate markets and models.

    Donaldson, Lufkin & Jenrette, Inc. -- Pershing Division, Jersey City, NJ
    Summer 1994:  Developed a stock forecasting system based on technical analysis and economic indicators. Developed a DJIA trading strategy based on S&P 500 futures and demonstrated its profitability.

    MIT Laboratory for Information and Decision Systems, Cambridge, MA
    Aug 1993 - May 1994:  Developed a trading strategy for US Treasury bonds based on multi-resolution wavelet analysis. Demonstrated its profitability as compared to the conventional moving average models.

     

    PROGRAMMING
    C++, Java, MATLAB; Various packages for statistics, neural networks and system dynamics.  
    PUBLICATIONS
    Published 13 papers in refereed conferences, 8 journal papers, 1 book chapter. The complete list, including technical reports, is available at http://research.sun.com/people/vengerov/publications.html.  

    PATENTS
    Four patents granted, 10 patent applications are currently under review at the US Patent Bureau.


    PERSONAL
    United States Citizen. Fluent in Russian and English. Black belt and instructor in Tae Kwon Do.
     

    【外籍人才求職英文簡(jiǎn)歷】相關(guān)文章:

    外籍老師英文簡(jiǎn)歷范文01-05

    文秘人才個(gè)人英文簡(jiǎn)歷范文01-01

    優(yōu)秀人才英文簡(jiǎn)歷模板表格03-02

    物流人才個(gè)人英文簡(jiǎn)歷范文02-27

    翻譯人才求職簡(jiǎn)歷03-28

    電子商務(wù)人才個(gè)人英文簡(jiǎn)歷模板02-28

    求職英文簡(jiǎn)歷模板03-29

    英文簡(jiǎn)歷的求職目標(biāo)01-12

    平面設(shè)計(jì)人才個(gè)人英文簡(jiǎn)歷范文01-01

    2017求職英文簡(jiǎn)歷模板02-21

    主站蜘蛛池模板: 欧美韩国精品另类综合| 日韩欧美精品不卡| 亚洲精品电影网| 亚洲日韩精品一区二区三区| 国产精品电影在线| 国产精品三级在线| 久久久久99精品成人片直播| 久久久久九国产精品| 亚洲国产精品成| 99精品国产一区二区三区| 人妻少妇精品视频一区二区三区| 久久性精品| 国产精品JIZZ在线观看老狼| 97久久久精品综合88久久| 亚洲精品视频免费观看| 久久伊人精品青青草原日本| 国产福利电影一区二区三区,亚洲国模精品一区| 国产精品免费看久久久| 亚洲精品成人片在线观看精品字幕| 久久se这里只有精品| 国产精品美女久久久久AV福利 | 国产精品白丝jkav网站| 国产91精品在线观看| 久久精品aⅴ无码中文字字幕重口| 亚洲人午夜射精精品日韩| 日本精品一区二区三区在线视频| 国内精品伊人久久久久网站| 国产高清在线精品一本大道| 2021年精品国产福利在线| 久久亚洲欧美日本精品| 久久亚洲精品中文字幕三区| 欧美久久精品一级c片片| 欧美精品在线一区二区三区| 亚洲嫩草影院久久精品| 99久久精品费精品国产 | 青娱乐国产精品视频| 麻豆精品| 亚洲无码日韩精品第一页| 亚洲国产另类久久久精品| 亚洲热线99精品视频| 久久精品亚洲日本波多野结衣|