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- https://davidishere.com/
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링크 · 24개 결과
페이지에서 식별된 외부 링크
링크 | 텍스트 |
---|---|
https://github.com/dzchen314/ | Github |
https://moneybball.blogspot.com/ | predict NBA player performance |
https://aclanthology.org/2022.coling-1.586.pdf | COLING |
https://aclanthology.org/2021.eval4nlp-1.19.pdf | EMNLP |
https://phy.duke.edu/ | Physics Department |
http://www.duke.edu/ | Duke |
http://jrgreer.caltech.edu/ | Materials Science |
http://www.craftypuzzles.com/ | wooden puzzles |
https://youtu.be/Hm4cdKB74iY?t=13m47s | memory of the past |
http://ready-player2.com/ | recommend games to groups |
JavaScript 변수 · 8개 결과
페이지의 창 개체에 로드된 전역 JavaScript 변수는 함수 외부에서 선언된 변수로, 현재 범위 내에서 코드의 어느 부분에서나 액세스할 수 있습니다
이름 | 유형 |
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onbeforetoggle | object |
documentPictureInPicture | object |
onscrollend | object |
$ | function |
jQuery | function |
skel | object |
onorientationchange | function |
jQuery111305288897787158022 | object |
콘솔 로그 메시지 · 1개 결과
웹 콘솔에 기록된 메시지
유형 | 카테고리 | 로그 |
---|---|---|
error | network |
|
HTML
페이지의 원시 HTML 본문
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<h2><strong>David Ken</strong></h2>
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<p align="justify">I am currently a Data Scientist at Capital One, where I am a technical lead focused on training and deploying LLMs for customer call understanding. Recently, I have led publications in <a href="https://aclanthology.org/2022.coling-1.586.pdf">COLING</a> and <a href="https://aclanthology.org/2021.eval4nlp-1.19.pdf">EMNLP</a>. Previously, I've worked as a Lead Data Scientist at Wells Fargo and a Data Science Fellow at Insight Data Science. Prior to working as a Data Scientist in industry, I was a Lab Manager and Postdoctoral Associate in the <a href="https://phy.duke.edu/">Physics Department</a> at <a href="http://www.duke.edu/">Duke</a>. I received a PhD from Caltech in <a href="http://jrgreer.caltech.edu/">Materials Science</a>, where I studied glassy materials and their mechanics. I love complex networks: from <a href="http://www.craftypuzzles.com/">wooden puzzles</a> and grains of sand, to glasses and neural networks. What these diverse subjects have in common is their ability to remember. Piles of sand, just like our brains and neural networks can have a <a href="https://youtu.be/Hm4cdKB74iY?t=13m47s">memory of the past</a> through their complex fabric of contacts!</p>
<p align="justify">I believe that these networks will transform how we understand the world. Outside of research, I use machine learning to make models that try to: <a href="http://ready-player2.com/">recommend games to groups</a>, <a href="https://moneybball.blogspot.com/">predict NBA player performance</a>, and <a href="http://potion.us-east-2.elasticbeanstalk.com/">learn what perfumes smell like</a>. In my free time, I am an avid baller - currently repping a pair of the Westbrook Why Not?'s. I also enjoy taking pictures and traveling (outside of basketball).</p>
<p align="justify">P.S. If you're wondering why my name appears as "Chen" and "Ken" in various places, it is because I recently got married and my wife and I decided to combine our names into a new one!</p>
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<h3 align="justify">Online fragrance recommendation engine based on a distributed memory model</h3>
<p align="justify">NLP model is trained using "paragraph vectors" (see: <a href="https://cs.stanford.edu/~quocle/paragraph_vector.pdf">https://cs.stanford.edu/~quocle/paragraph_vector.pdf</a>) denoting perfumes/colognes, along with a word corpus consisting of over 140k user reviews scraped from basenotes.com (pulled on 4/18). Model was implemented in gensim. The code and a tutorial/background is here: <a href="https://github.com/dzchen314/deep-perfumes-potion-app">https://github.com/dzchen314/deep-perfumes-potion-app</a>. Try it out at <a href="http://potion.us-east-2.elasticbeanstalk.com/">potionfinder.com</a>!</p>
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<h3 align="justify">Online game recommendation engine based on implicit feedback and bayesian personalized ranking</h3>
<p align="justify">Matrix factorization model is trained on Steam user data of over 100 Million users, utilizing game-ownership data as implicit feedback. The loss function is optimized using a <a href="https://arxiv.org/pdf/1205.2618.pdf">bayesian personalized ranking</a>, which achieves an AUC of 98% on a dataset that is >99.6% sparse. Try it out at <a href="http://ready-player2.com/">ready-player2.com</a> and use your Steam ID. Or try it with mine: snowmen314</p>
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<h3 align="left">3D imaging the shear jamming process in hydrogel spheres</h3>
<p align="justify">3D laser optical fluorescence tomography. 3D contact networks, e.g. fabric tensors. Image processing and contact mechanics for statistical contact force analysis.</p>
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<h3 align="left">Rheology and rate-stiffening of suspensions and granular composites</h3>
<p align="justify">Discontinuous shear thickening of cornstarch and water. Novel granular composites with discontiuous rate-stiffening properties.</p>
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<h3 align="left">Force chains in granular materials</h3>
<p align="justify">Rheology of grains around an intruder. Dynamics of grains during shear/impact. Statistical nature of granular force networks and contact fabrics. Machine learning approach to particle contact detection.</p>
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<h3 align="left">Fundamental deformation mechanisms in glasses</h3>
<p align="justify">Size effect of ductility in metallic glasses. Mechanisms for plasticity in nano-metallic glasses. Molecular dynamics simulations of deformation.</p>
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<h3 align="left">Fabrication and testing of nanostructures</h3>
<p align="justify">Electroplating and sputtering of nanoscale/hierarchical structures and laminates for tensile/compressive mechanical testing at room and cryogenic temperatures.</p>
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<h3 align="left">Atomic structure of glasses</h3>
<p align="justify">In-situ tomography and diffraction of atomic neighborhoods in metallic glasses under hydrostatic pressure. Molecular dynamics simulations of structure and fractal properties in glasses.</p>
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<a href="https://www.sciencemag.org/content/349/6254/1306.full" class="image featured"><img src="images/tomo+MD_science.png" alt=""></a>
<h5 align="left"><a href="https://www.sciencemag.org/content/349/6254/1306.full">Fractal atomic-level percolation in metallic glasses</a></h5>
<p align="justify"><strong>D.Z. Chen</strong>, C.Y. Shi, Q. An, Q.S. Zhang, W.L. Mao, W.A. Goddard III, J.R. Greer, <em>Science</em> 349 (6254), 1306-1310 (2015)</p>
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<a href="http://pubs.acs.org/doi/abs/10.1021/acs.nanolett.5b01034" class="image featured"><img src="images/nl-2015-SWL.gif" alt=""></a>
<h5 align="left"><a href="http://pubs.acs.org/doi/abs/10.1021/acs.nanolett.5b01034">Size Effect Suppresses Brittle Failure in Hollow Cu<sub>60</sub>Zr<sub>40</sub> Metallic Glass Nanolattices Deformed at Cryogenic Temperatures</a></h5>
<p align="justify">S.W. Lee, J.Z. Mehdi, <strong>D.Z. Chen</strong>, Y.W. Zhang, J.R. Greer, <em>Nano Letters</em> 15 (9), 5673–5681 (2015)</p>
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<a href="http://pubs.acs.org/doi/abs/10.1021/acsnano.5b00468" class="image featured"><img src="images/nl-2015-betar.gif" alt=""></a>
<h5 align="left"><a href="http://pubs.acs.org/doi/abs/10.1021/acsnano.5b00468"> Tailoring of Interfacial Mechanical Shear Strength by Surface Chemical Modification of Silicon Microwires Embedded in Nafion Membranes</a></h5>
<p align="justify">B.M. Gallant, X.W. Gu, <strong>D.Z. Chen</strong>, J.R. Greer, and N.S. Lewis, <em>ACS Nano</em>, 9 (5), 5143-5153 (2015)</p>
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<a href="http://scitation.aip.org/content/aip/journal/apl/106/6/10.1063/1.4907773" class="image featured"><img src="images/APL-2015-Chen.gif" alt=""></a>
<h5 align="left"><a href="http://scitation.aip.org/content/aip/journal/apl/106/6/10.1063/1.4907773">Ductility and work hardening in nano-sized metallic glasses</a></h5>
<p align="justify"><strong>D.Z. Chen</strong>, X.W. Gu, Q.An, W.A. Goddard III, and J.R. Greer, <em>Applied Physics Letters</em> 106, 061903 (2015)</p>
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<a href="http://pubs.acs.org/doi/abs/10.1021/nl5027869" class="image featured"><img src="images/nl-2014-wendygu.gif" alt=""></a>
<h5 align="left"><a href="http://pubs.acs.org/doi/abs/10.1021/nl5027869">Mechanisms of Failure in Nanoscale Metallic Glass</a></h5>
<p align="justify">X.W. Gu, M. Jafary-Zadeh, <strong>D.Z. Chen</strong>, Z. Wu,Y.-W. Zhang, D.J. Srolovitz, and J.R. Greer, <em>Nano Letters</em> 14 (10), 5858–5864 (2014)</p>
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<a href="http://pubs.acs.org/doi/abs/10.1021/nl402384r" class="image featured"><img src="images/nl-2013-chen.gif" alt=""></a>
<h5 align="left"><a href="http://pubs.acs.org/doi/abs/10.1021/nl402384r">Nano-Metallic Glasses: Size Reduction Brings Ductility, Surface State Drives its Extent</a></h5>
<p align="justify"><strong>D.Z. Chen</strong>, D. Jang, K.M. Guan, Q. An, W.A. Goddard, III, J.R. Greer, <em>Nano Letters</em> 13 (9), 4462-4468 (2013)</p>
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