-
-
Notifications
You must be signed in to change notification settings - Fork 0
/
index.html
542 lines (477 loc) · 19.7 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
<!DOCTYPE html>
<html lang="en" dir="ltr">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
<meta http-equiv="Last-Modified" content="Sun, 24 Dec 2017 15:53:00 GMT">
<meta name="generator" content="jsonresume-theme-relaxed v0.1.9">
<meta name="author" content="Wei Li">
<meta property="og:site_name" content="Wei Li">
<meta name="twitter:card" content="summary">
<meta name="version" content="v1.0.0">
<link rel="alternate" type="application/json" title="resume.json"
href="https://raw.githubusercontent.com/jsonresume/resume-schema/master/resume.json">
<link rel="stylesheet" type="text/css" href="https://use.typekit.net/wav6afv.css">
<style>
:root {
font-size: 10pt
}
:root {
font-family: "Lato", sans-serif;
text-rendering: geometricPrecision
}
@media not print {
@page {
margin: 2ex
}
section {
break-inside: avoid-page
}
}
@media print {
@page {
margin: 2.5cm
}
}
body {
padding: 0
}
@media only screen and (min-width:297mm) {
body {
height: 210mm;
width: 297mm;
margin: auto
}
}
main {
margin: 0 1ex
}
header {
height: 8em;
margin: 1ex 1.5ex -1ex
}
article:not(.flex)>h3 {
margin-block-end: .75em
}
h1 {
font-size: 2em;
font-weight: 600;
margin: .5em 0
}
h2 {
font-size: 1.5em;
font-weight: 400;
margin: .5em 0
}
h3 {
font-size: 1.25em;
font-weight: 600
}
h3::before {
content: " ";
height: 0;
width: calc(100% + 2ex);
display: block;
position: relative;
padding-block-start: 1em;
border-block-start: .2ex solid #789;
left: -1ex;
right: -1ex
}
strong {
font-size: 1.1em;
font-weight: 600
}
b {
font-weight: 600
}
small {
font-size: .9em
}
em {
font-style: normal;
text-decoration: underline #000 solid .15ex;
text-underline-position: under
}
address {
font-style: inherit
}
a,
a:hover {
color: inherit;
outline: none;
text-decoration: underline #0ff solid .15ex;
text-underline-position: under
}
mark {
color: #fff;
background-color: #008b8b;
border-radius: .2em;
display: inline-block;
padding: .15em .25em;
margin: 0 0 .2em .2em;
print-color-adjust: exact
}
ul {
padding-inline-start: 2em;
list-style-type: disclosure-closed
}
progress {
height: .5em;
border: 0;
width: 95%;
background-color: #808080;
display: inline-block;
border-radius: .25em;
margin: .25em 0;
print-color-adjust: exact
}
progress::-moz-progress-bar {
border-radius: .25em;
background-color: #008000;
print-color-adjust: exact
}
progress::-webkit-progress-value {
border-radius: .25em;
background-color: #008000;
print-color-adjust: exact
}
progress::-webkit-progress-bar {
border-radius: .25em
}
time+ :is(time, span)::before {
content: "–";
padding: 0 .25em
}
.flex {
display: flex;
flex-wrap: wrap;
justify-content: space-evenly;
gap: 0 .75em
}
.flex>h3 {
flex-basis: 100%
}
.flex>section {
flex: 1
}
.details> :first-child {
margin-block-end: 1em
}
.details:not(:first-of-type) {
padding-block-start: 1em
}
.details:not(:last-of-type) {
padding-block-end: 1em;
border-block-end: .15ex dashed #2f4f4f
}
.wrap {
line-height: 1.5em;
white-space: pre-wrap
}
.icon {
height: .9em;
width: .9em;
vertical-align: middle;
margin-inline-end: .2em
}
h3>.icon {
margin-block-end: .4ex
}
.icon[src$="map-pin.svg"] {
vertical-align: initial;
margin-block-start: -.4ex
}
.icon[src$="trophy.svg"],
.icon[src$="document-text.svg"] {
margin-block-start: -.2ex
}
.icon[src$="heart.svg"],
.icon[src$="academic-cap.svg"] {
margin-block-start: -.1ex
}
.icon[src$="github"] {
margin-block-end: .4ex
}
.icon[src$="element"] {
margin-block-end: .3ex
}
.icon[src$="signal"],
.icon[src$="globe-alt.svg"] {
margin-block-end: .2ex
}
.icon[src$="linkedin"],
.icon[src$="phone.svg"],
.icon[src$="envelope.svg"] {
margin-block-end: .1ex
}
.float {
float: inline-end;
margin-inline-end: .75em
}
.sep {
margin-block-start: .25em
}
.sep>b::after {
content: "·";
padding: 0 .5em
}
.education>div+div {
margin-block-start: 1.5ex
}
.education .courses>ul {
display: flex;
flex-wrap: wrap;
margin-block-end: 0
}
.education .courses>ul>li {
flex-basis: 50%
}
.project>div+div {
margin-block-start: 1.5ex
}
.reference {
background: #d3d3d3;
border-radius: 1.5ex;
padding: .5em 1em;
print-color-adjust: exact
}
.reference>blockquote {
font-style: italic;
quotes: "“" "”";
margin: 0
}
.reference>blockquote::before {
content: open-quote;
font-size: 2em;
line-height: .1em;
vertical-align: -.4em;
color: #789;
padding-inline-end: .25em
}
.reference>blockquote::after {
content: close-quote;
font-size: 2em;
line-height: .1em;
vertical-align: -.4em;
color: #789;
padding-inline-start: .2em
}
.reference>b::before {
content: "–";
padding: 0 .5em 0 0
}
:is(.skill, .language, .interest)>div {
margin-block-start: .75ex
}
#summary {
padding-block-end: 1em;
border-block-end: .1ex dotted #a9a9a9
}
#image {
display: contents
}
#image>img {
float: inline-end;
max-height: 90%;
border: .3ex solid #006400;
border-radius: 15%
}
:is(#contact, #profiles)>div {
margin-block-end: .25ex
}
@supports not (float:inline-end) {
html[dir="ltr"] #image>img,
html[dir="ltr"] .float {
float: right
}
html[dir="rtl"] #image>img,
html[dir="rtl"] .float {
float: left
}
}
</style>
<title>Wei Li</title>
</head>
<body>
<header class="flex">
<section>
<h1 id="name">Wei Li</h1>
</section>
</header>
<main>
<article id="about">
<h3><img class="icon" alt=""
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/identification.svg">Personal
Info</h3>
<address class="flex">
<section id="contact">
<div class="url"><img class="icon" alt="E-mail"
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/envelope.svg"><a
rel="me" href="mailto:wxl885@student.bham.ac.uk">wxl885@student.bham.ac.uk</a></div>
<div><img class="icon" alt="Address"
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/map-pin.svg"><span>University
of Birmingham, Edgbaston, Birmingham, B15 2TT, West Midlands, United Kingdom</span></div>
</section>
<section id="profiles">
<div class="brand"><img class="icon" alt="LinkedIn" src="https://cdn.simpleicons.org/linkedin"><a
rel="me" href="www.linkedin.com/in/wei-li-69a187174">Wei Li</a></div>
</section>
</address>
</article>
<article id="education">
<h3><img class="icon" alt=""
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/academic-cap.svg">Education
</h3>
<section class="education details">
<div><strong><span>PhD Candidate - Natural Language Processing</span></strong><span class="float"><time
datetime="2020-02-01">February 2020</time><span>Present</span></span></div>
<div><strong>University of Birmingham</strong><b class="float">PhD</b></div>
</section>
<section class="education details">
<div><strong><span>M.Sc. (Taught) Advanced Computer Science</span></strong><span class="float"><time
datetime="2019-09-01">September 2019</time><span>Present</span></span></div>
<div><strong>University of Birmingham</strong><b class="float">MSc</b></div>
<div class="grade"><b>Grade: </b>Distinction</div>
</section>
<section class="education details">
<div><strong><span>Computer Science</span></strong><span class="float"><time
datetime="2017-09-01">September 2017</time><span>Present</span></span></div>
<div><strong>Changsha University of Science and Technology</strong><b class="float">BEng</b></div>
<div class="grade"><b>Grade: </b>Overall GPA 83.99/100 (rank 13/154)</div>
</section>
</article>
<article id="publications" class="flex">
<h3><img class="icon" alt=""
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/document-text.svg">Publications
</h3>
<section class="publication">
<div><strong><span>Sparse KD: Knowledge Distillation for Sparse Models in Constrained Fine-tuning
Scenarios</span></strong></div>
<div class="sep"><b>arXiv</b><time datetime="2024">Jan 2024</time></div>
<p class="wrap">This paper proposed Sparse KD, the first distillation framework specifically designed
for sparse models in constrained finetuning scenarios.</p>
</section>
<section class="publication">
<div><strong><span>UoB_UK at SemEval 2021 Task 2: Zero-Shot and Few-Shot Learning for Multi-lingual and
Cross-lingual Word Sense Disambiguation</span></strong></div>
<div class="sep"><b>Association for Computational Linguistics (SemEval-2021)</b><time
datetime="2022">Jan 2022</time></div>
<p class="wrap">This paper describes our submission to SemEval 2021 Task 2. The experiments on both the
multi-lingual and cross-lingual data show that XLM-RoBERTa Large, unlike the Base version, seems to
be able to more effectively transfer learning in a few-shot setting and that the k-nearest
neighbours’ classifier is indeed a more powerful classifier than a multi-layered perceptron when
used in few-shot learning.</p>
</section>
<section class="publication">
<div><strong><span>Location Data Privacy Protection based on Differential Privacy
Mechanism</span></strong></div>
<div class="sep"><b>Application Research of Computers, China</b><time datetime="2018">Jan 2018</time>
</div>
<p class="wrap">This paper proposes using contextual augmentation by fine-tuning the BERT model and
constructing auxiliary sentences for the sentence-pair classification task. Adequate experiments are
conducted on Sentihood dataset for TABSA(target aspect-based sentiment analysis) task, and the
results show the effectiveness of the proposed method.</p>
</section>
</article>
<article id="work">
<h3><img class="icon" alt=""
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/building-office-2.svg">Work
Experience</h3>
<section class="work details">
<div><strong><span>Shenzhen Fortune Technology Co., Ltd.</span></strong><span class="float"><time
datetime="2013-12-01">December 2013</time><time datetime="2014-12-01">December
2014</time></span></div>
<div><strong>Software Engineer Internship</strong></div>
<p class="wrap">Mainly analyzed and fixed bugs for database, inserting a large quantity of data and
software tests. Wrote an analysis tool by Java to speed up the process of inserting big data,
assembled as an interface to be used by other staff.</p>
</section>
<section class="work details">
<div><strong></strong><span class="float"><time datetime="2020-05-01">May 2020</time><time
datetime="2023-09-01">September 2023</time></span></div>
<div><strong>Teaching Assistant Experience in University of Birmingham</strong></div>
<ul class="highlights">
<li>Module 06-30203 (2020/2021.2022)-Programming in C/C++</li>
<li>Module 06-34238 (2021/2022/2023)-Artificial Intelligence 1</li>
</ul>
</section>
</article>
<article id="projects">
<h3><img class="icon" alt=""
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/archive-box.svg">Projects
</h3>
<section class="project details">
<div><strong><span>Thesis- Advanced MSc: Targeted aspect-based sentiment analysis: Utilizing contextual
augmentation with fine-tuning BERT</span></strong><span class="float"><time
datetime="2019-02-24">February 24, 2019</time><time datetime="2019-08-24">August 24,
2019</time></span></div>
<div class="wrap">This project proposes using contextual augmentation by fine-tuning the BERT model and
constructing auxiliary sentences for the sentence-pair classification task. Adequate experiments are
conducted on Sentihood dataset for TABSA(target aspect-based sentiment analysis) task, and the
results show the effectiveness of the proposed method.</div>
<ul class="highlights">
<li>constructing auxiliary sentences for the sentence-pair classification task</li>
</ul>
<div class="keywords"><mark>Bert</mark><mark>sentiment analysis</mark><mark>Python</mark></div>
</section>
<section class="project details">
<div><strong><span>Mini-Project: Understanding Emotions in Textual Conversations</span></strong><span
class="float"><time datetime="2018-12-24">December 24, 2018</time><time
datetime="2019-04-24">April 24, 2019</time></span></div>
<div class="wrap">This project proposes using contextual augmentation by fine-tuning the BERT model and
constructing auxiliary sentences for the sentence-pair classification task. Adequate experiments are
conducted on Sentihood dataset for TABSA(target aspect-based sentiment analysis) task, and the
results show the effectiveness of the proposed method.</div>
<ul class="highlights">
<li>Emotion Classification</li>
<li>Hybrid Model Approach</li>
</ul>
<div class="keywords"><mark>Hybrid Model Approach</mark><mark>sentiment
analysis</mark><mark>Python</mark><mark>Xgboost</mark><mark>SVM</mark></div>
</section>
</article>
<article id="skills" class="flex">
<h3><img class="icon" alt=""
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/wrench-screwdriver.svg">Skills
</h3>
<section class="skill"><strong>Coding Level</strong>
<div title="Master"><progress max="100" value="100"></progress></div>
<div class="keywords"><mark>Python</mark><mark>C</mark><mark>Java</mark></div>
</section>
<section class="skill"><strong>Libraries and tools</strong>
<div title="Master"><progress max="100" value="100"></progress></div>
<div class="keywords"><mark>Spacy</mark><mark>Sci-Kit</mark><mark>PyTorch</mark><mark>NLTK</mark></div>
</section>
</article>
<article id="awards" class="flex">
<h3><img class="icon" alt=""
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/trophy.svg">Awards
</h3>
<section class="award">
<div><strong>Third Prize in the National College Student Computer Design Contest, China</strong></div>
<div class="sep"><b>Committee of China College Students' Computer Design Competition</b><time
datetime="2014-01-01">Jan 2014</time></div>
</section>
<section class="award">
<div><strong>Three times university First-class Scholarship, China</strong></div>
<div class="sep"><b>Changsha University of Science and Technology</b><time datetime="2017-01-01">Jan
2017</time></div>
</section>
<section class="award">
<div><strong>Excellent Prize in China College Students' 'Internet+'Innovation and Entrepreneurship
Competition</strong></div>
<div class="sep"><b>Hunan Education Department</b><time datetime="2015-01-01">Jan 2015</time></div>
</section>
</article>
<article id="interests" class="flex">
<h3><img class="icon" alt=""
src="https://cdn.statically.io/gh/tailwindlabs/heroicons/master/src/24/outline/heart.svg">Interests
</h3>
<section class="interest"><strong>Wildlife</strong>
<div class="keywords"><mark>Ferrets</mark><mark>Unicorns</mark></div>
</section>
</article>
</main>
</body>
</html>