JUNRU LUNatural Language Processing andMachine Learning
enthusiast[ [email protected] ½ Coventry, UK
github.com/LuJunru ® lujunru.github.io
ACHIEVEMENTS3 National 6th position - SMP
• The 6th position in the final-round of the6th national-level
Social Media Process-ing Contest. The contest asked to realize3
tasks including keywords extractionfrom blogs, user interests
labeling, anduser growth prediction.
• For the 1st task, we used Tf-Idf, Tex-trank, LDA, andmanual
rules combinedto find keywords. The 2nd task was real-ized by a
stacking classification on docu-ment embeddings (a later
improvementof 3%was to use TextCNN and self-attention). The final
task was donewitha regressive stackingmodel [Codes].
3 University Honor• University Scholarships of Universityof
International Relations 2015, 2016,2017 (Top 5%).
• 2018 excellent graduation thesis andoutstanding graduates of
University ofInternational Relations.
3 EnactusWord CupThird prize of national final and firstprize of
refional semi-final in 2018 En-actusWorld Cup.
3 Like a Boss Product Design ContestGlobal champion,
awardedwith$30,000. This contest is hosted byBoss Zhipin App,
aiming to invite stu-dents to improve product design forthem.
[OfficialWebsite]
STRENGTHS& SKILLSNatural Language ProcessingMachine Learning
Web Crawler
Pytorch PySpark SkLearn
CODINGPython ○○○○○Sql ○○○○○Javascript ○○○○○
EDUCATIONMPhil/Ph.D. candidate in Computer ScienceUniversity
ofWarwick� Nov. 2019 –Nov. 2023 ½ Coventry, UK• Supervisor: Prof.
Yulan He• Department: Computer Science• Research Interests: Text
representation, question answering and controllabletext generation.
Currently, mywork is around question answering under realworld
scenarios.
M.S. in Applied Urban Science & InformaticsNewYork
University� Sept. 2018 – Sept. 2019 ½ NewYork City, USA• GPA:
3.67/4.00• Center: Center for Urban Science + Progress• Department:
Tandon School of Engineering• Project1: Collect geo-tagged tweets
in NYC using Twitter API and createemotional time-spatial maps
through sentiment analysis [Codes].
• Project2: With RandomForest and LGBMmodels, use Yelp reviews
and re-lated user and business historical infos to predict the
reviews’ ratings [Codes].
• Capstone project: Using DID and Bayesian Network to infer
causality fromthe increase of Uber & Lyft on NYC’s parking
violation. [Codes].
B.Eng. in InformationManagement and Information SystemUniversity
of International Relations� Sept. 2014 – July 2018 ½ Beijing,
China• GPA: 90.6/100• Supervisor: Prof. Binyang Li• Department:
School of Information Science and Technology• Final Thesis: a
two-stagemulti-attentionMachine Reading Comprehensionmodel
(A-Reader). In A-Reader, text representation is realized with
self-attention, while semantic interaction between article and
question is based onself-attention and bi-attention. "Two-stage"
refers to firstly use the final se-mantic matrix (FSM) within a
binary classificationmodel to select a best para-graph, and
secondly predict the answer via pointer network with the FSM.
Double Bachelor of EconomicsPeking University� Sept. 2015 – July
2018 ½ Beijing, China• GPA: 84.2/100• Department: National School
of Development• Major courses: Accounting, Econometrics,
Microeconomics, and Finance.• Notes: TheDouble B.Eco. is a program
for non-economics undergraduatesfrom PKU and other universities who
are interested in economics since 2003.
https://github.com/LuJunruhttps://lujunru.github.io/https://github.com/LuJunru/SMPCUP2017_ELPhttps://www.zhipin.com/zt/2019/likeaboss/pc/https://sites.google.com/view/yulanhe/home?authuser=0https://github.com/LuJunru/ADS2018_Final_Projecthttps://github.com/LuJunru/MLC2019_Final_Projecthttps://github.com/LuJunru/NYU-CUSP-Capstone-2019https://xinke.uir.cn/c/2016-02-26/541594.shtmlhttp://en.nsd.pku.edu.cn/programs/doublemajor/index.htm
PUBLICATIONSq Journal Articles• Lu, Junru et al. (2019).
“Identifying UserProfile by Incorporating Self-AttentionMechanism
based on CSDNData Set”. In:Data Intelligence 1.2, pp. 160–175.
Conference Proceedings• [Accepted by COLING 2020] Lu, Junru
etal. (2020). “Chime: Cross-passage Hierar-chical Memory Network
for GenerativeReviewQuestion Answering”. In: The 28thInternational
Conference on ComputationalLinguistics.
• Cai, Junjie et al. (2020). “Estimating theeffect of Uber &
Lyft on parking violationin NYC”. in: Transportation Research
BoardAnnual Meeting.
last updated: July 2nd, 2019
WORKEXPERIENCENatural Language Processing Engineer
InternshipBeijing iDeepWise Artificial Intelligence Tech Ltd� Mar.
2018 – June 2018 ½ Beijing, China• Project1: Research on two
sentence similarity models, TextCNN and Siamese-LSTM. TextCNN is to
construct 2D input by calculatingW2V-Cosine-Similarityof sentences’
sub-units, while Siamese-LSTM is to useManhattan distance tocompare
the final hidden states of the sentences encodedwith LSTM
[Codes].
• Project2: Implement a two-stage BiDAFmodel on Dureader
Dataset. TheBiDAFmodel is a traditionalMachine Reading
Comprehensionmodel, whichuses bi-LSTM to realize text
representation and bi-attention on semantic in-teraction.
"Two-stage" refers to firstly select the best
paragraphwithmanu-ally selected features, and secondly predict the
answer via Pointer Network.
DataMining Engineer Internship, Dept. of TextMiningBeijing
Baifendian InfoTech Ltd� Oct. 2017 –Mar. 2018 ½ Beijing, China•
Project: Develop a single-round Community-based Chinese DeepQA
System.The system consists of (Q, A) knowledge database,
first-round query enginebased on Elasticsearch, second-round
selectivemodules including semanticsimilarity check on (NewQ, OldQ)
and pair quality check on (NewQ, Old A),and compensatory web
crawler for unknown new questions [Codes].
https://github.com/LuJunru/Sentences_Pair_Similarity_Calculation_Siamese_LSTMhttps://github.com/LuJunru/My_QA_Robot
