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JAYADEV  JAYARAMAN              

2126 Oak Street, Los Angeles, CA 90007                                      Email:     jdevjram@gmail.com

Phone:  (310) 729-7230                                                                  Website:  www-scf.usc.edu/~jjayaram

·       Programming languages:           C/C++, JAVA, Python, PERL, Javascript, PL/SQL, Verilog HDL

·       Packages:                                 MATLAB, MySQL,  Lex & Yacc, Altera Quartus II

·       Natural language toolkits:         GIZA++, Carmel, Tiburon, SRILM

·       Operating Systems:                    Microsoft Windows, GNU/Linux (Debian/Ubuntu)

1.        “Linear Time Decoding in Machine Translation” – Directed Research                                                        (Jan ‘10 – present) 

Advisors:  Dr. D. Chiang & Dr. L. Huang, ISI Natural Language Group, Marina Del Rey, CA

 Project Accomplishments:

·       Adapting SCFG-based left-to-right target generation algorithm (T. Watanabe, 2006) to work with generic SCFGs.

·       Improving decoder performance using cube-pruning (Chiang, 2007); investigating left-corner parsing variants.

2.        “A Word-based French-English Machine Translation (MT) System”                                                           (Oct ‘09 – Dec ‘09) 

 Advisors:  Dr. D. Chiang & Dr. L. Huang, ISI Natural Language Group, Marina Del Rey, CA

Project Accomplishments:

·       Built and evaluated a MT system for French to English translation based on IBM word-alignment models.

·       A stack decoder incorporating beam-search was developed and used to generate candidate translations.

3.        “Causal link detection in data using Monte Carlo methods”                                                                           (Mar ‘10 – May ‘10)

Advisor:   Dr. F. Sha, Dept. of CS, Univ. of S. California, Los Angeles, CA  

Project Accomplishments:

·       Implemented a method for weighting hypotheses of Bayesian Network structure, given sparse-data.

·       Monte-Carlo sampling of BN orderings was used to weight edge and path features given a dataset.

4.         "Feature-phrase directed extraction of sentiment from text”                                                                   (Jan ‘09 – May ‘09)

 Advisor:  Dr. V. Gopalakrishnan, Dept. of CSE., NIT Trichy, India

Project Accomplishments:

·        Designed and developed methods for unsupervised learning for Hidden-Markov-Model based PoS tagging.

·        A PoS tagger was built and used to build a MLE (of word mixture-models) based feature-phrase extractor.

M.S. Computer Science (Specialization: Human Language Technology)                                           Aug ‘09 – Dec ‘10

University of Southern California, Los Angeles, CA                                                                                       GPA:     3.74/4.00

·       Directed Research experience in NLP;  Secured A grades in advanced level NLP courses

B.Tech. Computer Science & Engineering                                                                                    Jul ‘05 – May ‘09

National Institute of Technology (formerly Regional Engineering College), Trichy, India                                           GPA:  7.71/10.00                                                                                                               

·       School-first: 98% in Computer Science – Class XII final All-India Senior School Certificate Exam (2005)

·       General proficiency: 95.6% overall – Class XII final All-India Senior School Certificate Exam (2005)

·       Obtained state rank 95 & admission to NIT, Trichy – All India Engineering Entrance Exam (AIEEE – May 2005)

·       1056 points in 3 online Single Round Programming Contests, on Topcoder (handle: thejdev; www.topcoder.com).

·       Coordinator, Org. Committee: ‘Vortex 2008’, a national-level annual Technical Symposium, CSE Dept., NIT, Trichy, India

·       Coordinator, Printing Committee:  ‘Festember 2006’, a national-level inter-collegiate cultural festival, NIT, Trichy, India

REFERENCES:    Several excellent references furnished upon request.          (Also, please see my website for further details.)