Anagha Kulkarni

Associate Professor
Computer Science Department
San Francisco State University
Ph: 415 338 2539
Office: Thornton Hall 970
ak@sfsu.edu

About

Anagha Kulkarni is an Associate Professor of Computer Science at San Francisco State University. Her research investigates problems at the intersection of information retrieval (IR), natural language processing (NLP), and machine learning (ML). Her work applies IR, NLP, and ML tools and techniques to multidisciplinary problems in public health, social justice, women's health, and biomedical search and visualization. She is involved in CS education and diversity initiatives such as PINC (Promoting INclusivity in Computing). She is affiliated with the SOUL Lab and the CoSE Computing for Life Sciences. Currently she serves as the Senior advisor for the Computer Science department.

Publications

(* indicates undergraduate and graduate student co-authors.)

Lowell M.* Motamarry S.* and Kulkarni A. (2019) ARtPM: Article Retrieval for Precision Medicine. Journal of Biomedical Informatics, 103224.

Costa J.* and Kulkarni A. (2018) Leveraging Knowledge Graph for Open-domain Question Answering. In the Proceedings of 2018 IEEE International Conference on Web Intelligence. December 2018. Santiago, Chile.

Kulkarni A., Yoon I., Pennings P., Okada K., and Domingo C. (2018) Promoting Diversity in Computing. In the Proceedings of 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education. July 2018. Larnaca, Cyprus.

Yoon I., Pennings P., Kulkarni A., Okada K., and Domingo C. (2018) Promoting Inclusivity in Computing (PINC) via Computing Application Minor. In the Proceedings of Collaborative Network for Engineering and Computing Diversity Conference. April 2018. Arlington, Virginia, USA.

Pithyaachariyakul C.* and Kulkarni A. (2018) Automated Question Answering System for Community-based Questions. In the Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, Student Abstract and Poster Program. February 2018. New Orleans, USA.

Previde P.*, Thomas B.*, Wong M., Mallory E.*, Petkovic D., Altman R., and Kulkarni A. (2018) GeneDive: A Gene Interaction Search and Visualization Tool to Facilitate Precision Medicine. In the Proceedings of Pacific Symposium on Biocomputing, Vol 23, pp. 590-601. January 2018. Hawaii, USA.

Chuang M.* and Kulkarni A. (2017) Improving Shard Selection for Selective Search. In the Proceedings of the Asia Information Retrieval Societies Conference. November 2017. Jeju, Korea.

Chuang M.* and Kulkarni A. (2017) Balancing Precision and Recall with Selective Search. In the Proceedings of the Annual International Symposium on Information Management and Big Data. September 2017. Lima, Peru.

Pithyaachariyakul C.*, Khvalchik M.*, Kulkarni A. (2017) Automated Question Answering System. In the Proceedings of the Annual International Symposium on Information Management and Big Data. September 2017. Lima, Peru.

Khvalchik M.*, and Kulkarni A. (2017) Open-domain Non-factoid Question Answering. In the Proceedings of the International Conference on Text, Speech, and Dialogue. August 2017. Prague, Czechia.

Khvalchik M.*, Pithyaachariyakul C.*, and Kulkarni A. (2017) Answering the Hard Questions. In the Proceedings of the Language, Data, and Knowledge. June 2017, Galway, Ireland.

Wei W.*, Kulkarni A., Wong M. (2017) PF-Words: Biomedical Literature Based Protein Function Search. In the Proceedings of the International Conference on Bioinformatics and Computational Biology. March 2017, Honolulu, HI, USA.

Saylor B.*, Kulkarni A., Martinez N., and Yoon I. (2016) Optimizing Ecological Sustainability by Integrating Intuition and Machine Learning via Gamification. In the Proceedings of the International Conference on Computational Sustainability. July 2016, Ithaca, NY, USA.

Khvalchik M.* and Kulkarni A. (2016) San Francisco State University at LiveQA Track of TREC 2016. In the Proceedings of the Twenty-Fifth Text REtrieval Conference (TREC 2016). National Institute of Standards and Technology, special publication.

Chuang M*. and Kulkarni A. (2016) San Francisco State University at Total Recall Track of TREC 2016. In the Proceedings of the Twenty-Fifth Text REtrieval Conference (TREC 2016). National Institute of Standards and Technology, special publication.

Kulkarni A. and Callan J. (2015) Selective Search: Efficient and Effective Search of Large Textual Collections. ACM Transactions on Information Systems, 33(4). ACM. 2015.

Kulkarni A. (2015) ShRkC: Shard Rank Cutoff Prediction for Selective Search. In the Proceedings of the International Symposium on String Processing and Information Retrieval, pages 337—349, Sept 2015, London, UK.

Kulkarni A. (2015) Searching Large Textual Dataset With Limited Computational Resources. In the Proceedings of the Grace Hopper Conference. Oct 2015, Houston, USA.

Bhandari A.*, Klinkhammer J.*, and Kulkarni A. (2014) San Francisco State University at TREC 2014: Clinical Decision Support System Track and Microblog Track. In Proceedings of the Twenty-Third Text REtrieval Conference (TREC 2014). National Institute of Standards and Technology, special publication. 2015.

Kulkarni A. (2013) Efficient and Effective Large-scale Search. Carnegie Mellon Unversity.

Kulkarni A., Tigelaar A., Hiemstra D. and Callan J. (2012) Shard Ranking and Cutoff Estimation for Topically Partitioned Collections: In the Proceedings of the ACM Conference on Information and Knowledge Management, pages 555—564, Oct 2012, Maui, USA.

Kulkarni A., Teevan J., Svore K. and Dumais S. (2012) Creating Temporally Dynamic Web Search Snippets: In the Proceedings of the Poster Session of Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 1045-1046, Aug 2012, Portland, USA.

Kulkarni A., Teevan J., Svore K. and Dumais S. (2011) Understanding Temporal Query Dynamics: In the Proceedings of the ACM International Conference on Web Search and Data Mining, pages 167-176, Feb 2011, Hong Kong.

Kulkarni A. and Callan J. (2010) Document Allocation Policies for Selective Searching of Distributed Indexes: In the Proceedings of the ACM Conference on Information and Knowledge Management, pages 449-458, Oct 2010, Toronto, Canada.

Kulkarni A. and Callan J. (2010) Topic-based Index Partitions for Efficient and Effective Selective Search: In the Proceedings of SIGIR 2010 Workshop on Large-Scale Distributed Information Retrieval, July 2010, Geneva, Switzerland.

Kulkarni A. and Pedersen T. (2008) Name Discrimination and E-mail Clustering Using Unsupervised Clustering of Similar Concepts: Journal of Intelligent Systems (Special Issue: Recent Advances in Knowledge-Based Systems and Their Applications), 17(1-3), 37-50, 2008.

Kulkarni A. and Callan J. (2008) Dictionary Definitions based Homograph Identification using a Generative Hierarchical Model: In the Proceedings of the Association for Computational Linguistics: Human Language Technologies, pages 85-88, June 15-20, Columbus, Ohio, USA.

Kulkarni A., Heilman M., Callan J. and Eskenazi M. (2008) Word Sense Disambiguation for Vocabulary: In the Proceedings of the International Conference on Intelligent Tutoring Systems, pages 500-509, June 23-27, 2008, Montreal, Canada.

Kulkarni A., Callan J. and Eskenazi M. (2007) Dictionary Definitions: The Likes and the Unlikes: In the Proceedings of the SLaTE Workshop on Speech and Language Technology in Education, October 1-3, 2007, Farmington, PA, USA.

Pedersen T. and Kulkarni A. (2007) Unsupervised Discrimination of Person Names in Web Contexts: In the Proceedings of the Conference on Intelligent Text Processing and Computational Linguistics, pages 299-310, February 18-24, 2007, Mexico City.

Pedersen T. and Kulkarni A. (2007) Discovering Identities in Web Contexts with Unsupervised: In the Proceedings IJCAI-2007 Workshop on Analytics for Noisy Unstructured Text Data, January 8, 2007, Hyderabad, India.

Kulkarni A. and Pedersen T. (2006) How many different "John Smiths", and who are they?: In the Proceedings of the Student Abstract and Poster Session of the Twenty-First National Conference on Artificial Intelligence, pages 1885-1886, July 16-20, 2006, Boston, Massachusetts.

Pedersen T. and Kulkarni A. (2006) Automatic Cluster Stopping with Criterion Functions and the Gap Statistics: In the Proceedings of the Demonstration Session of the Human Language Technology Conference and the Annual Meeting of the North American Chapter of the Association for Computational Linguistic, pages 276-279, June 6, 2006, New York City.

Pedersen T., Kulkarni A., Angheluta R., Kozareva Z. and Solorio T. (2006) Improving Name Discrimination: A Language Salad Approach: In the Proceedings of the EACL 2006 Workshop on Cross-Language Knowledge Induction, April 3, 2006, Trento, Italy.

Pedersen T. and Kulkarni A. (2006) Selecting the "Right" Number of Senses Based on Clustering Criterion Functions: In the Proceedings of the Posters and Demo Program of the European Chapter of the Association for Computational Linguistics, pages 111-114, April 3-7, 2006, Trento, Italy.

Pedersen T., Kulkarni A., Angheluta R., Kozareva Z. and Solorio T. (2006) An Unsupervised Language Independent Method of Name Discrimination Using Second Order Co-Occurrence Vectors: In the Proceedings of the Conference on Intelligent Text Processing and Computational Linguistics, Lecture Notes in Computer Science, Springer, pages 208-222, February 19-25, 2006, Mexico.

Kulkarni A. and Pedersen T. (2005) Name Discrimination and Email Clustering using Unsupervised Clustering and Labeling of Similar Contexts: In Proceedings of the Indian International Conference on Artificial Intelligence, pages 703-722, December 20-22, 2005, Pune, India.

Pedersen T. and Kulkarni A. (2005) Identifying Similar Words and Contexts in Natural Language with SenseClusters: In AAAI ’05: Proceedings of the National Conference on Artificial Intelligence, pages 1694-1695, July 2005, Pittsburgh, PA, USA. (Intelligent Systems Demonstration)

Kulkarni A. and Pedersen T. (2005) SenseClusters: Unsupervised Clustering and Labeling of Similar Contexts: In Proceedings of the Demonstration and Interactive Poster Session of the Annual Meeting of the Association for Computational Linguistics, pages 105-108, June 26, 2005, Ann Arbor.

Kulkarni A. (2005) Unsupervised Discrimination and Labeling of Ambiguous Names: In Proceedings of the Student Research Workshop of the 43rd Annual Meeting of the Association of Computational Linguistics, June 25-30, 2005, Ann Arbor, MI, USA.

Pedersen T., Purandare A., and Kulkarni A. (2005) Name Discrimination by Clustering Similar Contexts: In Proceedings of the Conference on Intelligent Text Processing and Computational Linguistics, Lecture Notes in Computer Science, Springer, pages 226-237, February 13-19, 2005, Mexico.

Research Group

Praharshit Gorripaty studies neighborhood smoking norms through crowdsourced and social media data.

Sirisha Motamarry works on article retrieval systems for precision medicine.

Karuna Nayak works on understanding the impact of reflective journaling on students success and retention.

Tejasvi Belsare studies the information barriers in regards to long acting reversible contraceptives.

Nayana Laxmeshwar works on biomedical search and visualization.

Girish Tiwale works on large-scale search.

Former Students

Lowell Milliken, Thesis: ARtPM: Article Retrieval for Precision Medicine. Fall `18.
Jose Ortiz-Costa, Thesis: A Framework for Knowledge Graph Based Question Answering. Summer `18.
Mon Shih Chuang, Thesis: Balancing Precision and Recall with Selective Search. Spring `18.
Meghana Dayanand, Thesis: PGxAssist: A Retrieval and Summarization System for Pharmacogenomics. Spring `18.
Chanin Pithyaachariyakul, Thesis: Automated Question Answering System. Fall `17.
Brook Thomas, Thesis: GeneDive: Gene Relationship Search and Discovery. Fall `17.
Maria Khvalchik, Thesis: Automatic Question Answering System for Factoid and Non-Factoid Open-Domain Questions. Spring `17.
Jack Cole, Independent study: Toward Production-grade GeneDive. Fall `18.
Diana Yu Yu, Independent study: LARC Information on the Web. Fall `18.
Nimiksha Mahajan, Independent study: Study of Toxic comments on Social Media. Fall `18.
Emily Fryer, Independent study: Topic Modeling of Social Media Data for Neighborhood Smoking Norms. Fall `18.
Amanda Nikkole Robinsen, Independent study: Exploiting Linguistic Signals for Question Answering. Spring `18.

Courses Taught

I teach the Search Engines course, and Introduction to Database Management Systems course on regular basis. In the past I have taught Introduction to Computer Programming, and Discrete Mathematical Structures for Computer Science. In Fall 2017 I started instructing a new course (CSc 698: Topics in Computing) for the PINC program. In this 2-semester long course students work in groups on a project of their choice. Here are some of the project topics that the students have undertaken in Fall `17: social media data analysis to detect messaging biases related to stigmatized medical conditions, image processing for biological cells, classification of sequencing data for HIV subtypes, an educational game for teaching genetics, alcohol level detection using facial image processing, audio analysis, and geo locations.