Publications

Journals 

1) M. Bhattacharya, C. Jurkovitz and H. Shatkay. Co-occurrence of Medical Conditions: Exposing Patterns by Topic-Modeling of SNOMED Codes. Journal of Biomedical Informatics. 2018; 82: 31-40 .

2) M. Bhattacharya, C. Jurkovitz and H. Shatkay. Chronic Kidney Disease Stratification using Office Visit Records: Handling Data Imbalance via Hierarchical Meta-Classification. Journal of BMC Medical Informatics and Decision Making. 2018; 18 (Suppl 4), 35-44

3) M. Bhattacharya, D. Lu, P. Lingamaneni, et al. Identifying Ventricular Arrhythmia Cases and their Predictors by Applying Machine Learning Methods to Electronic Health Records of Hypertrophic Cardiomyopathy Patients. The American Journal of Cardiology.

Conference

4) M. Bhattacharya*, Vito Ostuni*, S. Lamkhede. Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn). In Proc. of  RecSys. 

5) Sejoon Oh, Moumita Bhattacharya, Yesu Feng, Sudarshan Lamkhede. IntentRec: Predicting User Session Intent with Hierarchical Multi-Task Learning. arXiv link.

6) M. Bhattacharya, S. Lamkhede. Augmenting Netflix Search with In-Session Adapted Recommendations (link). In Proc. of RecSys 2022.

7) M. Bhattacharya, A. Barapatre. Query as Context for Item-to-Item Recommendation. In Proc. of  RecSys 2020.

8) R. Louca*, M. Bhattacharya*, D. Hu, L. Hong. Joint Optimization of Profit and Relevance for Recommendation Systems in E-commerce. In Proc. of  RecSys.

9) M. Bhattacharya, C. Jurkovitz and H. Shatkay. Assessing Chronic Kidney Disease from Office Visit Records Using Hierarchical Meta-Classification of an Imbalanced Dataset. Proc. of the IEEE Int. Conference on Bioinformatics and Biomedicine (BIBM), 2017. (Acceptance rate ~ 19%)

**Invited by the IEEE BIBM program chair as one of the 10 papers to be included in the special issue of the Journal of BMC Medical Informatics and Decision Making 

10) G. Zhang, M. Bhattacharya, H. Wu, P. Li, L. Li, and H. Shatkay. Identifying Articles Relevant to Drug-Drug Interaction: Addressing Class Imbalance. Workshop on Biomedical and Health Informatics. Proc. of the IEEE Int. Conference on Bioinformatics and Biomedicine (BIBM), 2017. 

11)  M. Bhattacharya, D. Lu, P. Lingamaneni, S. Kudchadkar, G. Villareal, S. Sivalokanathan, P.C. Villalobos, S. Zimmerman, T.P. Abrahram, M. Abraham, H. Shatkay. Identifying Ventricular Arrhythmia Cases and their Predictors by Applying Machine Learning Methods to Electronic Health Records (EHR) of Hypertrophic Cardiomyopathy (HCM) Patients. Proc. of the American Heart Association (AHA), Anaheim, California, 2017.

12) M. Bhattacharya, C. Jurkovitz and H. Shatkay. Identifying Patterns of Associated-Conditions through Topic Models of Electronic Medical Records. Proc. of the IEEE Int. Conference on Bioinformatics and Biomedicine (BIBM), Shenzhen, China, December, 2016. Top Viewed & 3rd most Liked Among 150 Papers Presented. (Acceptance rate ~ 20%)

13) M. Bhattacharya, C. Jurkovitz and H. Shatkay. Identifying Patterns of Co-occurring Medical Conditions through Topic Models of Electronic Health Records (Abstract). AMIA iHealth Clinical Informatics Conference, 2016.

14) M. Bhattacharya, D. Ehrenthal and H. Shatkay. Identifying Growth-Patterns in Children by Applying Cluster Analysis to Electronic Medical Records.  Proc. Of the IEEE International Conference of Bioinformatics and Biomedicine (BIBM), Belfast, UK. 2014. (Acceptance rate ~ 20%)

Other Papers 

15) M. Bhattacharya. Using Machine Learning for Disease Prediction and Patient Risk-Stratification: Studies in the context of Chronic Kidney Disease and Childhood Obesity. PhD Thesis Proposal, Computer and Information Sciences, University of Delaware, 2016. 

16) M. Bhattacharya. Comparative Study of Clustering Methods for Modeling Repeated Time Series Data. PhD Preliminary Examination Thesis, Computer and Information Sciences, University of Delaware, 2014. 

Talks & Presentations

Spring 2018 - Machine Learning Approaches for Patient Risk Stratification, Accelerating Clinical and Translational Research (ACCEL) Tech Talk Seminar Series, Christiana Care Health System, Newark, DE. (INVITED TALK) [Video]

Fall 2017 - Addressing the Challenge of Imbalanced data in the Biomedical Domain for Patient Risk Stratification; Biomedical Engineering Seminar Series, University of Delaware, Newark, DE. (INVITED TALK)

Fall 2017 – Session Chair of Medical Informatics Track, IEEE International Conference of Bioinformatics and Biomedicine (BIBM), Kansas city, USA. 

Fall 2017 - Assessing Chronic Kidney Disease from Office Visit Records Using Hierarchical Meta-Classification of an Imbalanced Dataset, IEEE International Conference of Bioinformatics and Biomedicine (BIBM), Kansas city, USA. 

Fall 2017 - Identifying Articles Relevant to Drug-Drug Interaction: Addressing Class Imbalance, IEEE International Conference of Bioinformatics and Biomedicine (BIBM), Kansas city, USA. 

Spring 2017 – Identifying Patterns of Co-occurring Medical Conditions through Topic Models of Electronic Health Records. Analytics and the Learning Health System Session, AMIA iHealth 2017 Clinical Informatics Conference, Philadelphia, USA. (INVITED TALK)

Fall 2016 – Session Chair of Biomedical Intelligence Track, IEEE International Conference of Bioinformatics and Biomedicine (BIBM), Shenzhen, China. 

Fall 2016 - Identifying Patterns of Associated-Conditions through Topic Models of Electronic Medical Records, IEEE International Conference of Bioinformatics and Biomedicine (BIBM), Shenzhen, China. 

Fall 2016 - Using Machine Learning Techniques to Analyze Electronic Health Records for Patients Risk Stratification; Bioinformatics Seminar Series, University of Delaware, Newark, DE. (INVITED TALK)

Fall 2014 - Identifying Growth-Patterns in Children by Applying Cluster analysis to Electronic Medical Records, IEEE International Conference of Bioinformatics and Biomedicine (BIBM), Belfast, UK. 

Summer 2014 - Automatic Time of Management dashboard using AngularJS and MVC framework; Presented to Senior Leadership, Bank of America, Hopewell, NJ. 

Spring 2014 - Analysis of Repeated Time Series Data Acquired from Electronic Medical Records of Children using 

Clustering Techniques, PhD Prelims Defense Presentation, University of Delaware, Newark, DE.

Poster Presentation

Fall 2017 – Identifying Ventricular Arrhythmia Cases and their Predictors by Applying Machine Learning Methods to Electronic Health Records (EHR) of Hypertrophic Cardiomyopathy (HCM) Patients. Poster presentation at the Proc. of the American Heart Association (AHA), Anaheim, California, 2017. 

Summer 2017 – Identifying Predictive Biomarkers of Type 1 Diabetes Using Supervised Machine Learning Methods. Poster presentation at the National Security Internship Program Symposium, Pacific Northwest National Laboratory, Richland, WA, USA. 

Spring 2017 – Using Machine Learning to Build a Scalable Tool to Support Dietitians to Fight Chronic Diseases. Poster Session Big Data in Healthcare, University of Delaware, Newark, DE