Marija Stanojevic

[Paper] Stanojevic, M., and Novikova, J. (under review). Predicting Alzheimer's in Multilingual Settings.

[Paper] Nowenstein, I., Stanojevic, M., Ornolfsson, G., Jonsdottir, M. K., Simpson, B., Nerin, J. S., Bergporsdottir, B., Hannesdottir, K., Novikova, J., and Curcic, J. (2024). Speech and Language Biomarkers of Neurodegenerative Conditions: Developing Cross-Linguistically Valid Tools for Automatic Analysis. In Proceedings. RAPID-5 Workshop, LREC-COLING Conference 2024.

[Preface] Stanojevic, M. (2024). Machine Learning for Cognitive and Mental Health. In Proceedings. Machine Learning for Cognitive and Mental Health Workshop, AAAI 2024.

[Paper][Poster][Presentation] Diep, B., Stanojevic, M., and Novikova, J. (2022). Multi-modal Deep Learning System for Depression and Anxiety Detection. In Proceedings. Empowering Communities: A Participatory Approach to AI for Mental Health, NeurIPS 2022.

[Internship] Adapted Neural Collaborative Filtering with Multimodal Longitudinal Representation Learning for User Embedding, LinkedIn, Summer 2021.

[Internship] Multitask Multilabel MMultimodal Attention Architecture for Extreme Classification, Facebook, Summer 2020.

[Preprint] Akram, A., Stanojevic, M., Ehghaghi, M., and Novikova, J. (2024). Zero-Shot Multi-Lingual Speaker Verification in Clinical Trials. In arXiv preprint arXiv:2404.01981.

[Paper][Poster] Ehghaghi, M., Stanojevic, M., Akram, A., and Novikova, J. (2023). Factors Affecting the Performance of Automated Speaker Verification in Alzheimer’s Disease Clinical Trials. In Proceedings. ClinicalNLP Workshop, ACL 2023.

[Paper] Norris, L.A., Stanojevic, M., Skriner, L.C., Chu, B.C., Aalberg, M., Silverman, W.K., Bodden, D., Piacentini, J.C., Obradovic, Z., & Kendall, P.C. (under review). Using machine learning to predict treatment outcome in a harmonized dataset of youth anxiety treatments.

[Abstract] Norris, L.A., Stanojevic, M., Obradovic, Z., and Kendall P.C. (2022). Predicting Anxiety Treatment Outcomes with Machine Learning. Association for Behavioral and Cognitive Therapies Annual Conference, New York, December 2022.

[Paper][Poster][Presentation][Code] Stanojevic, M., Norris, L., Kendall, P., and Obradovic, Z. (2022). Predicting Anxiety Treatment Outcomes with Machine Learning. Proc. 21st International Conference on Machine Learning and Applications, Special Session on Machine Learning in Health, Bahamas, December 2022.

[Ph.D. Thesis] Stanojevic, M. (2023). Domain Adaptation Applications to Complex High-dimensional Target Data. Doctoral dissertation. Temple University Libraries.

[Paper][Code] Stanojevic, M., Andjelkovic, J., Kasprowicz, A., Huuki, L. A., Chao, J., Hedges, S. B., Kumar, S., and Obradovic, Z. (2023). Discovering Research Articles Containing Evolutionary Timetrees by Machine Learning. Bioinformatics, 39(1), btad035.

[Paper] Andjelkovic, J., Ljubic, B., Hai, A.A., Stanojevic, M., Pavlovski, M., Diaz, W., and Obradovic, Z. (2022). Sequential Machine Learning in Prediction of Common Cancers. Informatics in Medicine Unlocked, p.100928.

[Paper][Code] Ljubic, B., Hai, A.A., Stanojevic, M., Diaz, W., Polimac, D., Pavlovski, M., and Obradovic, Z., (2020). Predicting Complications of Diabetes Mellitus using Advanced Machine Learning Algorithms. Journal of the American Medical Informatics Association, 27(9), pp.1343-1351.

[Paper][Presentation] Alshehri, J., Stanojevic, M., Dragut, E., and Obradovic, Z., 2022. On Label Quality in Class Imbalance Setting - A Case Study. Proc. 21st International Conference on Machine Learning and Applications, Special Session on Machine Learning for Natural Language Processing, Bahamas, December 2022.

[Paper] Alshehri, J., Stanojevic, M., Khan, P., Rapp, P., Dragut, E., and Obradovic, Z. (2022). MultiLayerET: A Unified Representation of Entities and Topics Using Multilayer Graphs. Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Grenoble, France, September 2022.

[Paper][Presentation] Alshehri, J.^*, Stanojevic, M.^*, Dragut, E., and Obradovic, Z. (2021). March. Stay on Topic, Please: Aligning User Comments to the Content of a News Article. In European Conference on Information Retrieval (pp. 3-17). Springer, Cham.

[Book Chapter] Stanojevic, M., Alshehri, J., and Obradovic, Z. (2021). High Performance Computing for Understanding Natural Language. In Handbook of Research on Methodologies and Applications of Supercomputing (pp. 133-144). IGI Global.

[Arxiv Report][Code] Pham, Q., Stanojevic, M., and Obradovic, Z. (2020, May). Extracting Entities and Topics from News and Connecting Criminal Records. In arXiv preprint arXiv:2005.00950.

[Paper][Presentation][Code] Stanojevic, M.^*, Alshehri, J.^*, and Obradovic, Z. (2019, Aug). Surveying Public Opinion Using Label Prediction on Social Media Data. In 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 188-195). IEEE.

[Paper][Poster][Presentation][Code] Stanojevic, M., Alshehri, J., Dragut, E.C. and Obradovic, Z. (2019, Jun). Biased News Data Influence on Classifying Social Media Posts. In 3rd International Workshop on Recent Trends in News Information Retrieval (NewsIR 2019), collocated with 42nd International ACM SIGIR Conf. on Research Development in Information retrieval.

[Paper][Presentation] Han, C., Cao, X.H., Stanojevic, M., Ghalwash, M. and Obradovic, Z., (2019, May). Temporal Graph Regression via Structure-Aware Intrinsic Representation Learning. In Proceedings of the 2019 SIAM International Conference on Data Mining (pp. 360-368). Society for Industrial and Applied Mathematics.

[Grant] Secured a grant with Zoran Obradovic as the Principal Investigator and myself as a collaborator, resulting in an award of 7,500 node hours on TACC Supercomputer resources.

[Paper][Our Report][Our Presentation][Code] Tarca, A.L., Pataki, B.Á., Romero, R., Sirota, M., Guan, Y., Kutum, R., Gomez-Lopez, N., Done, B., Bhatti, G., Yu, T., Andreoletti, G., Chaiworapongsa, T., The DREAM Preterm Birth Prediction Challenge Consortium, Hassan, S.S., Hsu, C.D., Aghaeepour, N., Stolovitzky, G., Csabai, I., and Costello, J.C., (2021). Crowdsourcing Assessment of Maternal Blood Multi-Omics for Predicting Gestational Age and Preterm Birth. Cell Reports Medicine, 2(6), p.100323.

[Abstract] McGee, F., Stanojevic, M., and Biswas A., (2020, Oct). Perplexity And Statistical Energy: Bridging the Gap Between Language and Proteins.

[Report][Presentation] Stanojevic, M., and Obradovic, Z. (2018, Apr). Generalized Procedure for Selecting Methylation CpGs Associated with Cancer.

[Report][Presentation] Stanojevic, M., and Obradovic, Z. (2017, Apr). Network Clustering of Cancer Patients Based on DNA Methylation Variability.

[Abstract] Ball, S., Stanojevic, M., Knighton, C., Campbell, W., Thaung, A., Fisher, A., Bhatti, A., Kang, Y., Srivastava, P., Zhou, F., Obradovic, Z., and Greby, S. (2018, November). Early Feedback From a Pilot of a Cognitive Computing System to Analyze Immunization Data. In Open Forum Infectious Diseases (Vol. 5, No. Suppl 1, p. S741). Oxford University Press.

[Poster][Presentation] Stanojevic, M., Zhou, F., Ball, S., Campbell, W., Thaung, A., Brinkley, J., Greby, S., Bhatti, A., Fisher, A., Kang, Y., Knighton, C., Srivastava, P., and Obradovic, Z., (2018, Aug). A Pilot Cognitive Computing System to Understand Immunization Programs. NSF Workshop.

[Abstract] (2018, Aug). A Pilot of a Cognitive Computing System to Analyze Immunization Data. Public Health Informatics Conference.

[Abstract][Poster] Brinkley, J., Ball, S., Thaung, A., Campbell, W., Obradovic, Z., Stanojevic, M., Zhou, F., Greby, S., Knighton, C., and Fisher, A. (2018, Jun). Exploring the Metadata of Vaccine-Related Twitter Posts: Just How Much Activity Is There and Where Does It Come from? AcademyHealth Annual Research Meeting.

[Abstract][Presentation] (2018, May). Early Feedback from a Pilot of a Cognitive Computing System to Analyze Immunization Data. National Immunization Conference.

[Report] Stanojevic, M. (2018, Mar). A Pilot Cognitive Computing System to Understand Immunization Programs.

[Internship] Recruiting Science: Improved candidate search by implementing NLP and IR techniques to reduce long tail in skills distribution and by proposing, implementing, and evaluating a novel Siamese-like architecture to embed job descriptions (Python, Presto, PyTorch, Caffe2, DL, NLP, IR, internal tools). Facebook, Summer 2019.

[Internship] Pioneered a solution to a large-volume spatio-temporal problem utilizing mean-shift, quick-shift, and hdbscan clustering. Created a proxy to test existing product. Defined evaluation metrics to show potential for implementation into a product (Hadoop, Hive, python, pandas, geo, folium, geopandas, and shapely). Alliance Data Systes, Epsilon, Conversant, Summer 2018.

[Report][Presentation][Code] Stanojevic, M., and Chanda, A. K. (2017, Dec). Multi-class Image Classification using Deep Neural Networks on Extremely Large Dataset.

[Presentation][Code] Stanojevic, M., (2017, Dec). Predicting Grocery Sales.

[Master Thesis] Stanojevic, M., (2017, Sep). Determination of the similarity between the scientific papers using machine learning methods. University of Belgrade

[Project][Code] Stanojevic, M., (2015, Jul). Language Detection.

[Paper][Abstract] Stanojevic, M., Martinez, I. S., & Mazur, N. (2014). Virtual Internships Provided in Collaboration Among Companies and Universities-the Future of Practical Development of Students. In International Technology, Education and Development Conference 2014 Proceedings (pp. 6939-6945). IATED.

[Paper] Campogiani, G., Czahajda, R., Mazur, N., and Stanojevic, M. (2014). Involving students in curriculum development. In Proceedings of Annual Conference of European Society for Englineerinng Education (SEFI AC 2014).