• Ph.D. in Statistics, Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
• M.S. in Statistics , Department of Statistics, Faculty of Mathematical Sciences, Univer- sity of Tehran, Tehran, Iran
• B.A. in Statistics, Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran

• Member of the organizing committee, Scientific Committee for the First Event on Play with Real Data, with support from International Statistical Institute (2020-2021)
• Member of the organizing committee, The third Frontiers in Biological Sciences sympo- sium at the School of Biological Sciences, Institute for research in fundamental sciences (IPM), Iran (2019)
• Member of the organizing committee, Workshop on Advanced Statistical Methods in Cognitive Science (SDAT Team) (2018)
• Member of the organizing committee, Second Frontiers in Biological Sciences sympo- sium at School of Biological Sciences, part of the Institute for research in fundamental sciences (IPM) in Iran (2018)
• Member of the organizing committee, Systems Biology Seminar at School of Biological Sciences, part of the Institute for research in fundamental sciences (IPM) in Iran (2018)
• Member of the organizing committee, NGS workshop at School of Biological Sciences, Institute for research in fundamental sciences (IPM) in Iran (2018)
• Member of the organizing committee, The First Frontiers in Biological Sciences sym- posium at School of Biological Sciences, Institute for research in fundamental sciences (IPM) in Iran (2017)
• Member of the organizing committee, Workshop on Advanced Statistical Methods (SDAT Team) (2016)
• Member of the organizing committee, Summer School in Bioinformatics at School of Biological Sciences, Institute for research in fundamental sciences (IPM) in Iran (2015)
• Reviewer for Bioinformatics Journal (5 reviews) (2016)
• Reviewer for IEEE Access Journal (9 reviews) (2018)
• Reviewer for Wiley Interdisciplinary Reviews: Systems Biology and Medicine Journal (2 reviews) (2020)
• Reviewer for BMC Bioinformatic Journal (2 reviews) (2020)
• Reviewer for BMC Genomics Journal (2 reviews) (2020)
• Reviewer for Pattern Recognition Letters Journal (1 reviews) (2016)
• Reviewer for Pattern Recognition Journal (1 reviews) (2015)
• Reviewer for Computational and Mathematical Methods in Medicine Journal (1 reviews) (2019)
• Reviewer for Iranian Journal of Biotechnology Journal (1 reviews) (2015)
• Reviewer for Journal of the Iranian Statistical Society (1 reviews) (2016)
• Reviewer for INFS Proposals (reviewed 1 proposal) (2019)

• Rosa Aghdam, Mahnaz Habibi, and Golnaz Taheri. Using informative features in ma- chine learning based method for covid-19 drug repurposing. Journal of Cheminformatics, 13(70), 2021.
• Raziyeh Masumshah, Rosa Aghdam, and Changiz Eslahchi. A neural network-based method for polypharmacy side effects prediction. BMC bioinformatics, 22(1):1–17, 2021.
• Sayyed Hadi Mahmoodi, Rosa Aghdam, and Changiz Eslahchi. An order independent algorithm for inferring gene regulatory network using quantile value for conditional independence tests. Scientific Reports, 11(1):1–15, 2021.
• Mahnaz Habibi, Golnaz Taheri, and Rosa Aghdam. A SARS-CoV-2 (COVID-19) biolog- ical network to find targets for drug repurposing. Scientific Reports, 11(1):1–15, 2021.
• Elnaz Saberi Ansar, Changiz Eslahchi, Mahsa Rahimi, Lobat Geranpayeh, Marzieh Ebrahimi, Rosa Aghdam, and Gwenneg Kerdivel. Significant random signatures reveals new biomarker for breast cancer. BMC Medical Genomics, 12(1):160, 2019.
• Rosa Aghdam, Vahid Rezaei Tabar, and Hamid Pezeshk. Some node ordering methods for the K2 algorithm. Computational Intelligence, 35(1):42–58, 2019.
• Rosa Aghdam, Taban Baghfalaki, Pegah Khosravi, and Elnaz Saberi Ansari. The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer. Genomics, proteomics & bioinformatics, 15(6):396–404, 2017.
• Rosa Aghdam, Mojtaba Ganjali, Parisa Niloofar, and Changiz Eslahchi. Inferring gene regulatory networks by an order independent algorithm using incomplete data sets. Journal of Applied Statistics, 43(5):893–913, 2016.
• Rosa Aghdam, Taban Baghfalaki, Pegah Khosravi, and Elnaz Saberi Ansari. Compar- ative Analysis of Gene Regulatory Networks Concepts in Normal and Cancer Groups. Bioinformatics & Biocomputational Research, 1(1), 2016.
• Rosa Aghdam, Mohsen Alijanpour, Mehrdad Azadi, Ali Ebrahimi, Changiz Eslahchi, and Abolfazl Rezvan. Inferring gene regulatory networks by PCA-CMI using Hill climbing algorithm based on MIT score and SORDER method. International Journal of Biomathematics, 9(03):1650040, 2016.
• Mahnaz Habibi, Pooneh Khoda Bakhshi, and Rosa Aghdam. LRC: A new algorithm for prediction of conformational B-cell epitopes using statistical approach and clustering method. Journal of immunological methods, 427:51–57, 2015.
• Rosa Aghdam, Mojtaba Ganjali, Xiujun Zhang, and Changiz Eslahchi. CN: a consensus algorithm for inferring gene regulatory networks using the SORDER algorithm and conditional mutual information test. Molecular BioSystems, 11(3):942–949, 2015.
• Rosa Aghdam, Mojtaba Ganjali, and Changiz Eslahchi. IPCA-CMI: an algorithm for inferring gene regulatory networks based on a combination of PCA-CMI and MIT score. PloS one, 9(4):e92600, 2014.
• Sattar Soltani, Hossein Askari, Nasim Ejlali, and Rosa Aghdam. The structural prop- erties of DNA regulate gene expression. Molecular BioSystems, 10(2):273–280, 2014.
• Rosa Aghdam, Hamid Pezeshk, Seyed Amir Malekpour, Soudabeh Shemehsavar, and Changiz Eslahchi. A clustering approach for estimating parameters of a profile hidden Markov model. International journal of data mining and bioinformatics, 8(1):66–82, 2013.
• Ali Ebrahimi, Rosa Aghdam, Parisa Niloofar, Mojtaba Ganjali, and Changiz Eslahchi. LSPC: An algorithm for inference of gene networks using Bayesian network. Journal of Emerging Trends in Computing and Information Sciences, 3(5), 2012.
• Rosa Aghdam, Hamid Pezeshk, Seyed Amir Malekpour, Mehdi Sadeghi Shemehsavar, Soudabeh, and Changiz Eslahchi. A Bidirectional Bayesian Monte Carlo Approach for Estimating Parameters of A Profile Hidden Markov Model. Applied Science Segment, 1(2):1–10, 2011.
• Rosa Aghdam, Nasim Ejlali, and Hamid Pezeshk. A New Method for Estimating Pa- rameters of a Profile Hidden Markov Model. Biostatistics, Bioinformatics and Biomathe- matics, 2(1):33–42, 2010.

• Rosa Aghdam, Mojtaba Ganjali, and Changiz Eslahchi. A Hybrid Algorithm for Infer- ring Gene Regulatory Networks. Twelfth Iranian Statistical Conference. Kermanshah, Iran, 2014.
• Rosa Aghdam, Mohsen Alijanpour, Mehrdad Azadi, and Ali Ebrahimim. Applying a Hybrid Method based on PC algorithm-based approach and MIT Score to Infer Gene Regulatory Networks. 5th Iranian Conference on Bioinformatics. Tehran, Iran, 2013.
• Rosa Aghdam, Hamid Pezeshk, and Mojtaba Ganjali. A new method for estimating pa- rameters of a profile hidden Markov model based on phylogenetic tree. 11th conference of Statistics.Tehran, Iran, 2012.

• Talk & Demo: “MISSL: Multiple Instance Semi Supervised Learning”. 23rd International Conference on Machine Learning (Pittsburgh, Pennsylvania) (2006)
• Talk & Demo: “Accio! Localized Content Based Image Retrieval”. Waseda University (Tokyo, Japan) (2005). University of Electro­Communications (Tokyo, Japan) (2005). National University of Singapore (Singapore) (2005). 7th ACM SIGMM International Workshop on Multimedia (Singapore) (2005)

• IEEE Transactions on Pattern Analysis and Machine Intelligence (2010)

Reviewer for article submitted for publication.

• IEEE Transactions on Knowledge and Data Engineering (2009)

-Reviewer for article submitted for publication.

• Journal of Pattern Recognition (2009)

-Reviewer for article submitted for publication.

• Journal of Machine Learning Research (2005)

-Co­reviewed 2 articles submitted for publication.

• IEEE Transactions on Neural Networks (2005)

-Co­reviewed article submitted for publication.

• Improving CBIR Accuracy through Semi­Supervised Learning (2007)

-Principle Investigators: Sally Goldman

-Proposal, National Science Foundation (recommended for funding)

• Knowledge­Based Image Segmentation through Machine Learning (2007)

-Principle Investigators: Sally Goldman, Jason Fritts

-Proposal, National Science Foundation (recommended for funding)

• Applying Multiple­Instance Learning to Content­Based Image Retrieval (2005)

-Principle Investigator: Sally Goldman

-Annual Report 0329241, National Science Foundation

•  Technical Writing in English, School of Electrical & Computer Engineering, (2008)
  – Master and Doctoral level course
  – Challenging course – the goal was to teach writing excellence in English to foreign language students.
  -Developed course material set and taught 3 hours/week
  -Received excellent reviews from students and colleagues
• Advanced Algorithms, Department of Computer Science,Washington University, St. Louis, Missouri (2006)
  – Graduate level course.
  – Prepared and taught weekly recitation section ­ 3 hours/week class time
  – Held weekly office hours and helped run grading sessions
  – Received high evaluation scores from students
• Engineering and Scientific Computing, Department of Computer Science, Washington University, St. Louis, Missouri(2007)
  -Conducted weekly MATLAB laboratory section – 1.5 hours/week.
  – Held weekly office hours and helped run grading sessions
• Beginning Persian I, Department of Near Eastern Languages,Washington University, St. Louis, Missouri (2005)
  – Prepared and taught cultural section on Persian culture and language ­ 1 hour/week class time
  – Received high evaluation scores from students

• Dean’s Honorary Scholarship
• E. & Goldie G. Millstone Scholarship
• Dean’s List
• Bausch and Lomb Award
• AP Scholar with Honors