Mostafa Karimi Data and Applied Scientist 2 Microsoft Corporation contact Redmond,WA 98052 Email: mkarimi@microsoft.com Phone: +1-979-224-5153

About Me

I am currently a data and applied scientist 2 in Microsoft. I interned at Ancestry.com and Anadarko Petroleum as a data scientist in summer of 2019 and 2018. I graduated with a Ph.D. degree at Texas A&M University (TAMU) in Electrical Engineering under the supervision of Professor Yang Shen in 2020. I worked as a graduate research assistant affiliated with the Genomic Signal Processing Laboratory and the Center for Bioinformatics and Genomic Systems Engineering. My research lied at the intersection of Combinatorial Optimization and Machine Learning with applications in Molecular Biology and Genetics. Before joining TAMU, I received a B.S. in Electrical Engineering and a B.S. in Computer Science from Sharif University of Technology (SUT) in 2015. At SUT, I was a member of Advanced Communications Research Institute under the supervision of Professor Farokh Marvasti for three years.

News

2021

• “Adversarial network for transforming handwritten text” submitted as US/WO patent pending.

• “Crowdsourced mapping of unexplored target space of kinase inhibitors” published in Nature Communications.

• Recipient of the Association of Former students Distinguished Graduate Student Award for Excellence in Research-Doctoral, Texas A&M University. (news1, news2)

2020

• Joined Microsoft as a Data and applied scientist 2 in Speech Research Team.

• Our paper “De Novo Protein Design for Novel Folds Using Guided Conditional Wasserstein Generative Adversarial Networks”, featured as cover of Journal of Chemical Information and Modeling.

• “Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts”, published in Journal of Chemical Information and Modeling

• “De Novo Protein Design for Novel Folds Using Guided Conditional Wasserstein Generative Adversarial Networks”, published in Journal of Chemical Information and Modeling

• “Directionally Dependent Multi-View Clustering Using Copula Model”, published in Plos One

• “Illegible Text to Readable Text: An Image-to-Image Transformation using Conditional Sliced Wasserstein Adversarial Networks”, accepted in CVPR workshop 2020.

• “Network-principled deep generative models for designing drug combinations as graph sets”, accepted in ISMB and published in Bioinformatics

2019

• Recieved NIH-funded travel fellowship to attend CAGI* workshop in San Francisco for presenting iCFN and its application in protein modeling.

• Joined Ancestry.com as a Data Scientist intern.

• Our paper “Genomic and Molecular Landscape of DNA Damage Repair Deficiency Across The Cancer Genome Atlas” has been selected among best of 2018 Cell Reports (news)

• “Predicting Pathogenicity of Missense Variants with Weakly Supervised Regression” published in Human Mutation

• “Evaluating the predictions of the protein stability change upon single amino acid substitutions for the FXN CAGI5 challenge” published in Human Mutation

• “Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen” published in Nature Communications

• “Engineering a HER2-specific antibody-drug conjugate to increase lysosomal delivery and therapeutic efficacy” published in Nature Biotechnology (Highlighted in TAMU research bulletin, TAMU Engineering, and TAMU health science center)

• “DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks” published in Bioinformatics.

2018

• Joined Anadarko Petroleum Corporation as a Data Scientist intern.

• “Interconnected Cost Function Networks (iCFN): an exact algorithm for multistate protein design with substate ensembles” accepted in ECCB 2018 and published in Bioinformatics.

• “The SERM/SERD Bazedoxifene Disrupts ESR1 Helix 12 to Overcome Acquired Hormone Resistance in Breast Cancer Cells” published in eLife.

• “Genomic and Molecular Landscape of DNA Damage Repair Deficiency Across The Cancer Genome Atlas” published in Cell Reports.

2016

• “Multihypothesis Compressed Video Sensing Technique” published in IEEE TCSVT.

• Received a NSF award for young professionals contributing to smart and connected health & attending 2016 IEEE EMBS annual conference.