Hello!

Hello! 👋

I am a Ph.D. student at the University of Cincinnati, working under the guidance of Prof. Anil Jegga and Prof. Ali A. Minai.

My doctoral research has focused on the study of graph neural networks (GNN) and their ability to handle complex networks, particularly those involving multimodal datasets. I have published several papers analyzing biomedical networks and modeling them via GNN.

During my PhD program, I also interned at Seagate where I investigated Transformers and convolutions for soft-sensing semiconductor data. This work led me to propose innovative approaches for addressing imbalanced time-series datasets.

Prior to pursuing academia, I had the opportunity to work as a founding team member in several innovative product startups in healthcare, advertising, and cloud storage industries. These experiences helped me gain valuable insights into building products from the ground up and raising capital to bring these ideas to fruition.

In the moments I wrest from the fabric of time, I enjoy thinking about startups, economics, and humans in space. For fun, I build things 👨🏼‍💻, lift weights 🏋🏻‍♂️, watch movies 🍿, play video games 🎮, read books 📚, and practice guitar 🎸.

Publications

  • Yella, Jaswanth, Chao Zhang, Sergei Petrov, Yu Huang, Xiaoye Qian, Ali A. Minai, and Sthitie Bom. “Soft-sensing conformer: A curriculum learning-based convolutional transformer.” In 2021 IEEE International Conference on Big Data (Big Data), pp. 1990-1998. IEEE, 2021.

  • Huang, Yu, Chao Zhang, Jaswanth Yella, Sergei Petrov, Xiaoye Qian, Yufei Tang, Xingquan Zhu, and Sthitie Bom. “Grassnet: Graph soft sensing neural networks.” In 2021 IEEE International Conference on Big Data (Big Data), pp. 746-756. IEEE, 2021.

  • Zhang, Chao, Jaswanth Yella, Yu Huang, Xiaoye Qian, Sergei Petrov, Andrey Rzhetsky, and Sthitie Bom. “Soft sensing transformer: hundreds of sensors are worth a single word.” In 2021 IEEE International Conference on Big Data (Big Data), pp. 1999-2008. IEEE, 2021.

  • Jaswanth K Yella, Anil G Jegga. MGATRx: Discovering Drug Repositioning Candidates Using Multi-view Graph. In Proceedings of BIOKDD’20: International Workshop on Data Mining for Bioinformatics. 2020.

  • Cheng, Yizong, Jaswanth K. Yella, and Anil G. Jegga. “Triangle-Based Tripartite Graph Clustering.” 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2020.

  • Yunguan Wang, Jaswanth K Yella, Sudhir Ghandikota, Tejaswini C Cherukuri, Satish K Madala, Anil G Jegga. Pan-transcriptome-based Candidate Therapeutic Discovery for Idiopathic Pulmonary Fibrosis. bioRxiv 2019.

  • Yunguan Wang, Jaswanth Yella, and Anil G Jegga. Transcriptomic data mining and repurposing for computational drug discovery. In Computational Methods for Drug Repurposing, pages 73–95. Humana Press, New York, NY, 2019.

  • Jaswanth Yella, Suryanarayana Yaddanapudi, Yunguan Wang, and Anil Jegga. Changing trends in computational drug repositioning. Pharmaceuticals, 11(2):57, 2018.

  • Y Wang, J Yella, SK Madala, and A Jegga. Prioritizing idiopathic pulmonary fibrosis candidate genes based on” guilt by association” analysis. In A68. MOLECULAR DETERMINANTS OF REMODELING IN LUNG FIBROSIS, pages A2228–A2228. American Thoracic Society, 2018.

Education

  • Ph.D in Computer Science, 2023
    University of Cincinnati
  • MS in Computer Science, 2018
    University of Cincinnati
  • B.Tech in Computer Science, 2013
    Jawaharlal Nehru Technological University

Contact me

Feel free to reach me at yellajk@mail.uc.edu