I am a researcher at the Illumina Artificial Intelligence Laboratory, where I develop deep learning models to better understand the human genome. I completed my PhD in Computer Science at UC Berkeley with Prof. Nilah Ioannidis, where my research focused on using deep learning to understand and regulate gene expression. Before that, I pursued an MS in Machine Learning at Carnegie Mellon University, working with Prof. Leila Wehbe to understand how linguistic syntax is processed in the human brain using machine learning. I received my undergraduate degree in Computer Science from BITS Pilani, Hyderabad.

Selected Publications

• Aniketh Janardhan Reddy. Predicting and Regulating Gene Expression Using Sequence-Based Deep Learning Models. [Doctoral Thesis]

• Aniketh Janardhan Reddy^, Xinyang Geng^, Michael H. Herschl^, Sathvik Kolli, Aviral Kumar, Patrick D. Hsu, Sergey Levine, and Nilah M. Ioannidis. “Designing Cell-Type-Specific Promoter Sequences Using Conservative Model-Based Optimization.” Advances in Neural Information Processing Systems 38 (NeurIPS 2024). [Paper] [Code]

• Ruchir Rastogi^, Aniketh Janardhan Reddy^, Ryan Chung, and Nilah M. Ioannidis. “Fine-tuning sequence-to-expression models on personal genome and transcriptome data.” bioRxiv (2024): 2024-09. In review. [Preprint] [Code]

• Aniketh Janardhan Reddy^, Michael H. Herschl^, Sathvik Kolli, Amy X. Lu, Xinyang Geng, Aviral Kumar, Patrick D. Hsu, Sergey Levine, and Nilah M. Ioannidis. “Strategies for effectively modelling promoter-driven gene expression using transfer learning.” bioRxiv (2023): 2023-02. [Preprint] [Code]

• Aniketh Janardhan Reddy and Leila Wehbe. “Can fMRI reveal the representation of syntactic structure in the brain?” Advances in Neural Information Processing Systems 35 (NeurIPS 2021). [Paper] [Code]

^Equal contribution.