Rohit Agarwal

I am Rohit Agarwal, a 4th-Year Ph.D. student at the Department of Computer Science, UiT Tromsø, Norway. I work on building scalable AI architectures for complex biological systems. I work in the Bio-AI and 3DNanoscopy Lab under the supervision of Dilip K. Prasad, Alexander Horsch and Krishna Agarwal.

I am interested in making dynamic deep learning models where the number of inputs to a model keeps changing with streaming data. I call them Haphazard Inputs. Along with these, I have experience in computer vision and natural language processing. Recently, I am also exploring large language models (LLMs) with a focus on continual learning and quantization.

Selected Publications

Haphazard Inputs

Haphazard Inputs as Images in Online Learning

Rohit Agarwal, Aryan Dessai, Arif Ahmed Sekh , and 3 more authors

In International Joint Conference on Neural Networks , 2025

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Book

Cloud Computing for Everyone

Rohit Agarwal, and Dilip K Prasad

2025

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Haphazard Inputs

packetLSTM: Dynamic LSTM Framework for Streaming Data with Varying Feature Space

Rohit Agarwal, Karaka Prasanth Naidu, Alexander Horsch , and 2 more authors

arXiv preprint arXiv:2410.17394, 2024

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@article{agarwal2024packetlstm,
  title = {packetLSTM: Dynamic LSTM Framework for Streaming Data with Varying Feature Space},
  author = {Agarwal, Rohit and Naidu, Karaka Prasanth and Horsch, Alexander and Agarwal, Krishna and Prasad, Dilip K},
  journal = {arXiv preprint arXiv:2410.17394},
  year = {2024},
  doi = {10.48550/arXiv.2410.17394},
}

Haphazard Inputs

Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts

Rohit Agarwal, Deepak Gupta, Alexander Horsch , and 1 more author

Transactions on Machine Learning Research, 2023

Reproducibility Certification

Bib HTML PDF Code

@article{agarwal2023auxdrop,
  title = {Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts},
  author = {Agarwal, Rohit and Gupta, Deepak and Horsch, Alexander and Prasad, Dilip K.},
  journal = {Transactions on Machine Learning Research},
  issn = {2835-8856},
  year = {2023},
  url = {https://openreview.net/forum?id=R9CgBkeZ6Z},
  note = {Reproducibility Certification},
}