Joint Post Baccalaureate Fellow, Harvard University
Northwest Building, 147
52 Oxford Street
Cambridge, Massachusetts 02138
Hi there! My name is Mithunjha Anandakumar. I am a joint post baccalaureate research fellow at Faculty of Arts and Sciences, Harvard University. Currently my research work involves developing deep learning algorithms to reconstruct microscopic images with Dr. Dushan Wadduwage, Wadduwage Lab, Harvard University and protein structure generation with of Dr. Sergey Ovchinnikov, SO lab, Harvard University.
I received my bachelor’s degree in Biomedical engineering from Department of Electronic and Telecommication, University of Moratuwa, Sri Lanka in 2022. I completed my thesis on “Interpretable multi-modal sleep monitoring system using Ear EEG and EOG” with Dr. Anjula De Silva, University of Moratuwa, Dr. Chamira Edussooriya, University of Moratuwa and Dr. Simon Lind Kappel, Aarhus University. I gained industry experience working as a trainee biomedical research engineer at Zone24x7, developing biosignal processing algorithms to extract Breathing Rate (BR) from ECG and PPG.
I am aspired to work towards developing cutting-edge machine learning methods for advancing medicine and healthcare. I have keen interest on Computer Vision, Deep Learning, Medical Imaging, and Biosignal Processing.
|Oct 27, 2022||Our preprint titled “A Knowledge Distillation Framework For Enhancing Ear-EEG Based Sleep Staging With Scalp-EEG Data” released.|
|Oct 21, 2022||Our preprint titled “DEEP^2: Deep Learning Powered De-scattering with Excitation Patterning” released.|
|Sep 14, 2022||Presented my final year thesis project to the Center for Ear EEG at Aarhus University, Denmark.|
|Aug 23, 2022||Served as an invited reviewer at ECCV 2022: L2ID Workshop.|
|Aug 14, 2022||Our preprint titled “Towards Interpretable Sleep Stage Classification Using Cross-Modal Transformers” released.|
- A Knowledge Distillation Framework For Enhancing Ear-EEG Based Sleep Staging With Scalp-EEG DataarXiv preprint arXiv:2211.02638 2022
- Towards Interpretable Sleep Stage Classification Using Cross-Modal TransformersarXiv preprint arXiv:2208.06991 2022
- DEEP^2: Deep Learning Powered De-scattering with Excitation PatterningarXiv preprint arXiv:2210.10892 2022
- Physics Augmented U-Net: A High-Frequency Aware Generative Prior for MicroscopybioRxiv 2021
- Decoding of Hand Gestures from Electrocorticography with LSTM Based Deep Neural Network2021