Tamjid Imtiaz

Tamjid Imtiaz

University of Pennsylvania

👤 About Me:

I am a fourth year PhD Candidate in Bioengineering at the University of Pennsylvania, advised by Dr. Kathryn A Davis, in the Center for Neuroengineering and Therapeutics. With a background in Electrical & Electronics Engineering and Throughout my PhD, I developed substantial expertise in handling large-scale neuroimaging datasets, performing advanced statistical analyses, and applying machine and deep learning methods to study cognitive network in the epileptic brain.

⚠️ Looking for Internship Opportunities

With a background at the intersection of Electrical Engineering and Bioengineering, I enjoy tackling multidisciplinary challenges. I am seeking internship opportunities in Data Science and AI/ML—particularly those focused on biomedical applications—for Summer 2026.

🗣️ Research Interest

My research interest includes Biomedical Signal Processing and Machine Learning. I have published several papers in top international Publishers including Nature, Cell Press, IEEE, Elsevier with total google scholar citations 500+.

📖 Educations

  • *2022.09 - 2027.01,(Exp), PhD Candidate in Bioengineering, University of Pennsylvania.
  • *2019.04 - 2022.07, MSc Electrical & Electronics Engineering, Bangladesh University of Engineering & Technology.
  • *2014.06 - 2018.10, BSc Electrical & Electronics Engineering, Bangladesh University of Engineering & Technology.

🔥 News

  • 2025.12:  🎉🎉 I presented my work titled “Language and Verbal Memory Network Alterations in Temporal Lobe Epilepsy” on American Epilepsy Society Annual Meeting 2025.
  • 2025.09:  🎉🎉 We released a large dataset comprising multimodal paired 3T and 7T MRI scans collected from patients with drug-resistant focal epilepsy along with intracranial EEG data.
  • 2024.12:  🎉🎉 I presented my work titled “High-field 7T Image Synthesis Using Generative Adversarial Network for Enhancing Epilepsy Diagnosis “ on American Epilepsy Society Annual Meeting 2024.
  • 2024.06:  🎉🎉 Our paper titled “Mapping the cellular biogeography of human bone marrow niches using single-cell transcriptomics and proteomic imaging” is published in Cell. Congratulations to the coauthors and collaborators.

📝 Publications

  • 2025.12: Imtiaz, T., Lucas, A., Cornblath, E., Josyula, M., Petillo, N., Zhou, D.J., Stein, J. M., Das, S., Davis, K. A., 2025. Epileptogenic Influences on Language Network Reorganization in Temporal Lobe Epilepsy: Insights from Task-Based fMRI. [Under review, Epilepsia]
  • 2025.10: Imtiaz, T., Lucas, A., Josyula, M., Petillo, N., Wagenaar, J., Stein, J. M., Das, S., Sinha, N., Davis, K. A., 2025. A multimodal epilepsy dataset of paired 3-Tesla and 7-Tesla MRI and intracranial EEG. [Under review, Scientific Data, Nature]
  • 2024.6: Bandyopadhyay, S., Duffy, M.P., Ahn, K.J., Sussman, J.H., Pang, M., Smith, D., Duncan, G., Zhang, I., Huang, J., Lin, Y., Xiong, B., Imtiaz, T., and Tan, K., 2024. Mapping the cellular biogeography of human bone marrow niches using single-cell transcriptomics and proteomic imaging. Cell, 187(12), pp.3120-3140.
  • 2023.10: Imtiaz, T., Fattah, S.A. and Saquib, M., 2023. ConDANet: Contourlet driven attention network for automatic nuclei segmentation in histopathology images. IEEE Access, 11, pp.129321-129330.
  • 2023.10: Imtiaz, T., Fattah, S.A. and Kung, S.Y., 2023. BAWGNet: Boundary aware wavelet guided network for the nuclei segmentation in histopathology images. Computers in Biology and Medicine, 165, p.107378.
  • 2023.08: Jain, S., Pei, L., Spraggins, J.M., Angelo, M., Carson, J.P., Gehlenborg, N., Ginty, F., Gonçalves, J.P., Hagood, J.S., Hickey, J.W. and Kelleher, N.L., 2023. Advances and prospects for the human BioMolecular atlas Program (HuBMAP). Nature cell biology, 25(8), pp.1089-1100.
  • 2023.01: Imtiaz, T., Doumani, J., Tay, F., Komatsu, N., Marcon, S., Nakamura, M., Ghosh, S., Baydin, A., Kono, J. and Zubair, A., 2023. Facile alignment estimation in carbon nanotube films using image processing. Signal Processing, 202, p.108751.
  • 2021.08: Saif, A.F.M., Imtiaz, T., Rifat, S., Shahnaz, C., Zhu, W.P. and Ahmad, M.O., 2021. CapsCovNet: A modified capsule network to diagnose Covid-19 from multimodal medical imaging. IEEE Transactions on Artificial Intelligence, 2(6), pp.608-617.
  • 2021.08: Saif, A.F.M., Imtiaz, T., Shahnaz, C., Zhu, W.P. and Ahmad, M.O., 2021. Exploiting cascaded ensemble of features for the detection of tuberculosis using chest radiographs. IEEE Access, 9, pp.112388-112399.
  • 2019.12: Imtiaz, T., Rifat, S., Fattah, S.A. and Wahid, K.A., 2019. Automated brain tumor segmentation based on multi-planar superpixel level features extracted from 3D MR images. IEEE Access, 8, pp.25335-25349.
  • 2019.12: Imtiaz, T., Rifat, S. and Fattah, S.A., 2019, November. Automated brain tumor segmentation from MRI data based on local region analysis. In 2019 IEEE International Conference on Biomedical Engineering, Computer and Information Technology for Health (BECITHCON) (pp. 107-110). IEEE.

💬 Presentations

  • 2025.12, Presented in American Epilepsy Society Annual Meeting 2025, Title: _Language and Verbal Memory Network Alterations in Temporal Lobe Epilepsy _
  • 2024.12, Presented in American Epilepsy Society Annual Meeting 2024, Title: High-field 7T Image Synthesis Using Generative Adversarial Network for Enhancing Epilepsy Diagnosis
  • 2019.11, Presented in 2019 IEEE International Conference on Biomedical Engineering, Computer and Information Technology for Health (BECITHCON), Title: Automated Brain Tumor Segmentation from MRI Data Based on Local Region Analysis