Seminar Spring 2024

• Theme: AI and IoT for Medicine (AIM)
• Instructor: Prof. Chenyang Lu
• Semester: Fall 2023
• Time: Wednesday at 11am-12pm
• Location: McKelvey 1030
• Guidelines:
• Recommended sources: NeurIPS ([1]), ICML ([2]), AAAI ([3]), SIGKDD ([4]), IJCAI ([5]), IMWUT ([6]), HEALTH ([7]), Digital Medicine ([8]), Lancet Digital Health ([9]), SenSys, MobiSys, MobiCom

Presentation Schedule

---Sep 06 ---

Hangyue

Letzgus, Simon, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, and Gregoire Montavon. "Toward explainable artificial intelligence for regression models: A methodological perspective." IEEE Signal Processing Magazine 39, no. 4 (2022): 40-58. [10]

---Sep 13 ---

Ruiqi

Gupta, Akshita, Sanath Narayan, K. J. Joseph, Salman Khan, Fahad Shahbaz Khan, and Mubarak Shah. "Ow-detr: Open-world detection transformer." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 9235-9244. 2022. [11]

---Sep 20 ---

Jingwen

Dissertation Proposal Practice Talk

---Sep 27 ---

Bing

Li, Xiang Lisa, and Percy Liang. "Prefix-tuning: Optimizing continuous prompts for generation." arXiv preprint arXiv:2101.00190 (2021). [12]

---Oct 04 ---

Ziqi

Li, Y., Hu, P., Liu, Z., Peng, D., Zhou, J. T., & Peng, X. "Contrastive Clustering." Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 10, 2021, pp. 8547-8555. [13]

---Oct 11 ---

Ben

Mao, H., Liu, H., Dou, J. X., & Benos, P. V. (2022, November). Towards cross-modal causal structure and representation learning. In Machine Learning for Health (pp. 120-140). PMLR. [14]

---Oct 18 ---

Cancelled

---Oct 25 ---

Daoyi

Ravindra, N. G., Espinosa, C., Berson, E., Phongpreecha, T., Zhao, P., Becker, M., ... & Aghaeepour, N. (2023). Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity. NPJ Digital Medicine, 6(1), 171. [15]

---Nov 01 ---

Charles

Liu, H., Tam, D., Muqeeth, M., Mohta, J., Huang, T., Bansal, M., & Raffel, C. A. (2022). Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning. Advances in Neural Information Processing Systems, 35, 1950-1965. [16]

Hu, E. J. . yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. (2022) LoRA: Low-rank adaptation of large language models. In International Conference on Learning Representations (Vol. 3, p. 7). https://arxiv.org/pdf/2106.09685.pdf

---Nov 08 ---

Jiaming

Ghosh, Anurag, et al. "REACT: Streaming Video Analytics On The Edge With Asynchronous Cloud Support." Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation. 2023. [17]

---Nov 15 ---

Claire

Brathwaite, R., Ssewamala, F. M., Neilands, T. B., Okumu, M., Mutumba, M., Damulira, C., ... & McKay, M. M. (2021). Predicting the individualized risk of poor adherence to ART medication among adolescents living with HIV in Uganda: the Suubi+ Adherence study. African Journal of Reproduction and Gynaecological Endoscopy, 24(6), e25756. [18]

---Nov 22 ---

Thanksgiving Break

---Nov 29 ---

Mingzhen

Acevedo, Andrea, Anna Merino, Laura Boldú, Angel Molina, Santiago Alférez, and José Rodellar. "A new convolutional neural network predictive model for the automatic recognition of hypogranulated neutrophils in myelodysplastic syndromes." Computers in Biology and Medicine 134 (2021): 104479. [19]

Lewis, Joshua E., Conrad W. Shebelut, Bradley R. Drumheller, Xuebao Zhang, Nithya Shanmugam, Michel Attieh, Michael C. Horwath et al. "An automated pipeline for differential cell counts on whole-slide bone marrow aspirate smears." Modern Pathology 36, no. 2 (2023): 100003. [20]