Publications

A selected list of my publications that are relevant to my current research interests can be found here. A more comprehensive list including papers from my undergraduate days can be found on my google scholar profile.

*indicates co-first authorship.

Preprints

  • Sumit Mukherjee, et al. "A machine learning pipeline for aiding school identification from child trafficking images." Submitted to ACM GoodIT [Arxiv].

  • M. Pereira*, M. Kshirsagar*, S. Mukherjee*, R. Dodhia, J.L. Ferres, "An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises", Submitted to ICML workshop on on Machine Learning for Data: Automated Creation, Privacy, Bias [Arxiv].

  • J-F. Rajotte, S. Mukherjee, et. al. "Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary", Submitted to ACM GoodIT [Arxiv]

  • X. Liu, Y. Xu, S. Tople, J.L. Ferres*, S. Mukherjee*. "MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models". Submitted to USENIX 20221 [Arxiv]. *co-senior author

  • Y. Zhang, S. Mao, S. Mukherjee, S. Kannan, G. Seelig, 'UNCURL-App: Interactive Database-Driven Analysis of scRNA-Seq Data'. Under major revision at OUP Bioinformatics [Biorxiv].

Journals

  • B. E. Dixon, S. Mukherjee, et. al. " Capturing COVID-19 Symptoms At-Scale using Banner Ads: A Novel Survey Methodology Pilot using an Online News Platform". JMIR [Preprint].

  • S. Mukherjee, Y. Xu, A. Trivedi, J. L. Ferres, 'privGAN: Protecting GANs from membership inference attacks at low cost'. Accepted at PETS [Arxiv].

  • S. Mukherjee, C. Preuss, G. Carter, L. Mangravite, B. Logsdon. "Molecular estimation of neurodegeneration pseudotime in older brains". Accepted to Nature communications [BioRxiv].

  • B. Logsdon, ..., S. Mukherjee, .. L. Mangravite. "Meta-analysis of the Alzheimer’s disease human brain transcriptome and functional dissection in mouse models ". Cell Reports. [Biorxiv].

  • S. Mukherjee, T. Perumal, K. Daily, S. Sieberts, C. Preuss, G. Carter, L. Mangravite, B. Logsdon. "Ranking driver genes of Alzheimer's Disease using multi-view evidence aggregation". Bioinformatics, Volume 35, Issue 14, July 2019, Pages i568–i576 [BioRxiv].

  • A. Rosenberg, ..., S. Mukherjee, ..., G. Seelig. "Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding". Science 360, no. 6385 (2018): 176-182. [Biorxiv]

  • S. Mukherjee*, Y. Zhang*, J. Fan, G. Seelig, and S. Kannan. "Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge." Bioinformatics 34, no. 13 (2018): i124-i132. [Pdf]

  • Bolten, N., S. Mukherjee, V. Sipeeva, A. Tanweer, and A. Caspi. "A pedestrian-centered data approach for equitable access to urban infrastructure environments." IBM Journal of Research and Development 61, no. 6 (2017): 10-1. [Pdf]

Conference and workshop proceedings

  • M. Kshirsagar, ..., S. Mukherjee, ..., J.L. Ferres. "Becoming AI for Good". Accepted at AAAI/ACM AIES-21. [Arxiv]

  • S. Mukherjee, N. Becker, B. Weeks, J.L. Ferres "Using internet search trends to forecast short term drug overdose deaths: A case study on Connecticut". Accepted at ICMLA 2020 [Pdf]

  • S. Mukherjee*, A. Trivedi*, E. Tse*. 'Risks of Using Non-verified Open Data: A case study on using Machine Learning techniques for predicting Pregnancy Outcomes in India'. Accepted to NeurIPS workshop on ML for Developing World (2019 )[Arxiv].

  • S. Mukherjee, T. Perumal, K. Daily, S. Sieberts, C. Preuss, G. Carter, L. Mangravite, B. Logsdon. "Ranking driver genes of Alzheimer's Disease using multi-view evidence aggregation". To appear in Bioinformatics (ISMB/ECCB 2019 issue) [BioRxiv].

  • A. Carignano*, S. Mukherjee*, A. Singh, and G. Seelig. "Extrinsic Noise Suppression in Micro RNA Mediated Incoherent Feedforward Loops." Accepted to IEEE CDC (2018). [Biorxiv]

  • S. Mukherjee, A. Carignano, G. Seelig, and S.I. Lee. "Identifying progressive gene network perturbation from single-cell RNA-seq data." In transactions of IEEE EMBC (2018) (Oral presentation). [Biorxiv]

  • S. Mukherjee*, Y. Zhang*, J. Fan, G. Seelig, and S. Kannan. "Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge." ISMB (2018). [Pdf]

  • J. T. Wen., S. Mishra, S. Mukherjee, N. Tantisujjatham, and M. Minakais. "Building temperature control with adaptive feedforward." In Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on, pp. 4827-4832. IEEE, 2013. [Pdf]

  • S. Mukherjee, S. Mishra, J. T. Wen. "Building temperature control: A passivity-based approach." In Decision and Control (CDC), 2012 IEEE 51st Annual Conference on, pp. 6902-6907. IEEE, 2012. [Pdf]

Published conference abstracts

  • S. Mukherjee, C. Preuss, A. Greenwood, S. Jayadev, G. Garden, G. Carter, L. Mangravite, and B. Logsdon. "MOLECULAR ESTIMATION OF ALZHEIMER’S DISEASE PROGRESSION." Alzheimer's & Dementia: The Journal of the Alzheimer's Association 15, no. 7 (2019): P1321-P1322. [Link]

  • A. Greenwood, K. Daily, S. Mukherjee, T. M. Perumal, K. H. Woo, S. K. Sieberts, S. Simon et al. "AGORA: A PLATFORM FOR THE DEMOCRATIZATION OF ALZHEIMER’S DISEASE TARGET EVIDENCE." Alzheimer's & Dementia: The Journal of the Alzheimer's Association 15, no. 7 (2019): P1319. [Link]

  • B. Logsdon, A. K. Greenwood, K. Daily, Z. Leanza, K. H. Woo, C. Suver, K. Montgomery et al. "COMMUNITY-POWERED, RADICALLY OPEN TECHNOLOGIES TO ACCELERATE ALZHEIMER’S DISEASE THERAPEUTIC DISCOVERY." Alzheimer's & Dementia: The Journal of the Alzheimer's Association 15, no. 7 (2019): P1322. [Link]