Welcome!

This is Karandeep Singh, currently working as a Postdoctoral Researcher at ATMOS, UCLA.

Previously, I worked as a senior machine learning researcher at IBS Data Science Group (기초과학연구원 데이터사이언스그룹).

As a data scientist and deep learning researcher, I am driven by the opportunity to use my expertise to tackle real-world challenges and deliver societal benefits. With a strong foundation in both practical and theoretical aspects of the field, I have a proven track record of leading multidisciplinary teams and successfully delivering on research projects with large and complex datasets.

My work has been published in top computer science venues like KDD, CIKM, TKDE etc., and the models I've developed are currently in practical use, undergoing testing in a live setting. I am excited about the opportunity to apply my expertise to address new challenges for societal benefits as well as in generating valuable business insights and optimizing processes.

I completed my Ph.D. at Electronics and Telecommunications Research Institute (ETRI), Korea, and MS at Panjab Engineering College, India.

Get in touch:

singhkarandeep(at)ucla.edu

karandeepbrar(at)gmail.com

Recent Updates

Started working as a postdoctoral researcher at ATMOS, UCLA, Nov. 2024
Paper accepted: Self Supervised Vision for Climate Downscaling, IJCAI May 2024
Paper submitted: Self Supervised Vision for Climate Downscaling, IJCAI Feb. 2024
Preprint now online: Self Supervised Vision for Climate Downscaling, https://arxiv.org/abs/2401.09466
Article submitted: Explaining Gender Wage Gaps: The Role of Gender-Stereotypical Communication During a Major Organizational Shock, Nature Human Behavior, Dec. 2023
Paper accepted: Generating High-Resolution Regional Precipitation Using Conditional Diffusion Model, KAIA Nov. 2023
Paper accepted: K. Singh, Y.-C. Tsai, C.-T. Li, M. Cha, and S. -D. Lin, “GraphFC: Customs Fraud Detection with Label Scarcity,” in 31st ACM International Conference on Information and Knowledge Management (CIKM2023), Jun. 2023
Paper accepted: N. Shidqi, C. Jeong, S. Park, K. Singh, A. B. Nellikkattil, E. Zeller, M. Cha, "Leveraging Temporal Information for Self-Supervised Climate Downscaling in North America Region", Korea Computer Congress (KCC), Jun. 2023.
Article published: Multi-Stage Learning Model for Hierarchical Tie Valence Prediction, ACM Transactions on Knowledge Discovery from Data (TKDD), Jan. 2023.
Paper accepted: Self-supervised Deep Learning for Climate Downscaling, IEEE International Conference on Big data and Smart Computing (BIGCOMP 2023) , Oct. 2022.
Article submitted: GraphFC: Graph Neural Networks for Customs Fraud Detection, IEEE Transactions on Knowledge and Data Engineering (TKDE), Jul. 2022.
Paper accepted: Downscaling the Earth System Modeling with Deep Learning, SIGKDD Conference on knowledge discovery and data mining (KDD 2022), Mar. 2022.
Paper accepted: Aiding the Earth System Models with Super Resolution Deep Learning, KSC 2021, Dec. 2021.
Journal article submitted: Exploring Text Summarization for Fake News Detection, Journal of KIISE, Aug. 2021 (Under minor revision)
Extended abstract accepted, "A Multi-Stage Learning Model for Predicting Tie Valence in Organizations", IC2S2 2021, Jul. 2021.
Delivered talk: Multi-Stage Learning Model for Tie Valence in Organizational Social Network, at Conference on Complex Systems - Machine learning Prospective for Complex Networks (CCS 2020), Dec. 2020.
North London Collegiate School Jeju Interview., Dec. 2020, https://tinyurl.com/omaj3yjp, (page 14-15).
Magazine Article: [Hatred in the corona era]- How did the infodemic, as scary as the pandemic, promote prejudice and hatred? in Donga Science Dec. 2020, https://tinyurl.com/1fyvl8fw.
Delivered talk: Insights Learnt from a Misinformation Study: COVID-19 Infodemic Attacks Vulnerable Nations the Most , at Conference for Truth and Trust Online (TTO 2020), Oct. 2020.
Delivered talk: COVID-19: Infodemic, Fact-Checks and Vaccination Tendencies, at IBS Seminar on Misinformation in times of a pandemic, Sep. 2020.
Arirang TV Interview., May 2020, https://tinyurl.com/bxrvjxm6.

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