Talks
Startup
Publication
Media
Lab
For the complete list of Kalyan’s research publications and the theses he has advised, visit the MIT Data-to-AI Lab’s Publications page.
Scientific Publications
2022
AER: Auto-Encoder with Regression for Time Series Anomaly Detection
Lawrence Wong, Dongyu Liu, Laure Berti-Equille, Sarah Alnegheimish, Kalyan Veeramachaneni
BigData-2022. In Proceedings of IEEE International Conference on Big Data, December 2022.
R&R: Metric-guided Adversarial Sentence Generation
Lei Xu, Alfredo Cuesta-Infante, Laure Berti-Equille, Kalyan Veeramachaneni
AACL-2022. In Findings of the Association for Computational Linguistics: AACL-IJCNLP , November 2022.
AutoML to Date and Beyond: Challenges and Opportunities
Shubhra Kanti Karmaker Santu, Md. Mahadi Hassan, Micah J. Smith, Lei Xu, ChengXiang Zhai, Kalyan Veeramachaneni
CSUR-2022. In ACM Computing Surveys, November 2022.
MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series
Dongyu Liu, Sarah Alnegheimish, Alexandra Zytek, Kalyan Veeramachaneni
CSCW-2022. In Proceedings of the ACM Conference On Computer-Supported Cooperative Work And Social Computing, October 2022.
In Situ Augmentation for Defending Against Adversarial Attacks on Text Classifiers
Lei Xu, Laure Berti-Equille, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
ICONIP-2022. In Proceedings of the International Conference on Neural Information Processing, November 2022.
AdvML-2022. In KDD Workshop on Adversarial Learning Methods for Machine Learning and Data Mining, August 2022.
The Need for Interpretable Features: Motivation and Taxonomy
Alexandra Zytek, Ignacio Arnaldo, Dongyu Liu, Laure Berti-Equille, Kalyan Veeramachaneni
KDD Explorations. June 2022.
Sintel: A Machine Learning Framework to Extract Insights from Signals
Sarah Alnegheimish, Dongyu Liu, Carles Sala, Laure Berti-Equille, Kalyan Veeramachaneni
SIGMOD-2022. In Proceedings of International Conference on Management of Data, June 2022.
[code]
2021
Sibyl: Understanding and Addressing the Usability Challenges of Machine Learning In High-Stakes Decision Making
Alexandra Zytek, Dongyu Liu, Rhema Vaithianathan, Kalyan Veeramachaneni
VIS-2021. In IEEE Transactions on Visualization and Computer Graphics (TVCG), January 2022.
VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models **Honorable Mention Award**
Furui Cheng, Dongyu Liu, Fan Du, Yanna Lin, Alexandra Zytek, Haomin Li, Huamin Qu, Kalyan Veeramachaneni
VIS-2021. In IEEE Transactions on Visualization and Computer Graphics (TVCG), January 2022.
Enabling Collaborative Data Science Development with the Ballet Framework
Micah J. Smith, Jürgen Cito, Kelvin Lu, Kalyan Veeramachaneni
CSCW-2021. In Proceedings of the ACM Conference on Computer-Supported Cooperative Work and Social Computing, October 2021.
Towards Reducing Biases in Combining Multiple Experts Online
Yi Sun, Ivan Ramirez, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
IJCAI-2021. In Proceedings of the International Joint Conference on Artificial Intelligence, August 2021.
Sibyl: Explaining Machine Learning Models for High-Stakes Decision Making
Alexandra Zytek, Dongyu Liu, Rhema Vaithianathan, Kalyan Veeramachaneni
CHI-2021. In Extended Abstracts of ACM CHI Conference on Human Factors in Computing Systems , May 2021.
Meeting in the notebook: a notebook-based environment for micro-submissions in data science collaborations
Micah J. Smith, Jürgen Cito, Kalyan Veeramachaneni
Preprint. March 2021.
For the complete list of Kalyan’s research publications and the theses he has advised, visit the MIT Data-to-AI Lab’s Publications page.