Shivam Agarwal

I am a graduate student at University of Illinois at Urbana-Champaign (UIUC) where I study CS and AI. Previously, I was an Engineer at Cisco and a research intern at IIIT-Delhi and Vanderbilt University. I obtained my bachelors degree in ECE from Manipal Institute of Technology, India.

I am especially passionate about machine learning, natural language processing, and graph-based deep learning. I have been fortunate to contribute to a wide range of research directions, including large language models, text mining, text representation learning, spatio-temporal information processing, reinforcement learning, quantitative finance, and computational social sciences. I would be happy to discuss any project idea at the intersection of the above areas; feel free to reach out if you are interested!

Email / Google Scholar / LinkedIn / Github / Semantic Scholar

Research

I'm interested in natural machine learning, and natural language processing. Recently, I have been working on making language AI more efficient and accessible. I am evaluating and improving large language models' reasoning capabilities, factuality, and trustworthiness.

	Scaling Diffusion Language Models via Adaptation From Autoregressive Models Shansan Gong, Shivam Agarwal, Yizhe Zhang, Jiacheng Ye, Lin Zheng, Mukai Li, Chenxin An, Peilin Zhao, Wei Bi, Jiawei Han, Hao Peng, Lingpeng Kong
	Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy SeongKu Kang, Shivam Agarwal, Bowen Jin, Dongha Lee, Hwanjo Yu, Jiawei Han Proceedings of the ACM on Web Conference 2024 (WWW 2024)
	DynaMiTE: Discovering Explosive Topic Evolutions with User Guidance Nishant Balepur, Shivam Agarwal, Karthik Ramanan, Diyi Yang, Jiawei Han Fingings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023)
	Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models Pengcheng Jiang, Shivam Agarwal, Bowen Jin, Xuan Wang, Jiawei Han Findings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023)
	Learning Through Interpolative Augmentation of Dynamic Curvature Spaces Parth Chhabra, Atula Tejaswi Neerkaje, Shivam Agarwal, Ramit Sawhney, Megh Thakkar, Preslav Nakov, Sudheer Chava The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023)
	HyperSteg: Hyperbolic Learning For Deep Steganography Shivam Agarwal, Ritesh Soun, Rahul Shivani, Vishnu Varanasi, Navroop Gill, Ramit Sawhney 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023)
	THINK: Temporal Hypergraph Hyperbolic Network Shivam Agarwal, Ramit Sawhney, Megh Thakkar, Preslav Nakov, Jiawei Han, Tyler Derr IEEE International Conference on Data Mining (ICDM 2022) [Slide]
	Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models Ramit Sawhney, Shivam Agarwal, Vivek Mittal, Paolo Rosso, Vikram Nanda, Sudheer Chava 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2022) [Code]
	Towards suicide ideation detection through online conversational context Ramit Sawhney, Shivam Agarwal, Atula Tejaswi Neerkaje, Nikolaos Aletras, Preslav Nakov, Lucie Flek The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022) [Code]
	HYPHEN: Hyperbolic Hawkes Attention For Text Streams Shivam Agarwal, Ramit Sawhney, Sanchit Ahuja, Ritesh Soun, Sudheer Chava 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) [Code]
	Orthogonal Multi-Manifold Enriching of Directed Networks Ramit Sawhney, Shivam Agarwal, Atula Tejaswi, Kapil Pathak The 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022) [Code]
	HypMix: Hyperbolic Interpolative Data Augmentation Ramit Sawhney, Megh Thakkar, Shivam Agarwal, Di Jin, Diyi Yang, Lucie Flek The 2021 Conference on Empirical Methods in Natural Language Processing (Proceedings of EMNLP 2021) [Code]
	Modeling Financial Uncertainty with Multivariate Temporal Entropy-based Curriculums Ramit Sawhney, Arnav Wadhwa, Vivek Mittal, Ayush Mangal, Shivam Agarwal, Rajiv Shah 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021) [Code]
	TEC: A Time Evolving Contextual Graph Model for Speaker State Analysis in Political Debates Ramit Sawhney, Shivam Agarwal*, Arnav Wadhwa, Rajiv Ratn Shah 30th International Joint Conference on Artificial Intelligence* (IJCAI 2021), [AR=13.9%] [Code]
	Hyperbolic Online Stream Modeling Ramit Sawhney, Shivam Agarwal*, Megh Thakkar, Arnav Wadhwa, Rajiv Ratn Shah The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval* (SIGIR 2021) [Code]
	Quantitative Day Trading From Natural Language Using Reinforcement Learning Ramit Sawhney, Arnav Wadhwa, Shivam Agarwal, Rajiv Ratn Shah 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics, (NAACL 2021) [Code]
	Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading Ramit Sawhney, Shivam Agarwal*, Arnav Wadhwa, Rajiv Ratn Shah 30th The Web Conference*, (WWW 2021) [Code]
	FAST: Financial news and tweet based Time Aware network for Stock Trading Ramit Sawhney, Arnav Wadhwa, Shivam Agarwal, Rajiv Ratn Shah European Chapter of the Association for Computational Linguistics, (EACL 2021), [AR=24%] [Code]
	Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach Ramit Sawhney, Shivam Agarwal*, Arnav Wadhwa, Tyler Derr, Rajiv Ratn Shah AAAI Conference on Artificial Intelligence*, (AAAI 2021), [AR=21%] [Code]
	GPolS: A Contextual Graph-Based Language Model for Analyzing Parliamentary Debates and Political Cohesion Ramit Sawhney, Arnav Wadhwa, Shivam Agarwal, Rajiv Ratn Shah International Conference on Computational Linguistics, (COLING 2020), [AR=21%] [Code] (Outstanding Paper Award)
	Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations Ramit Sawhney, Shivam Agarwal*, Arnav Wadhwa, Rajiv Ratn Shah Empirical Methods in Natural Language Processing*, (Proceedings of EMNLP 2020), [AR=24.6%] [Code]
	Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa, Rajiv Ratn Shah IEEE International Conference on Data Mining, (ICDM 2020), [AR=9.7%] [Code]

Services

Program Committee Member, WWW, 2021
Reviewer for WSDM, EMNLP, ACL, AISTATS, CIKM, NAACL, ASONAM

* Indicates Joint First Authors