Shashank Srivastava
I will be an Assistant Professor of Computer Science at UNC Chapel Hill starting 2019-20.
I am looking for motivated PhD students at the intersection of Natural Language Processing and Machine Learning.
Email: shsriva@gmail.com
I do research on natural language processing, with special interests in grounding language in perception, semantic parsing, neuro-symbolic methods, and interactive machine learning.
Currently, I am an AI Resident at Microsoft Research in Redmond. Till 2018, I was a graduate student in the Machine Learning Department at CMU. My dissertation research with Tom Mitchell focused on teaching machines new tasks through natural language supervision; and is a thrust towards a new direction of Conversational Machine Learning. I co-organized the first workshop on Learning by Instruction at NeurIPS 2018.
Previously, I worked on models of computational semantics with Ed Hovy and emergence of compositional language in artificial agents with Harish Karnick.
I am generally interested in machine intelligence, language, AI and story-telling.
I graduated from Indian Institute of Technology, Kanpur. Once upon a time, I did bad things with other people's money at Tower Research Capital.
Selected Publications:
- Learning to Ask for Conversational Machine Learning
S Srivastava, I Labutov, T Mitchell
EMNLP 2019
- An Agent for Learning New Natural Language Commands
A Azaria, S Srivastava, J Krishnamurthy, I Labutov, T Mitchell
JAAMAS 2019
- Teaching Machines to Classify from Natural Language Interactions
S Srivastava
PhD Thesis, CMU 2018
- A Spatial Model for Extracting and Visualizing Latent Discourse Structure in Text
S Srivastava, N Jojic
ACL 2018
- Zero-shot Learning of Classifiers from Natural Language Quantification
S Srivastava, I Labutov, T Mitchell
ACL 2018
- LIA: A Natural Language Programmable Personal Assistant
I Labutov, S Srivastava, T Mitchell
EMNLP 2018 (System Demos)
- Where have I heard this story before? : Identifying Narrative Similarity in Movie Remakes'
S Chaturvedi, S Srivastava, D Roth
NAACL 2018 (short)
- Learning Classifiers from Declarative Language
S Srivastava, I Labutov, T Mitchell
NIPS Workshop on Learning from Limited Data 2017
- Joint Concept Learning and Semantic Parsing from Natural Language Explanations
S Srivastava, I Labutov, T Mitchell
EMNLP 2017
- Parsing Natural Language Conversations with Contextual Cues
S Srivastava, A Azaria, T Mitchell
IJCAI 2017
- Inferring Interpersonal Relations in Narrative Summaries
S Srivastava, S Chaturvedi, T Mitchell
AAAI 2016
- Modeling Evolving Relationships Between Characters in Literary Novels
S Chaturvedi, S Srivastava, H Daume, C Dyer
AAAI 2016
- CMU-ML System for KBP Cold Start Slot Filling
B Kisiel, B McDowell, M Gardner, N Nakashole, E Platanios, A Saparov, S Srivastava, D Wijaya, T Mitchell
TAC 2015
- Vector-space semantics with frequency driven motifs
S Srivastava, E Hovy
ACL 2014
- Spatial Compactness meets Topical Consistency: Jointly modeling link and content for community detection
M Sachan, A Dubey, S Srivastava, EP Xing, E Hovy
WSDM 2014
- A Semantically Enriched Tree Kernel Over Distributed Word Representations
S Srivastava, D Hovy, E Hovy
EMNLP 2013 (short)
- A Structured Distributional Semantic Model for Event Co-reference
K Goyal*, S Jauhar*, H Li*, M Sachan*, S Srivastava*, E Hovy
ACL 2013 (short)
(* equally contributing)
- Identifying Metaphorical Word Use with Tree Kernels
D Hovy, S Srivastava, S Jauhar, M Sachan, K Goyal, H Li, E Hovy
NAACL-HLT Meta4NLP Workshop 2013
- A Structured Distributional Semantic Model : Integrating Structure with Semantics
K Goyal, S Jauhar, S Srivastava, M Sachan, H Li, E Hovy
Workshop on Continuous Vector Space Models and their Compositionality, ACL 2013
- A Topical graph-kernel for Link Prediction in Labeled Graphs
S Chaturvedi, H Daume III, T Moon, S Srivastava
ICML Workshop on Mining and Learning with Graphs (MLG) 2012
- Evolution of Compositional Languages in Multiple Agent Social Communities
S Srivastava
MTech Thesis, IIT Kanpur, Sep 2010