Krishna Garg

I am a Ph.D. candidate at the University of Illinois, Chicago , working under the supervision of Professor Cornelia Caragea . My research broadly focuses on applied natural language processing and deep learning. During the summer of 2024, I interned at Adobe Research in Bengaluru, where I worked in the GNN+LLM+NLP domain under the mentorship of Sambaran Bandyopadhyay.

I received B.E.(Hons.) in Computer Science from Birla Institute of Technology and Science, Pilani, where I was advised by Professor Virendra Singh Shekhawat. Additionally, I have gained industry experience of two years at Samsung Research Institute-Noida.

NEWS:

See you at EMNLP, 2024 (Miami, Florida)

I am on the job market. Please reach out if you are interested in my profile.

Sep 2024: Paper accepted in EMNLP 2024 (Findings)

May 2024: Joined Adobe Research, Bengaluru as PhD Research Intern

Jan 2024: Received offer from Adobe Research India for Research Internship during summers

Sep 2023: Passed Preliminary Examination and received PhD candidacy

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Publications
(*indicates equal contribution)

My research primarily focuses on advancing the downstream applications of Keyphrase Generation and Stance Detection. I am currently investigating innovative methods to integrate graph structures, such as knowledge graphs and citation networks encoded through Graph Neural Networks (GNNs), into Large Language Models (LLMs) to enhance performance in various NLP tasks. Additionally, I am deeply interested in exploring the explainability, robustness, and calibration of deep learning models to improve their reliability and interpretability.

Intent-based Summarization with Graph Prompt Learning
Krishna Garg, Sambaran Bandyopadhyay
Patent under submission

Stanceformer: Target-Aware Transformer for Stance Detection
Krishna Garg, Cornelia Caragea
EMNLP 2024 (Findings)
arXiv / code

A New Direction in Stance Detection: Target-Stance Extraction in the Wild
Krishna Garg*, Yingjie Li*, Cornelia Caragea
ACL 2023 (Oral Presentation)
arXiv / code

Data Augmentation for Low-Resource Keyphrase Generation
Krishna Garg, Jishnu Ray Chowdhury, Cornelia Caragea
ACL 2023 (Findings) (Spotlight)
arXiv / code

Keyphrase Generation Beyond the Boundaries of Title and Abstract
Krishna Garg, Jishnu Ray Chowdhury, Cornelia Caragea
EMNLP 2022 (Findings)
arXiv / code

Work Experience

	Adobe Research, Bengaluru, India PhD Research Intern Mentor: Sambaran Bandyopadhyay Topic: Intent-based Summarization with Graph Prompt Learning (GNN+LLM+NLP space) Patent under submission
	Samsung Research Institute, Noida, India AndroidOS Developer \| Corporate Assistant Engineer
	Central Public Works Department, Mussoorie, India Software Intern

Teaching Experience

Teaching Assistant
CS 341: Programming Language Design and Implementation, Fall 2024, UIC [HEAD TA]
CS 341: Programming Language Design and Implementation, Spring 2024, UIC
CS 341: Programming Language Design and Implementation, Fall 2023, UIC
CS 111: Programming Design I, Spring 2023, UIC
CS 251: Data Structures, Fall 2022, UIC
CS 480: Database Systems, Summers 2021, UIC
CS 362: Computer Design, Spring 2021, UIC
CS 341: Programming Language Design and Implementation, Spring 2020, UIC
CS 476: Programming Language Design, Fall 2019, UIC
CS 111: Program Design I, Legal and Public Policy Themes Section, Fall 2019, UIC
CS 341: Programming Language Design and Implementation, Fall 2018, UIC

Other Projects

[NLP]

Neural Machine Translation
NMT with RNN Models: (1) in Vanilla style, (2) with Sentencepiece, (3) using Pre-trained models from FairSeq
code

Disaster-Related Tweet Classification
BERT-based models for classification of tweets to facilitate disaster management
report / code

Travello
Extracting addresses from unstructured text (e.g.,restaurant blogs) using deep learning models like LSTM, BERT
report / code

Named Entity Recognition
PyTorch-based project to train a classifier to recognize entities like person, geographical entity, event, location, etc.
code

[Computer Vision & Machine Learning]

Visual Dialog: A Survey
Survey paper on recent advances in Visual Dialog task
report

Few Shot Learning
Ph.D. Qualifier report on Few-Shot Learning
report

optim-meta: Benchmarking meta-learning algorithms
Benchmarking optimization-based meta-learning algorithms
report / code

Hand Gesture Recognition
Using OpenCV2 library and deep learning-based methods
report / code

[Misc.]

Multi-path Routing Algorithm for Intra-domain Routing in Network Simulator-3
Bachelor Thesis with Prof. Virendra Singh Shekhawat at BITS Pilani

Achievements

Recipient of Peter and Deborah Wexler Graduate Scholarship ($5000), UIC
Recipient of GSC Travel Award ($500), UIC
Recipient of Merit Cum Need Scholarship (25% Fee Waiver), BITS Pilani
Ranked 6364/400k+, 5962/1.2m+, 13/135k+ in national entrance exams IIT-JEE, AIEEE, BITSAT

Invited Talks

2022 | DPI Research Scholars Workshop: Graduate School Prep and Planning
2023 | Keyphrase Generation: Redefining Data Science with NLP Applications | CS 418: Intro to Data Science

Service

Reviewer: ACL 2023, EMNLP 2023, NAACL 2024
Volunteer: ACL 2023, EMNLP 2022
Program Committee Member, EMNLP Industry Track 2023
Executive Committee Member, UIC Senate, 2023-24
Member, Committee on Budget, Planning, and Priorities, UIC, 2023-24
Representative of CS Dept in Graduate Student Council, UIC, 2022-23

Template taken from Jon Barron's website.