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Dr Aditya Joshi

Dr Aditya Joshi

Lecturer
  • PhD, Indian Institute of Technology Bombay, India and Monash University, Australia (jointly awarded). Thesis title: 'Investigations in Computational Sarcasm' [Monograph]
  • MTech (Computer Science and Engineering), IIT Bombay. Dissertation title: 'Adaptation of Sentiment Analysis to a New Text Form'
Engineering
Computer Science and Engineering

I am a Lecturer (US/India Equivalent: Assistant Professor) in the School of Computer Science & Engineering at UNSW, specializing in natural language processing (NLP).

Research: As of April 2024, my papers have 2500+ citations (h-index: 23), and I have been the lead investigator in grants with a cumulative total of AUD150,000, including Google exploreCSR and Google Research scholar grants. My publications are in conferences such as ACL, EMNLP, COLING, and CONLL, and in journals such as ACM Computing Surveys and PLOS One. I have been acknowledged as an outstanding reviewer at ICML, ACL and EACL. I have presented tutorials at EMNLP, AACL, ALTA and ICON. My 2018 TEDx talk 'Detecting sarcasm, combating hate' interleaved my PhD thesis with my personal journey. I apply NLP to epidemic intelligence in my collaboration with EPIWATCH (Kirby Institute) and to cybersecurity with IFCYBER (School of CSE). I supervise undergraduate, Masters and PhD students on their research projects in NLP.

Teaching: I designed and introduced a new NLP course at UNSW in 2024. I have co-authored a textbook on NLP with Pushpak Bhattacharyya, published by Wiley in 2023.
I am an Associate of the Human Rights Institute at UNSW, and co-lead the Community of Practice for Inclusive Research with Queer, Trans & people with variations of sex characteristics. I was the organizing chair for 'Rainbow AI': a workshop to support queer students in Australia interested in HDR and research careers in AI. The workshop was funded by Google's exploreCSR grant.

Past Experience: I also have over five years of industry experience in applying NLP techniques to various domains, such as online employment marketplace, meeting analytics and epidemic intelligence. I obtained a joint PhD degree from IIT Bombay (India) and Monash University (Australia) in 2018, and a best PhD thesis award by IITB-Monash Research Academy. Before joining UNSW in 2023, I worked as a data scientist at SEEK, a market leader in online employment marketplaces, and as a machine learning engineer at Notiv, a startup that provides AI-powered meeting insights, and a senior data scientist at Fractal, a leader in analytics. In these roles, I developed and deployed recommender systems, land natural language understanding systems, using state-of-the-art tools and frameworks, such as Azure Databricks, Atlassian Suite, and PyTorch. I have also worked as a lead trainer at the Institute of Data, that offers data science certifications to industry professionals.

 
E-mail
aditya.joshi@unsw.edu.au
  • Journal articles | 2020
    Ghafari SM; Beheshti A; Joshi A; Paris C; Mahmood A; Yakhchi S; Orgun MA, 2020, 'A Survey on Trust Prediction in Online Social Networks', IEEE Access, 8, pp. 144292 - 144309, http://dx.doi.org/10.1109/ACCESS.2020.3009445
    Journal articles | 2020
    Joshi A; Sparks R; Karimi S; Yan SLJ; Chughtai AA; Paris C; Raina MacIntyre C; MacIntyre R, 2020, 'Automated monitoring of tweets for early detection of the 2014 Ebola epidemic', PLoS ONE, 15, pp. e0230322, http://dx.doi.org/10.1371/journal.pone.0230322
    Journal articles | 2020
    Joshi A; Sparks R; McHugh J; Karimi S; Paris C; MacIntyre CR, 2020, 'Harnessing Tweets for Early Detection of an Acute Disease Event', Epidemiology, 31, pp. 90 - 97, http://dx.doi.org/10.1097/EDE.0000000000001133
    Journal articles | 2020
    Sparks R; Joshi A; Paris C; Karimi S; MacIntyre CR, 2020, 'Monitoring events with application to syndromic surveillance using social media data', Engineering Reports, 2, http://dx.doi.org/10.1002/eng2.12152
    Journal articles | 2020
    Sparks R; Paris C; Joshi A; Xu C, 2020, 'Comments on the three-zone approach for social media monitoring', Quality Engineering, 32, pp. 1 - 3, http://dx.doi.org/10.1080/08982112.2019.1644522
    Journal articles | 2019
    Joshi A; Karim S; Sparks R; Paris C; MacIntyre R, 2019, 'Survey of Text-based Epidemic Intelligence: A Computational Linguistic Perspective', ACM Computing Surveys
    Journal articles | 2019
    Joshi A; Karimi S; Sparks R; Paris C; MacIntyre CR, 2019, 'A Comparison of Word-based and Context-based Representations for Classification Problems in Health Informatics', SIGBIOMED WORKSHOP ON BIOMEDICAL NATURAL LANGUAGE PROCESSING (BIONLP 2019), pp. 135 - 141, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000521946800015&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
  • Preprints | 2024
    Chan FL; Nguyen D; Joshi A, 2024, "Is Hate Lost in Translation?": Evaluation of Multilingual LGBTQIA+ Hate Speech Detection, http://arxiv.org/abs/2410.11230v2
    Preprints | 2024
    Joshi A; Dabre R; Kanojia D; Li Z; Zhan H; Haffari G; Dippold D, 2024, Natural Language Processing for Dialects of a Language: A Survey, http://arxiv.org/abs/2401.05632v3
    Preprints | 2024
    Joshi A; Kanojia D; Lent H; Kaing H; Song H, 2024, Connecting Ideas in 'Lower-Resource' Scenarios: NLP for National Varieties, Creoles and Other Low-resource Scenarios, http://arxiv.org/abs/2409.12683v1
    Preprints | 2024
    Joshi A; Renzella J; Bhattacharyya P; Jha S; Zhang X, 2024, Striking a Balance between Classical and Deep Learning Approaches in Natural Language Processing Pedagogy, http://arxiv.org/abs/2405.09854v2
    Preprints | 2024
    Nguyen D; Joshi A; Salim F, 2024, Spectraformer: A Unified Random Feature Framework for Transformer, http://arxiv.org/abs/2405.15310v3
    Preprints | 2024
    Shen Z; Joshi A; Chen R-C, 2024, BAMBINO-LM: (Bilingual-)Human-Inspired Continual Pretraining of BabyLM, http://arxiv.org/abs/2406.11418v2
    Preprints | 2024
    Srirag D; Joshi A; Eisenstein J, 2024, Predicting the Target Word of Game-playing Conversations using a Low-Rank Dialect Adapter for Decoder Models, http://arxiv.org/abs/2409.00358v1
    Preprints | 2024
    Srirag D; Painter J; Joshi A; Kanojia D, 2024, Sampling Strategies for Creation of a Benchmark for Dialectal Sentiment Classification, http://arxiv.org/abs/2410.11216v1
    Preprints | 2024
    Srirag D; Sahoo NR; Joshi A, 2024, Evaluating Dialect Robustness of Language Models via Conversation Understanding, http://arxiv.org/abs/2405.05688v2
    Preprints | 2024
    Vaidya A; Arora A; Joshi A; Prabhakar T, 2024, Overview of the 2023 ICON Shared Task on Gendered Abuse Detection in Indic Languages, , http://arxiv.org/abs/2401.03677v1
    Preprints | 2023
    Hong J; Dung D; Hutchinson D; Akhtar Z; Chen R; Dawson R; Joshi A; Lim S; MacIntyre CR; Gurdasani D, 2023, Relation Extraction from News Articles (RENA): A Tool for Epidemic Surveillance, http://arxiv.org/abs/2311.01472v1
    Preprints | 2023
    Joshi A; Rawat S; Dange A, 2023, Evaluation of large language models using an Indian language LGBTI+ lexicon, http://arxiv.org/abs/2310.17787v1
    Preprints | 2023
    Nguyen D; Naing KMN; Joshi A, 2023, Stacking the Odds: Transformer-Based Ensemble for AI-Generated Text Detection, http://arxiv.org/abs/2310.18906v1
    Conference Papers | 2023
    Queerinai OO; Ovalle A; Subramonian A; Singh A; Voelcker C; Sutherland DJ; Locatelli D; Breznik E; Klubicka F; Yuan H; Hetvi J; Zhang H; Shriram J; Lehman K; Soldaini L; Sap M; Deisenroth MP; Pacheco ML; Ryskina M; Mundt M; Agarwal M; Mclean N; Xu P; Pranav A; Korpan R; Ray R; Mathew S; Arora S; John S; Anand T; Agrawal V; Agnew W; Long Y; Wang ZJ; Talat Z; Ghosh A; Dennler N; Noseworthy M; Jha S; Baylor E; Joshi A; Bilenko NY; Mcnamara A; Gontijo-Lopes R; Markham A; Dong E; Kay J; Saraswat M; Vytla N; Stark L, 2023, 'Queer In AI: A Case Study in Community-Led Participatory AI', in ACM International Conference Proceeding Series, pp. 1882 - 1895, http://dx.doi.org/10.1145/3593013.3594134
    Conference Papers | 2020
    Biddle R; Joshi A; Liu S; Paris C; Xu G, 2020, 'Leveraging Sentiment Distributions to Distinguish Figurative from Literal Health Reports on Twitter', in The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020, pp. 1217 - 1227, http://dx.doi.org/10.1145/3366423.3380198
    Conference Abstracts | 2020
    Jin B; Joshi A; Sparks R; Wan S; Paris C; MacIntyre CR, 2020, ''Watch the flu': A tweet monitoring tool for epidemic intelligence of influenza in australia', in AAAI 2020 - 34th AAAI Conference on Artificial Intelligence, pp. 13616 - 13617
    Preprints | 2019
    Iyer A; Joshi A; Karimi S; Sparks R; Paris C, 2019, Figurative Usage Detection of Symptom Words to Improve Personal Health Mention Detection, http://arxiv.org/abs/1906.05466v2
    Conference Papers | 2019
    Joshi A; Karimi S; Sparks R; Paris C; MacIntyre CR, 2019, 'A comparison of word-based and context-based representations for classification problems in health informatics', in BioNLP 2019 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 18th BioNLP Workshop and Shared Task, pp. 135 - 141
    Preprints | 2019
    Joshi A; Karimi S; Sparks R; Paris C; MacIntyre CR, 2019, A Comparison of Word-based and Context-based Representations for Classification Problems in Health Informatics, http://dx.doi.org/10.48550/arxiv.1906.05468
    Preprints | 2019
    Joshi A; Karimi S; Sparks R; Paris C; MacIntyre CR, 2019, Survey of Text-based Epidemic Intelligence: A Computational Linguistic Perspective, http://arxiv.org/abs/1903.05801v1
    Conference Papers | 2018
    Joshi A; Dai X; Karimi S; Sparks R; Paris C; MacIntyre CR, 2018, 'Shot Or Not: Comparison of NLP Approaches for Vaccination Behaviour Detection', in Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task, Association for Computational Linguistics, pp. 43 - 47, presented at Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task, - , http://dx.doi.org/10.18653/v1/w18-5911
    Preprints | 2018
    Kamble S; Joshi A, 2018, Hate Speech Detection from Code-mixed Hindi-English Tweets Using Deep Learning Models, http://arxiv.org/abs/1811.05145v1
    Preprints | 2017
    Joshi A; Agrawal S; Bhattacharyya P; Carman M, 2017, Expect the unexpected: Harnessing Sentence Completion for Sarcasm Detection, http://arxiv.org/abs/1707.06151v1
    Preprints | 2016
    Joshi A; Bhattacharyya P; Carman MJ, 2016, Automatic Sarcasm Detection: A Survey, http://arxiv.org/abs/1602.03426v2
    Preprints | 2016
    Joshi A; Goel P; Bhattacharyya P; Carman M, 2016, Automatic Identification of Sarcasm Target: An Introductory Approach, http://arxiv.org/abs/1610.07091v2
    Preprints | 2016
    Joshi A; Jain P; Bhattacharyya P; Carman M, 2016, `Who would have thought of that!': A Hierarchical Topic Model for Extraction of Sarcasm-prevalent Topics and Sarcasm Detection, http://arxiv.org/abs/1611.04326v2
    Preprints | 2016
    Joshi A; Mishra A; Balamurali AR; Bhattacharyya P; Carman M, 2016, A Computational Approach to Automatic Prediction of Drunk Texting, http://arxiv.org/abs/1610.00879v1
    Preprints | 2016
    Joshi A; Tripathi V; Patel K; Bhattacharyya P; Carman M, 2016, Are Word Embedding-based Features Useful for Sarcasm Detection?, http://arxiv.org/abs/1610.00883v1

Topic Funding organisation Name of Funding program Co-PIs Amount
A benchmark for sentiment and sarcasm classification for dialects of English (Lead Investigator) Google Research Google exploreCSR Dr. Diptesh Kanojia (Uni of Surrey, UK) 92K AUD
Fake news detection in the context of national security policy (Lead Investigator) UNSW Global Global Research and Innovation Program (GRIP) Profs. Sanjay Jha, Salil Kanhere (UNSW) 20K AUD
LGBTI+ inclusion in AI (Lead Investigator) Google Research Google exploreCSR Dr. Ben Hutchinson (Google) 51K AUD

 

Publications:

  • Best PhD Thesis (2018) awarded by IITB-Monash Research Academy
  • Best Paper at ACM FAccT 2023 in June 2023. (Collaborative paper by multiple authors at Queer in AI)
  • Best Paper at MoMM 2020 in December 2020. (Lead author was a PhD student at Macquarie University, Sydney, who was co-supervised by me).
  • Best Student Paper - Runner Up at ALTA 2019 in December 2019. (Lead author was a PhD Student at RMIT, Melbourne.)
  • Best Paper from IITB-Monash Research Academy consecutively in 2015 and 2014.

Presentations:

  • Best Sprint Thesis Talk (Senior Researcher category) at RISC 2016, Research symposium organized by Department of CSE, IIT Bombay in April 2016.
  • Best 3-Minute Thesis Talk Awards at IITB-Monash Research Academy in 2015 and 2014.
  • Best Poster, IBM Research Day, Dept. of CSE, IIT Bombay in August 2015.
  • Invited speaker, VAIBHAV Summit organised by the Government of India, 2020.

Other:

  • First place in the shared task on vaccination behaviour detection at SMM4H workshop at EMNLP 2018 in October 2018.
  • Tata Consulting Services Research Scholar Fellowship in 2013.

I have worked in several problems of natural language processing (NLP) and its applications to several fields: epidemic intelligence, cybersecurity and LGBTI inclusion. This includes research as well as industry outputs. A significant portion of my current research is making NLP models robust for dialects of English.

 

Tutorials:

  •  `NLP for Healthcare in the Absence of a Healthcare Dataset', AACL, Suzhou, China, December 2020. (Co-speaker: Sarvnaz Karimi)
  • `NLP for Healthcare in the Absence of a Healthcare Dataset',  ALTA, Sydney, Australia, December 2019. (Co-speaker: Sarvnaz Karimi)
  • `Computational Sarcasm', presented at \textbf{EMNLP} 2017, Copenhagen, Denmark, September 2017. (Co-speaker:  Pushpak Bhattacharyya) 

Non-conference talks:

  • `Language of the Queer in India' at the `Queer in AI' social at NAACL, 2021.
  •  `Social media-based epidemic intelligence' in the panel on `NLP for social good' at the VAIBHAV summit (Vaishwik Bharatiya Vaigyanik) summit organised by the Government of India, 2020.
  • `Detecting Sarcasm, Combating Hate', TEDx talk at TEDxSomaiyaVidyavihar, an independently organised TEDx event, Mumbai, India, 2018. 
  • `Detecting sarcasm using incongruity', invited speaker at WASSA workshop at EMNLP 2017, Copenhagen, Denmark, 2017.

Posters:

  • `Computational Sarcasm', Google NLP Summit organized by Google Zurich, September 2017. 
  •  `Sarcasm Detection' and `Drunk-Texting Prediction', Research Colloqium, XRCI Open 2016 organized by Xerox Research Center India, Bengaluru, January 2016.
  • `Sarcasm Technology', IBM Research Day 2015 organized by IBM Research Lab, Bengaluru, August 2015.
  • `Sentiment Annotation Complexity', Microsoft TechVista 2015 organized by Microsoft Research India, Bengaluru, January 2015.
     

Panel Discussions:

  • Panelist in a discussion on `Integrating ChatGPT in Education' organized by EdTech IIT Bombay, Mumbai, 2023. (Online event)
  • Panelist in a discussion on `Achieving better health through AI' organized by Venture Cafe Sydney in Macquarie Park, Sydney, 2019.
  • Panelist in a discussion on `AI in India: Today and Tomorrow' at Data Science Day organized by Web \& Coding Club at IIT Bombay, Mumbai, 2018.

My Research Supervision

- Kernel-based reformulation of attention in Transformers

- Prompt-based methods for sarcasm detection

- Conversation Understanding for Dialects

- Multilingual small-scale large language models

- Misinformation Detection in News Articles

-LLMs for personalized learning

-Emotion recognition in music

My Teaching

Course Convener and Lecturer:

- 2024 Term 1: Natural Language Processing (COMP6713) - Undergraduate/Postgraduate (New Course; Design & Delivery)

- 2023 Term 3: Data Structures and Algorithms (COMP9024) - Postgraduate