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Dr. Aakansha Aggarwal

Assistant Professor (Senior Grade), Department of Computer Science and Engineering, School of Computing, Haridwar

Qualification: Ph.D. in Computer Science & Engineering
aakanshagupta.74@gmail.com
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Research Interest: Artificial Intelligence, Machine Learning, Data Science, Natural Language Processing, Generative AI/LLMs, Time-Series Forecasting, Healthcare AI, Statistics

Bio Publications FDP / Workshops Conferences
Bio

Dr. Aakansha Aggarwal is an Assistant Professor (Senior Grade) in the Department of Computer Science and Engineering at Amrita Vishwa Vidyapeetham, Haridwar. She holds a Ph.D. in Computer Science & Engineering, with professional experience in Artificial Intelligence, Machine Learning, Data Science, and teaching and mentoring. Her research interests include AI/ML, NLP, Generative AI, time-series forecasting, healthcare applications, and data-driven intelligent systems.

Publications

Journal Article

Year : 2023

A deep-SIQRV epidemic model for COVID-19 to access the impact of prevention and control measures

Cite this Research Publication : Aakansha Gupta, Rahul Katarya, A deep-SIQRV epidemic model for COVID-19 to access the impact of prevention and control measures, Computational Biology and Chemistry, Elsevier BV, 2023, https://doi.org/10.1016/j.compbiolchem.2023.107941

Publisher : Elsevier BV

Year : 2022

Possibility of the COVID-19 third wave in India: mapping from second wave to third wave

Cite this Research Publication : Aakansha Gupta, Rahul Katarya, Possibility of the COVID-19 third wave in India: mapping from second wave to third wave, Indian Journal of Physics, Springer Science and Business Media LLC, 2022, https://doi.org/10.1007/s12648-022-02425-w

Publisher : Springer Science and Business Media LLC

Year : 2022

Deep embedding for mental health content on social media using vector space model with feature clusters

Cite this Research Publication : Aakansha Gupta, Rahul Katarya, Deep embedding for mental health content on social media using vector space model with feature clusters, Concurrency and Computation: Practice and Experience, Wiley, 2022, https://doi.org/10.1002/cpe.6930

Publisher : Wiley

Year : 2021

PAN-LDA: A latent Dirichlet allocation based novel feature extraction model for COVID-19 data using machine learning

Cite this Research Publication : Aakansha Gupta, Rahul Katarya, PAN-LDA: A latent Dirichlet allocation based novel feature extraction model for COVID-19 data using machine learning, Computers in Biology and Medicine, Elsevier BV, 2021, https://doi.org/10.1016/j.compbiomed.2021.104920

Publisher : Elsevier BV

Year : 2020

Social media based surveillance systems for healthcare using machine learning: A systematic review

Cite this Research Publication : Aakansha Gupta, Rahul Katarya, Social media based surveillance systems for healthcare using machine learning: A systematic review, Journal of Biomedical Informatics, Elsevier BV, 2020, https://doi.org/10.1016/j.jbi.2020.103500

Publisher : Elsevier BV

FDP / Workshops
  • 2-week FDP on “Deep Learning & Applications (Parallel Architectures)”, Aug 23 – Sept 3, 2021, organized by IITs, MNIT, NITs, IIITDM (under MeitY)
  • “N-SAMARTH” Webinar, Jan 12–14, 2021, DTU
  • One-week STTP on “Data Science & Learning Systems for Engineering Research & Design”, June 24–30, 2020, NIT Kurukshetra & Engineering College Bikaner
  • Five-day FDP on Data Science, AICTE-ATAL, Punjab Engineering College
  • One-week STTP on “Recent Trends in Security and Cryptography”, Nov 18–22, 2019, DTU
  • STTP on “Recent Trends in AI and Machine Learning”, Jul 29 – Aug 2, 2019, DTU
  • Coordinated & Participated in International Seminar: “Recent Trends in Big Data Analytics”, Aug 21, 2018, DTU (with New Zealand universities)
Conferences
  • Yash Verma; Aakansha Gupta; Rahul Katarya, “Exploratory Data Analysis On Student Alcohol Consumption”, ICIMMI 2022, Dec 23–24, 2022
  • Keshav Nath et al., “Socialympics – Sentiment Analysis of Tweets about Tokyo Olympics 2021”, 48th Int’l Conf., Sozopol, Jun 7–13, 2022
  • Aakansha Gupta; Rahul Katarya, “Human Mobility based Pandemic Prediction Model”, ICAC3N, Dec 17–18, 2021
  • Aakansha Gupta; Rahul Katarya, “Improving document representation using KPCA and clustered word embeddings”, ICEECCOT-2021, Dec 10–11, 2021
  • Harsh Raj et al., “Extract It! Product Category Extraction by Transfer Learning”, CICT-2021, Oct 29–30, 2021
  • Aakansha Gupta; Rahul Katarya, “Analyzing the Effects of Text Representations on the Performance of Document Clustering in Public Health Tweets”, ICCIDE-2021
  • Aakansha Gupta et al., “Artificial Eye for the Visually Impaired”, ICAAAIML-2021
  • Rahul Katarya et al., “Review of Mathematical and Deep Learning Forecasting Methods for COVID-19”, ICACCS 2021
  • Aakansha Gupta; Rahul Katarya, “A Novel LDA-based Framework to Forecast COVID-19 Trends”, ICICC-2021
  • Karan Keswani et al., “LDA Based model for mining textual features from financial news articles”, ICACCCN-2020
  • Samarth Garg et al., “A Literature Review On Sentiment Analysis Techniques Involving Social Media Platforms”, PDGC 2020
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