Abilasha S

Indian Institute of Technology, Palakkad

PhD: Machine Learning, 2018-2023 (CGPA 8.38/10, course work from IIT Madras)

University of Calicut

M.Tech: Computer Science and Engineering, 2014-2016 (CGPA 9.27/10)
B.Tech: Computer Science and Engineering, 2010-2014 (CGPA 8.68/10)

Fairness in Time series Anomaly Detection and Prediction

Robust Method for Anomaly Detection and Extreme Event Prediction in Time Series

• WaRTEm-AD: Developed a warping resilient model for anomaly detection in univariate time series data with help of novel warp operators, data augmentation and Twin Autoencoder model [repo]
• DXtreMM: Developed a deep model for extreme event prediction in time series combined with a mixture of probability distributions [repo]
• WRADMts: Developed a similarity based alignment technique for multivariate time series data for anomaly detection considering temporal and intervariable dependencies

Recent Publications

• Warping Resilient Scalable Anomaly Detection in Time Series, S Abilasha, S Bhadra, P Deepak, A Mathew, Neurocomputing, 2022, Elsevier [link]
• Deep Extreme Mixture Model for Time Series Forecasting, S Abilasha, Sahely Bhadra, Ahmed Dadarkar, P Deepak, CIKM 2022, [link]
• Warping resilient Robust Anomaly Detection in Multivariate Time Series, Abilasha S, Sahely Bhadra (upcoming)

Publications from Masters

• A genetic algorithm based heuristic search on graphs with weighted multiple attributes, IEEE International Conference on Next Generation Intelligent Systems (ICNGIS), 1-3 Sept. 2016 [link]
• A Survey on Multiple Attribute Graph Indexing Methods, International Journal of Computer Science Trends and Technology (IJCST) –Volume 4 Issue 2, Mar -Apr2016

• Develop machine learning based methods for anomaly detection and prediction
• Explainable and interpretable machine learning models
• Fairness in machine learning , Unsupervised Learning, Optimization

Programming languages

Python, C, C++, Matlab, Java*, C#*

Tools and Packages

Tensorflow, Pytorch, Scikit-Learn, Numpy, Scipy, Pandas, Matplotlib, Git*, HTML*
*elementary proficiency

• NSF/SIGWEB travel grant CIKM 2022
• Senior Research Fellow, Science and Engineering Research Board, grant for project “Robust multiview learning in time series data”

• IndoML machine learning symposium 2022, IIT Gandhinagar, Best Poster Award
• Research Scholars Day 2023, IIT Pkd, Best Doctoral Research Award
• CSIR National Eligibility Test (CS) Qualified, GATE qualified (2018, 2016,2014)

Teaching Assistance:
• Machine Learning lab (IIT Pkd), Jan 2021
• Artificial Intelligence lab (IIT Pkd), Jan 2019, Jan 2020
• Data Structures lab (IIT Pkd), Jun 2019
• DBMS lab (IIT Pkd), Jun 2021
• Big Data lab (IIT Pkd), Jun 2020
Previous positions:
• Guest Lecturer, Dept. of Computer Science, Kerala Government Polytechnic College, Kozhikode (2017-18)
• Asst. Prof Dept. of CSE, LBS Applied Science College, Parappanangadi (2018)

• Petrichor’23 (tech fest IIT Pkd) ML workshop (conducted a session on time series analysis)
• Research talk at Research Scholars Day, IIT Pkd, 2023
• Research talks at Queen’s University, Belfast, UK, 2023 (as part of research visit)
• Industry Academia Conclave 5.0 IIT Pkd, 2023, Poster presentation
• CIKM conference, Oral presentation, 2022
• IndoML symposium, IIT Gandhinagar, poster presentation, 2022
• CREDS 2021, IIT Pkd, poster presentation
• Fairness Accountability Transparency Explainability (FATE) -ML workshop, Indian Institute of Science (2020) (participation)
• Research Scholars Day 2019, poster presentation

• Machine Learning, Linear Algebra, Probability and Statistics, NonLinear Optimization, Algorithms and Data Structures (IIT Madras)
• Deep Learning (IIT Palakkad)

• Dr. Sahely Bhadra (Assoc Prof, IIT Palakkad) – sahely@iitpkd.ac.in
• Dr. Deepak Padmanabhan (Senior Lecturer, Queen’s University Belfast) – D.Padmanabhan@qub.ac.uk
• Dr. Chandrashekar Lakshminarayanan (Asst Prof, IIT Madras) – chandrashekar@cse.iitm.ac.in