Sukanya Patra

I am a PhD student affiliated with the Big Data and Machine Learning Lab at the University of Mons, Belgium. My research interests lie in exploring the theory of deep learning and its applications, focusing on problems related to image data. Presently, my research is centred around deep anomaly detection under the supervision of Professor Souhaib Ben Taieb. My work focuses on developing novel anomaly detection methods that can address some of the most challenging aspects of industrial applications, which include tackling non-stationarity in data and working with limited, weak labels. Prior to my current position, I received a Master's degree in Data Science from the Eindhoven University of Technology, The Netherlands.


Doctoral Researcher

University of Mons, Belgium

Conducting research on Anomaly Detection in Image Sequences under Prof Souhaib ben Taieb

Nov 2021 - Present

Graduate Intern

ASML, Eindhoven, The Netherlands

Key responsibilities:
• Building a context-aware machine learning framework that can adapt to concept drift
• Finding hidden patterns and interactions among more than 50 features
• Dealing with the unbalanced dataset

April 2021 - September 2021

Teaching Assistant

Eindhoven University of Technology (TU/e), The Netherlands

February 2021 - April 2021

Data Science Intern

Mentech Innovations, Eindhoven, The Netherlands

Key responsibilities:
• Performed an extensive literature review for emotion detection using facial expression
• Implemented a hybrid CNN-LSTM model
• Achieved an accuracy of 60% on CREMA-D and 54% on RAVDESS datasets
• Tested the model in real-time using a live video feed via webcam

August 2020 - November 2020

Associate Software Engineer

SOAIS, Kolkata, India

Key responsibilities:
• Enhancement, support, and maintenance activity of the delivered processes (Personal, and Job Data, Recruitment, Performance Management etc.) in the stringent timeline
• Responsible for 2 major clients having a total of 10,000+ employees
• Worked on XML Publisher, approval workflow engine (AWE) security-related activity, enhancements, and testing
• Modify several SQR reports based on client requirements

July 2018 - July 2019


International Management Institute, Kolkata, India

Key responsibilities:
• The following algorithms were used - User-based collaborative filtering (UBCF), Item-based collaborative filtering (IBCF), and Singular Vector Decomposition (SVD)
• Experiments were performed with the MovieLens dataset
• Multiple distance measures were employed: Cosine, Pearson correlation, and Jaccard

May 2017 - August 2017


Eindhoven University of Technology (TU/e), The Netherlands

Master of Science (MSc)
Computer Science - Data Science in Engineering
September 2019 - September 2021

Government College of Engineering & Leather Technology, India

Bachelor of Technology (BTech)
Information Technology

GPA: 8.76

August 2014 - July 2018


Programming Languages & Tools
  • Data Science Concepts Big Data, Data Mining, Data Analysis, Data Visualization, Machine Learning, Deep Learning
  • Technologies Related to Data Tableau, MatplotLib, Scikit-Learn, TensorFlow, Keras, PySpark
  • Programming Languages Python, R, SAS, Java, C, C++, SQL, PeopleCode
  • Scripting Language PHP, HTML, CSS
  • Operating Systems Android, Windows, and Linux
  • ERP PeopleSoft HRMS/ FSCM 9.2, PeopleTools 8.54
  • Databases SQL Server 12.0, Oracle 11g
  • Office Suite Microsoft Office Suite, Google Suite


Peer-reviewed Conference Attended
  • A Comparative Evaluation of Algorithms in Movie Recommender Systems with B. Ganguly, MARCON 2017 (International Marketing Conference) at International Management Institute (IMI), Kolkata, Dec 18-19, 2017.
  • Machine Learning Based Cyber Risk Assessment and Mitigation Framework for Phishing Attacks (MLP-CRAM): A Design Science Approach with A. Mukhopadhyay and B. Biswas, 13th Design Science Research in Information Systems and Technology (DESRIST - 2018), IIT Madras, June 3 - 6 ,2018.
Chapter in Edited Book
  • Forecasting Problems in Cyber Security: Applying Econometric Techniques to Measure IT Risk, with B. Biswas, In Handbook of Computer and Cyber Security: Principles, Algorithm, Applications and Perspectives, CRC Press, Brij B. Gupta, Dharma P. Agrawal and Haoxiang Wang (eds.).
Peer-reviewed Journal Articles
  • Improvising Singular Value Decomposition by KNN for Use in Movie Recommender Systems with B. Ganguly, Journal of Operations and Strategic Planning, 2(1), pp. 22-34. Academic Projects