About
PhD Candidate and Research Assistant specializing in advanced machine learning for partially-observed time-series data, with a strong focus on developing interpretable and explainable AI systems. Passionate about bridging mathematical methodologies with biomedical research to create trustworthy, automated solutions that enhance medical decision-making and provide transparent insights.
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Work
University of Rostock
PhD Student & Research Assistant
Université de Lille and ONCOLille
Research Intern
IISER Kolkata
Teaching Assistant for Introduction to Computation
IISER Kolkata
Teaching Assistant for Programming and Data Structures
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Volunteer
Ek Pehal
·Volunteer Computer Science Educator
Provided computer science education to underserved youth, fostering foundational technical skills and digital literacy.
Inventa (inter-IISER Science Communication Platform)
·Organizational Committee Member
Coordinated and managed activities for an inter-IISER science communication platform to foster scientific discourse.
IISER Kolkata's Science Communication Platform - Cogito
·Website Head
Led web development and content management for the university's science communication platform, ensuring effective digital outreach.
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Education
Mathematics (Statistics Focus)
Indian Institute of Science Education and Research, Kolkata
Algorithm Complexity Analysis, Graph Algorithms
IIIT Bangalore
Physics, Chemistry, Mathematics, Computer Science, English, Physical Education
Don Bosco School, Guwahati
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Awards
Technologies of the Future Scholarship
Recipient of a EUR 1700 scholarship for 2 months, awarded to 5 PhD students in Germany for a research exchange in France.
Abbe Grant
Awarded for participation in the 11th Heidelberg Research Forum.
All India Rank 24 in GATE Statistics
Achieved a top 0.1% rank in a highly competitive national examination for postgraduate admissions.
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Publications
Anomaly Detection via Mean Shift Density Enhancement
Under Review (arXiv)
Multivariate Functional Linear Discriminant Analysis for Partially-Observed Time Series
Machine Learning
Handling Missing Data in Downstream Tasks with Distribution-Preserving Guarantees
Under Review (arXiv)
FUSE: Fast Semi-Supervised Node Embedding Learning via Structural and Label-Aware Optimization
Under Review (arXiv)
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Skills
Programming Languages
Python (Tensorflow, Pytorch, JAX, statsmodels, networkx), C, C++
Databases
SQL, MongoDB, NoSQL
Tools & Platforms
Docker, LaTeX, Git
Machine Learning & AI
Time-Series Analysis, Functional Data Analysis, Interpretable AI (XAI), Explainable AI, Anomaly Detection, Graph Neural Networks (GNNs), Deep Learning, Semi-Supervised Learning, Feature Extraction, Classification, Imputation, Density Estimation, Statistical Modeling, Algorithm Development, Model Interpretability
Data Science & Analytics
Data Preprocessing, Statistical Analysis, Quantitative Research, Scientific Computing, Data Visualization
Research & Academic
Scientific Writing, Peer Review, Grant Writing, Academic Presentations, Technical Documentation
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References
Prof. Dr. Olaf Wolkenhauer
PhD Supervisor, Full Professor, Department of Systems Biology and Bioinformatics, Institute of Computer Science, University of Rostock. Email: olaf.wolkenhauer@uni-rostock.de
Dr. Clémence Réda
Co-supervisor / Co-author, Chargé de recherche, Institut de Biologie de l'École Normale Supérieure. Email: reda@bio.ens.psl.eu
Pr. Sophie Dabo
Internship Supervisor, Full Professor in Applied Mathematics, Inria - Modal - Université de Lille. Email: sophie.dabo@univ-lille.fr
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