Md Fahim Sikder
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    • I have attended the WASP, WASP-HS and DDLS conference
    • I have started working on a WASP-HS project (Synthetic Data)
    • I am co-organizing a Workshop - The Politics of Model
    • I am co-organizing a Hackathon
    • I have defended my Phd Thesis
    • PhD Thesis Nailing (Spikning)
    • Reserach Work Presented at NordicAIMeet
    • Close to Final Seminar PhD
    • Paper Accepted at ECAI 2025
    • Attended ICLR 2025
    • Champion at Swedens Largest AI Hackathon - Hackaping
    • Half Time Seminar PhD
  • Publications
    • T5Bench: Benchmarking Unconditional Time-Series Generation Beyond Fidelity and Usefulness
    • StreamFair: Online Fair Adaptation Under Temporal Intersectional Drift
    • FairCert: Certifiable Error Rate Fairness for ML and LLM Decision Systems
    • FairRep: Mitigating Intersectional Bias through Fair Representation Learning
    • Representative Synthetic Data for Fair Decision Making
    • Promoting Intersectional Fairness through Knowledge Distillation
    • TransFusion: Generating Long, High-Fidelity Time Series using Diffusion Models with Transformers
    • Fair4Free: Generating High-fidelity Fair Synthetic Samples using Data Free Distillation
    • FairX: A comprehensive benchmarking tool for model analysis using fairness, utility, and eXplainability
    • Bt-GAN: Generating Fair Synthetic Healthdata via Bias-transforming Generative Adversarial Networks
    • Predicting Students Yearly Performance using Neural Network: A Case Study of BSMRSTU
    • Generative Models for Time-Series and Fair Data Generation
    • Explainable Bengali Multiclass News Classification
    • Generating Private and Fair Long-Sequenced Longitudinal Healthcare Records
    • Fair Latent Deep Generative Models (FLDGM) for Syntax-agnostic and Fair Synthetic Data Generation
    • Synthesizing Longer and Higher-Fidelity Time-Series Data Using Generative Adversarial Networks
    • Sequential Ice Hockey Events Generation using Generative Adversarial Network
    • Measuring the Fairness, Privacy and Accuracy of Time-Series Generative Models - A Survey
    • Privacy-Preserving Synthetic Trajectory Data Generation
    • Bangla Handwritten Digit Recognition & Generation
    • Smart Disaster Notification System
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    • Synthetic Data: Facts, Representations, and Transparency
    • Computational Cardio Oncology
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    • Installing Texlive Latest Version (Texlive-2021) on Ubuntu-20.04/18.04
    • Installing Docker, Creating & Running First Python Script Using it on Ubuntu 20.04 LTS
    • How to Install R and two most popular R packages (tidyverse & rstan) in Ubuntu 20.04 LTS
    • Julia Tutorial Part 2: Data Structures
    • Julia Tutorial Part 1: Installations & Basics
    • ইউরোপে পিএইচডি
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FairCert: Certifiable Error Rate Fairness for ML and LLM Decision Systems

May 1, 2026·
Md Fahim Sikder
· 0 min read
Project
Type
Conference paper
Publication
Under Review
Last updated on May 1, 2026
Representation Learning ML for Healthcare Data Fairness Fair Representation Learning Intersectional Bias
← StreamFair: Online Fair Adaptation Under Temporal Intersectional Drift May 1, 2026
FairRep: Mitigating Intersectional Bias through Fair Representation Learning Feb 19, 2026 →

© 2026 Md Fahim Sikder. This work is licensed under CC BY NC ND 4.0

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