About Me

I'm a Ph.D. fellow at the Indian Statistical Institute (ISI), Kolkata, working under the supervision of Prof. Swagatam Das in the Electronics and Communication Sciences Unit (ECSU).

Most real-world datasets are far from idealโ€”they're imbalanced, biased, or simply too small to learn from effectively โ€” and that's exactly where I come in. My doctoral research focuses on building resilient deep learning models to solve challenges around class imbalance, long-tailed distributions, bias mitigation, and fairness.

Research Focus

My work focuses on designing algorithms that tackle real-world data challenges such as class imbalance, long-tailed distributions, bias mitigation, and fairness in machine learning. I develop novel techniques to ensure AI systems perform reliably even when trained on imperfect data.

Education

Ph.D. in Machine Learning
Indian Statistical Institute (ISI), Kolkata
Advisor: Prof. Swagatam Das

M.Tech in Computer Science and Engineering
Specialization: Software Engineering
Zakir Husain College of Engineering & Technology (ZHCET), Aligarh Muslim University (AMU)

B.Tech in Computer Engineering
Zakir Husain College of Engineering & Technology (ZHCET), Aligarh Muslim University (AMU)

Experience

Research Associate
Ericssion Research
Currently working on zero-shot and few-shot time series forecasting for channel data, enabling accurate predictions with minimal data to enhance resource allocation and operational efficiency. This is a practical application of zero-shot and few-shot time series forecasting.

Latest News

๐Ÿ“… Date ๐Ÿ—ž๏ธ News
October 2024 Presented my research (poster) at MICCAI 2024, Marrakesh, Morocco.
July 2024 (Poster) Paper titled "Algorithmic Fairness in Lesion Classification by Mitigating Class Imbalance and Skin Tone Bias" has been accepted for presentation at MICCAI 2024. Among the 15 papers accepted from India.
May 2024 Presented my research (poster) at IEEE ISBI 2024, Athens, Greece.
May 2024 Our work CCO: A Cluster Core-based Oversampling Technique for Improved Class-Imbalanced Learning has been published in IEEE TETCI.
February 2024 (Poster) Paper on Mo2E: Mixture of Two Experts for Class-Imbalanced Learning from Medical Images accepted at IEEE ISBI 2024. [View Paper]
April 2023 (Oral & Poster) Paper on Handling Class Imbalance by Estimating Minority Class Statistics accepted at IEEE IJCNN 2023. [View Paper]

Research Interests & Skills

Research Areas

Machine Learning Deep Learning Class Imbalance Long-tailed Distributions Bias Mitigation Fairness in ML Medical Image Analysis Computer Vision

Technical Skills

Python PyTorch TensorFlow Scikit-learn Data Analysis Statistical Methods Computer Vision Research & Publication

Contact Me

If you're interested in my research or potential collaborations, feel free to reach out!

Gmail

faizanansari541@gmail.com

Location

Electronics and Communication Sciences Unit (ECSU)
Indian Statistical Institute
Kolkata, India