Recommended expert

Musaib Parray

Research Intern – Exploring Reasoning with Diffusion Models

Musaib Parray
Erlangen, Germany

Experience

Oct 2025 - Present
4 months
Germany

Research Intern – Exploring Reasoning with Diffusion Models

Machine Learning and Perception group, FAU Erlangen-Nürnberg

  • Investigating the equivalence between the Tiny Reasoning Model (TRM) and diffusion models for structured reasoning tasks such as Sudoku and maze solving.
  • Exploring the reasoning and generative capabilities of diffusion models in symbolic problem-solving environments.
Apr 2025 - Aug 2025
5 months
Germany

Machine Learning Lab – Autonomous Driving & Generative Models

LMS, FAU Erlangen-Nürnberg

  • Built an ML pipeline for autonomous driving in OpenAI Gymnasium, generating labeled datasets from simulation frames and control actions.
  • Designed and trained lightweight CNN and RNN models for end-to-end control and implemented model compression for real-time inference.
  • Designed and trained a diffusion model from scratch on MNIST, implementing denoising, sampling, and image generation during inference.
Jan 2025 - Mar 2025
3 months
Germany

Canny Edge Detection Optimization (DSP Lab Project)

LMS, FAU Erlangen-Nürnberg

  • Implemented the full Canny Edge Detection pipeline in Python using OpenCV, modularizing key stages such as gradient computation and hysteresis thresholding.
  • Enhanced performance by integrating CLAHE preprocessing and multi-scale Gaussian filtering, improving edge contrast and localization.
  • Conducted experiments on the BSDS500 dataset to analyze the impact of parameter tuning and multi-scale edge combination.
Sep 2022 - May 2023
9 months
India

Bachelor Thesis – EEG Seizure Detection Using CNN

Aligarh Muslim University

  • Developed a CNN-based model for epileptic seizure detection using CHB-MIT EEG data.
  • Compared time-domain and FFT-based features, achieving superior performance with frequency-domain inputs.
  • Designed a lightweight CNN for real-time classification of seizure states (Interictal, Preictal, Ictal).

Summary

M.Sc. student majoring in Machine learning in Signal Processing at FAU Erlangen with a strong foundation in machine learning, signal processing, and deep generative models. Experienced in implementing neural architectures for perception and generation tasks.

Skills

  • Programming: Python, Matlab, C++
  • Libraries & Frameworks: Pytorch, Numpy, Scipy, Gymnasium, Librosa
  • Tools: Jupyter, Matlab, Git
  • Domains: Deep Learning, Generative Models (Gans, Diffusion Models), Reinforcement Learning, Audio And Image Processing, Adaptive Filters
  • Other Skills: Data Visualization, Version Control, Scientific Writing

Languages

English
Advanced
German
Elementary

Education

Oct 2023 - Present

Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

Master of Science, Communications and Multimedia Engineering · Communications and Multimedia Engineering · Erlangen, Germany

Oct 2019 - Jun 2023

Aligarh Muslim University

Bachelor of Technology, Electrical Engineering · Electrical Engineering · Aligarh, India · First Division Honours, 8.95/10.0

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