Curriculum Vitae

Education

• Ph.D. degree, 2025, Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Augsburg, Germany. Supervisor Prof. Dr. Björn W. Schuller
  • Dissertation title: "Foundation Models in Affective Computing".
  • Conducted peer-reviewed studies for using foundations models and LLMs (OpenAI GPT-4 and GPT-3.5) for more than 13 affective computing problems, including sentiment analysis and emotions detection and prompt engineering.
  • External researcher at the Chair of Health Informatics, Technical University of Munich (TUM), Prof. Dr. Björn W. Schuller, 2024.
• M.Sc. degree in Computer Science, 2018, Alberts-Ludwig Universität Freiburg, Freiburg, Germany.
  • Master's Thesis: Automatic Correction of Misaligned Spaces and Typos Using Deep Learning
  • Follow up-paper: Tokenization Repair in Presence of Spelling Errors
  • Chair of Algorithms and Data Structures, Prof. Dr. Hannah Bast
• B.Sc. degree in Computer Science and Engineering, 2014, German University in Cairo (GUC), Cairo, Egypt.

Work Experience

• Dynatrace: Senior Researcher in Generative AI, Nov 2024 -- Now, Vienna, Austria

• SYNCPILOT: Senior Research Data Scientist, Dec 2017 -- Oct 2024, Germany

  • Led the development of LLM-based solutions for developers, creating generative AI interfaces (Django web platform, VSCode extension), implementing advanced RAG techniques for deep code understanding (syntax-based splitting, vector indexing), and building LLM agents for workflow automation.
  • Led the development of a real-time social signals prediction product, utilizing deep learning (Keras/TensorFlow) for multimodal personality prediction (audio/images/text), designing streaming solutions for live predictions (Redis, NVIDIA Triton), deploying scalable MLOps infrastructures (Kubernetes, Docker, Kubeflow), and mentoring a team on ASR and sentiment analysis.

• University of Freiburg: HiWi Job, Summer 2016 - Autumn 2017, Freiburg, Germany

  • Freiburg RNA Tools: a tool that visualizes several RNA interaction algorithms for teaching purposes.
• Google: Software Engineering Intern, Winter 2016, Paris, France
• Facebook: Software Engineering Intern, Fall 2015, New York City, US
• German University in Cairo: Junior Teaching Assistant, Spring 2014, Cairo, Egypt
  • Teaching computational number theory in the course " Advanced Data Structures and Algorithms ", slides: Lecture 1 and Lecture 2
• Trustious: Research and Development Intern, Summer 2012, Cairo, Egypt

Publications

1. Björn Schuller, Adria Mallol-Ragolta, Alejandro Peña Almansa, Iosif Tsangko, Mostafa M. Amin, Anastasia Semertzidou, Lukas Christ, and Shahin Amiriparian. “Affective Computing Has Changed: The Foundation Model Disruption” In: arXiv preprint arXiv:2409.08907, 2024.
2. Mostafa M. Amin and Björn W. Schuller. "On Prompt Sensitivity of ChatGPT in Affective Computing" In: Proceedings of Affective Computing and Intelligent Interaction (ACII). Glasgow, Scotland: IEEE, 2024, S. 203–209.
3. Mostafa M. Amin, Rui Mao, Erik Cambria, and Björn W. Schuller. "A Wide Evaluation of ChatGPT on Affective Computing Tasks". In: IEEE Transactions on Affective Computing, 2024.
4. Mostafa M. Amin, Erik Cambria, and Björn W. Schuller. "Can ChatGPT's Responses Boost Traditional Natural Language Processing?". In: IEEE Intelligent Systems, vol. 38, no. 5, 2023, pp. 5–11.
5. Mostafa M. Amin, Erik Cambria, and Björn W. Schuller. "Will Affective Computing Emerge from Foundation Models and General AI? A First Evaluation on ChatGPT". In: IEEE Intelligent Systems, vol. 38, no. 2, 2023, pp. 15–23.
6. Mina Nessiem, Mostafa M. Amin, and Björn W. Schuller. "SMILENets: Audio Representation Learning via Neural Knowledge Distillation of Traditional Audio-Feature Extractors". In: IEEE 8th International Conference on Frontiers of Signal Processing (ICFSP). Corfu, Greece: IEEE, 2023, S. 32–37.
7. Mina A. Nessiem, Harry Coppock, Mostafa M. Mohamed, and Björn W. Schuller. "Artificial Intelligence in COVID-19". In: "Omics Approaches and Technologies in COVID-19", 2022.
8. Mostafa M. Amin and Björn W. Schuller. "Normalise for Fairness: A Simple Normalisation Technique for Fairness in Regression Machine Learning Problems". In: arXiv preprint arXiv:2202.00993, 2022.
9. Mostafa M. Mohamed, Mina A. Nessiem, Anton Batliner, Christian Bergler, Simone Hantke, Maximilian Schmitt, Alice Baird, Adria Mallol-Ragolta, Vincent Karas, Shahin Amiriparian and Björn W. Schuller. "Face mask recognition from audio: The MASC database and an overview on the mask challenge". In: Pattern Recognition 122 (2022), S. 108361.
10. Hannah Bast, Matthias Hertel and Mostafa M. Mohamed. "Tokenization Repair in the Presence of Spelling Errors“. In: Proceedings of the 25th Conference on Computational Natural Language Learning. Online: Association for Computational Linguistics, 2021, S. 279–289.
11. Mina A. Nessiem, Mostafa M. Mohamed, Harry Coppock, Alexander Gaskell and Björn W Schuller. "Detecting COVID-19 from Breathing and Coughing Sounds using Deep Neural Networks". In: IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS). Lisbon, Portugal: IEEE, 2021, S. 183–188. Best student paper award
12. Mostafa M. Mohamed and Björn W. Schuller. Concealnet: An End-to-End Neural Network for Packet Loss Concealment in Deep Speech Emotion Recognition. In: arXiv preprint arXiv:2005.07777, 2020.
13. Mostafa M. Mohamed and Björn W. Schuller. "I have vxxx bxx connexxxn!": Facing Packet Loss in Deep Speech Emotion Recognition. In: arXiv preprint arXiv:2005.07757, 2020.
14. Mostafa M. Mohamed, Mina A. Nessiem, and Björn W. Schuller. On Deep Speech Packet Loss Concealment: A Mini-survey. In: arXiv preprint arXiv:2005.07794, 2020.
15. Martin Raden, Syed M Ali, Omer S Alkhnbashi, Anke Busch, Fabrizio Costa, Jason A Davis, Florian Eggenhofer, Rick Gelhausen, Jens Georg, Steffen Heyne, et al. "Freiburg RNA tools: a central online resource for RNA-focused research and teaching". In: Nucleic acids research 46.W1 (2018), W25–W29.
16. Martin Raden, Mostafa Mahmoud Mohamed, Syed Mohsin Ali and Rolf Backofen. "Interactive implementations of thermodynamics-based RNA structure and RNA–RNA interaction prediction approaches for example-driven teaching". In: PLoS computational biology 14.8 (2018), e1006341.
17. Alexander Nutz, Daniel Dietsch, Mostafa Mahmoud Mohamed and Andreas Podelski. "Ultimate kojak with memory safety checks". In: International Conference on Tools and Algorithms for the Construction and Analysis of Systems. Springer. 2015, S. 458–460.

Competitive Programming

As Judge:

• Chief Judge, Africa and Arab Collegiate Programming Contest (ACPC) 2018 and 2019, Sharm El-Sheikh, Egypt
• Judge, ACPC 2014, 2017, 2022, 2023, Sharm El-Sheikh, Egypt
• Chief Judge, Egyptian Collegiate Programming Contest (ECPC) 2017, Alexandria, Egypt

As Contestant:

• World Finalist Team, International Collegiate Programming Contest (ICPC) World Finals 2014, Yekatrinburg, Russia
• Regional Champion Team, ACM-ACPC 2013, Sharm El-Sheikh, Egypt
• 4th place Team, ACM-ACPC 2012, Amman, Jordan
• Africa and Middle East Champion Team, ACM-ICPC World Finals 2012, Warsaw, Poland
• Regional Champion Team, ACM-ACPC 2011, Beirut, Lebanon
• National Champion Team, ACM-ECPC 2011, Alexandria, Egypt

Courses

• Neural Networks and Deep Learning
• Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
• Structuring Machine Learning Projects
• Convolutional Neural Networks
• Sequence Models
• Applied Plotting, Charting & Data Representation in Python
• Introduction to Deep Learning
• How to Win a Data Science Competition: Learn from Top Kagglers
• Bayesian Methods for Machine Learning
• Practical Reinforcement Learning
• Deep Learning in Computer Vision
• Natural Language Processing

Programming Languages and Technologies

Programming languages:

• Python
• C/C++
• Java
• HTML
• Javascript
• LaTeX
• Shell, Bash

Technologies:

• LangChain
• LangGraph
• Qdrant
• Keras and Tensorflow (v1 and v2)
• Hugging Face
• NumPy
• Pandas
• SciPy
• Scikit-learn
• LightGBM
• Librosa
• Matplotlib
• Seaborn
• Google Charts
• Docker, Docker-Compose
• Kubernetes
• Django
• Celery
• FastAPI
• Nvidia Triton Inference Server
• Redis, Redis-Streaming
• Nginx