Curriculum Vitae

PhD in Computer Science

MSc in Computer Engineering

• GPA: 4.00/4.00

BSc in Computer Engineering

• GPA: 3.70/4.00

Salaried PhD

• Led reinforcement learning research, resulting in a NeurIPS 2024 paper and ongoing preprints.
• Collaborated with the Intelligent Autonomous Systems group at TU Darmstadt under Jan Peters, leading to a submission.
• Contributed to open-source codebases (e.g., MOMBO, ObjectRL) adopted by the research community.

Research and Teaching Assistant

• Conducted research in computer vision and uncertainty quantification, leading to a publication at ICLR 2022.

Machine Learning Engineer

• Developed Siamese CNNs for fraud detection in signature verification.
• Achieved 95% test accuracy on internal data and 88% on CEDAR benchmark, reducing fraud risk.
• Applied various CNNs (MobileNetV2, ResNet50) using Keras/TensorFlow.

Research Intern

• Built simulated robot manipulation environments in pyBullet for kitchen tasks.
• Implemented Deep Deterministic Policy Gradient (DDPG) and Soft Actor-Critic (SAC) for robotic control.
• Integrated pyBullet and MoveIt environments for inverse kinematics calculations.

Front-End Developer Intern

• Built front-end web applications (JavaScript, Node.js) and back-office systems.
• Designed secure login pages, error-handling flows, and responsive user interfaces.
• Built an Arduino-based chatbot integrated with Slack for sensor-user interaction.

Teaching Assistant

• Courses: Introduction to Machine Learning Course, Data Mining and Machine Learning.
• Delivered exercise sessions on core machine learning concepts; guided students through assignments and provided constructive feedback.
• Mentored 2+ MSc students on their theses, supporting research design and implementation.

Teaching and Research Assistant

• Courses: Deep Learning, Probability and Statistics for Data Science, Computer Architecture, Introduction to Programming for Data Science (Python), Logic Circuits Laboratory
• Supervised undergraduate students, enhancing their problem-solving and programming skills.
• Mentored 3+ BSc students on final projects, leading to 2 workshop papers at NeurIPS and ICLR.
• Mentored 1 MSc student on thesis work, resulting in a TMLR publication.

• European Workshop on Reinforcement Learning (EWRL), Tubingen, Germany
• Danish Digitalization, Data Science and AI (D3A 3.0), Nyborg, Denmark

• The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada
• Danish Digitalization, Data Science and AI (D3A 2.0), Nyborg, Denmark
• The Forty-first International Conference on Machine Learning (ICML 2024), Vienna, Austria
• 6th Symposium on Advances in Approximate Bayesian Inference (AABI), Vienna, Austria