Beste Aydemir
I am an MSc student in Data Science at Ludwig-Maximilian University of Munich.
My research interests are vision language models and their applications to embodied agents and autonomous driving.
Email /
GitHub /
LinkedIn
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Education
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Ludwig Maximilian University of Munich
Master of Science in Data Science, GPA: 1.3 (1 is the best)
- Relevant Courses: Statistical Reasoning and Inference, Predictive Modeling, Advanced Deep Learning for Robotics
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Bilkent University
Bachelor of Science in Electrical and Electronics Engineering (Comprehensive Scholarship); GPA: 3.68/4
- Relevant Courses: Probability and Statistics, Fundamental Structures of Computer Science, Neural Networks, Algorithms and Programming I-II, Stochastic Models
- Signals and Systems, Linear Algebra and Differential Equations, Nonlinear Systems Theory
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Projects
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Autonomous Driving LLM-based Agent in Streaming Videos
Report
- Utilized multimodal models such as InstructBLIP and Video-Llava for in-context learning on driving datasets
- Implemented text based memory systems for LLM agents in streaming environments
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Diffusion Robot Path Planning
Project Poster
- Replication of "Planning with Diffusion for Flexible Behavior Synthesis" (Janner et al., 2022) in for 2D Maze environment in PyTorch
- Extension of the paper to 3D environment of robotic arm with 7 DoF
- Training on Google Cloud Engine
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Experience
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Huawei Munich Research Center
Student Worker (November 2024 - April 2025)
- Using video language models for autonomous driving tasks
- Experiments on fine-grained action understanding of videos in traffic scenarios
- Utilizing existing autonomous driving datasets to curate a more descriptive dataset to be used for retrieval
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Fraunhofer
Student Worker (November 2023 - November 2024)
- Simulation of centralized MPC control of multi-agent drone system for navigations, and experiments
- Developing learning-based alternatives to bypass linear solvers of CasADi for speedup
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The University of Edinburgh
Student Researcher (June 2020 - April 2024, Online)
- Q-Learning based models for behavioral analysis in the Morris Water Maze experiment
- Developed the cognitive value matric to assess the spatial navigation capabilities in the simulations
- Featured a poster at the 49th European Brain and Behaviour Society (EBBS) Meeting
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