Hi! I'm Mohamedalfateh 👋🏽

Fully funded by The Scientific and Technological Research Council of Turkey (TÜBİTAK 1001 Project)

• Investigated device heterogeneity in RSSI-based Indoor Positioning using the TUJI1 dataset; developed a CNN-LSTM framework reducing 3D positioning errors to 2.20 m and improving cross-device robustness by 0.17 m (accepted in IEEE Access, minor revisions, under resubmission).
• Led the ML component of TÜBİTAK 1001 project on wireless node topology and live location detection under earthquake debris; designed algorithms that improved detection accuracy by 2.4% and optimized node topology for disaster scenarios (ongoing).

Delivered virtual instruction in Electrical & Electronic Engineering to undergraduate students, utilizing innovative methods to ensure engagement and comprehension.

• Conducted over 28 online classes, each engaging more than 35 students across various engineering topics.
• Applied advanced pedagogical strategies to enhance student participation in virtual environments.
• Collaborated on course material development and curriculum improvement with faculty members.

Delivered practical instruction in robotics and microcontrollers, guiding student project development and ensuring academic excellence in embedded systems education.

• Implemented and managed both software and hardware-based robotics classes, mentoring over 80 students.
• Supervised and evaluated 9 microcontroller-based projects, achieving a 95% student project success rate.
• Delivered academic support across three additional electrical and computer engineering courses.

Supported engineering education through lecture preparation, student mentoring, and supplemental instruction in PLC and SCADA systems.

• Assisted in developing lectures, quizzes, and academic activities across 4 subjects for 3 student batches.
• Mentored over 10 students during their final-year graduation projects.
• Led 3 advanced PLC & SCADA application sessions, enhancing lab performance and achieving a 92.6% student success rate.

Funded by Erasmus+ Internship Program

• Designed and executed experiments and simulations, validating methods that improved video streaming quality by 1.9%, contributing to more efficient and reliable multimedia performance.
• Analyzed underwater imaging enhancement results and produced comprehensive discussion reports, synthesizing findings to guide further research and development.

Selected participant (18% acceptance rate), fully funded, in an intensive international program on cutting-edge machine learning research sponsored by Google DeepMind.

• Attended 22 hours of lectures and 10 hours of workshops by leading AI experts, plus 4 hours of discussions on computer vision and applied deep learning.
• Focused on generative/diffusion models, reinforcement learning, and ethics in machine learning.
• Strengthened research perspective at the intersection of academia and industry through technical labs, poster sessions, and panel discussions.