Aydin Ayanzadeh
CV

Curriculum vitae

Aydin Ayanzadeh

Ph.D. student in Computer Science, University of Maryland, Baltimore County · CORAL Lab

Ph.D. expected May 2028 · open to research internships and collaborations

aydina1@umbc.edu · a.ayanzadeh@gmail.com · Baltimore, Maryland, USA

Google Scholar · ORCID · DBLP · GitHub · LinkedIn · Hugging Face

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Summary

Ph.D. student in Computer Science working on computer vision, multimodal learning and medical image analysis. Current research integrates vision-language models with computer vision for assistive technology, in particular indoor navigation for people who are blind or have low vision.

Education

  1. Current – Present

    Ph.D. in Computer Science

    University of Maryland, Baltimore County

    GPA: 3.78/4.00

    • Advisor: Dr. Tim Oates
    • Research focus: multimodal AI systems for assistive technologies
    • Expected May 2028

  2. –

    M.S. in Computer Science

    University of Maryland, Baltimore County

    GPA: 3.78/4.00

    • Coursework: Advanced Algorithms, Knowledge Graphs, Machine Learning, Computer Vision, Data Privacy

  3. –

    M.Sc. in Applied Informatics

    Istanbul Technical University, Turkey

    GPA: 3.75/4.00

    • Coursework: Image Processing, Applied Informatics in Structural Biology, Fuzzy Logic

  4. –

    B.Sc. in Computer Science

    University of Tabriz, Iran

    GPA: 3.11/4.00

Research experience

  1. Current – Present

    CORAL Lab, UMBC

    Researcher · Advisor: Tim Oates

    Baltimore, MD

    • Developing a multi-task network for segmenting and classifying medical images on imbalanced datasets
    • Leading InVLM accessible indoor navigation research with Prof. Tim Oates (project notes)
    • Principal Investigator, UMBC IRB Protocol #1743 (Expedited, approved May 2025)

  2. –

    Tubitak 1001 (Grant #119E578)

    Research Assistant · Supervisor: Devrim Unay

    Izmir, Turkey

    Project: Image processing and machine learning tools for phase-contrast optical microscopy time series

    • Analyzed cell morphology and movement in phase-contrast optical microscopy time series
    • Designed an auto-encoder that sped up training, improved tracking robustness, and reduced overfitting on segmentation and tracking

  3. –

    Arcelik Global Co.

    Researcher · Supervisor: Nazim Kemal Ure

    Istanbul, Turkey

    Project: Optimization of Multi-Task Network on Surveillance Cameras

    • Quantized a multi-task model for edge devices, raising inference from 2 fps to 18 fps

    Project: Model Compression for Efficient Video Processing on Edge Devices

    • Built a multi-task people-monitoring network for surveillance cameras on edge devices
    • Compressed the models with quantization, using Intel OpenVINO

  4. –

    Vodafone FutureLab

    Research Fellowship · Supervisor: Mehmet Basaran

    Istanbul, Turkey

    • Introduced Res-VGAE, a variational graph auto-encoder with residual connections
    • Proposed dynamic Word2Vec to examine social structure of Vodafone customers

  5. –

    SP4CING Lab

    Research Assistant · Co-Advisors: Behcet Ugur Toreyin and Devrim Unay

    Istanbul, Turkey

    • Introduced an auto-encoder with a modified ResNet-18 encoder

  6. –

    SiMiT Lab

    Researcher (Unpaid) · Supervisor: Hazim Kemal Ekenel

    Istanbul, Turkey

    Project: Kaggle Dog Breeds Identification with transfer learning

    • Fine-tuned ImageNet-pretrained models for the Kaggle dog-breed identification dataset

    Project: Google Cloud YouTube-8M Video Understanding Challenge

    • Examined deep neural networks with skip connections for the Kaggle video understanding challenge

Publications

Journal articles and book chapters

  1. Reyhan Kevser Keser, Aydin Ayanzadeh, Omid Abdollahi Aghdam, Çağlar Kılcıoğlu, Behçet Uğur Töreyin, and Nazım Kemal Üre. PURSUhInT: In Search of Informative Hint Points Based on Layer Clustering for Knowledge Distillation. Expert Systems with Applications, vol. 213, 119040, 2023.
  2. Yusuf Sait Erdem, Aydin Ayanzadeh, Berkay Mayalı, Muhammed Balıkçi, Özge Nur Belli, Mahmut Uçar, Özden Yalçın Özyusal, Devrim Pesen Okvur, Sevgi Önal, Kenan Morani, Leonardo Obinna Iheme, Behçet Uğur Töreyin, and Devrim Ünay. Automated analysis of phase-contrast optical microscopy time-lapse images: application to wound healing and cell motility assays of breast cancer. In Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods, pp. 137-154, Academic Press, 2023.
  3. Aydin Ayanzadeh, Özden Yalçın Özuysal, Devrim Pesen Okvur, Sevgi Önal, Behçet Uğur Töreyin, and Devrim Ünay. Improved cell segmentation using deep learning in label-free optical microscopy images. Turkish Journal of Electrical Engineering and Computer Sciences, vol. 29, no. 8, pp. 2855-2868, 2021.

Conference and workshop papers

  1. Aydin Ayanzadeh and Tim Oates. Characterizing an On-Device Depth-Aware Multimodal Workload in Assistive Navigation for Blind and Low-Vision Users. IEEE International Symposium on Workload Characterization (IISWC) 2026.
  2. Aydin Ayanzadeh and Tim Oates. LLM-Guided Agentic Floor Plan Parsing for Accessible Indoor Navigation of Blind and Low-Vision People. CVPR 2026 Workshop (GRAIL-V) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops.
  3. Aydin Ayanzadeh, Prakhar Dixit, Sadia Kamal, and Milton Halem. WildfireVLM: AI-Powered Analysis for Early Wildfire Detection Using Satellite Imagery. IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2026.
  4. Aydin Ayanzadeh and Tim Oates. Floorplan2Guide: LLM-Guided Floorplan Parsing for BLV Indoor Navigation. 2025 IEEE International Conference on Big Data (BigData).
  5. Aydin Ayanzadeh, Özden Yalçın Özuysal, Devrim Pesen Okvur, Sevgi Önal, Behçet Uğur Töreyin, and Devrim Ünay. Deep Learning based Segmentation Pipeline for Label-Free Phase-Contrast Microscopy Images. 2020 28th Signal Processing and Communications Applications Conference (SIU), pp. 1-4, IEEE, 2020.
  6. Reyhan Kevser Keser, Indrit Nallbani, Nurullah Çalık, Aydin Ayanzadeh, and Behçet Uğur Töreyin. Graph Embedding For Link Prediction Using Residual Variational Graph Autoencoders. 2020 28th Signal Processing and Communications Applications Conference (SIU), pp. 1-4, IEEE, 2020.
  7. Aydin Ayanzadeh, Hüseyin Onur Yağar, Özden Yalçın Özuysal, Devrim Pesen Okvur, Behçet Uğur Töreyin, Devrim Ünay, and Sevgi Önal. Cell Segmentation of 2D Phase-Contrast Microscopy Images with Deep Learning Method. 2019 Medical Technologies Congress (TIPTEKNO), pp. 1-4, IEEE, 2019.
  8. Rıfkı Can Binici, Umut Şahin, Aydin Ayanzadeh, Behçet Uğur Töreyin, Sevgi Önal, Devrim Pesen Okvur, Özden Yalçın Özuysal, and Devrim Ünay. Automated Segmentation of Cells in Phase Contrast Optical Microscopy Time Series Images. 2019 Medical Technologies Congress (TIPTEKNO), pp. 1-4, IEEE, 2019.
  9. Aydin Ayanzadeh, Hossein Pourghaemi, and Yousef Seyfari. A Modified Ant colony Based Approach to Digital Image Edge Detection. 2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI), pp. 504-509, IEEE, 2015.
  10. Safar Irandoust-Pakchin, Aydin Ayanzadeh, and Siamak Beikzadeh. Gaussian Three-Dimensional kernel SVM for Edge Detection Applications. International Conference on New Research Findings in Electrical Engineering and Computer Science, Tehran, 2015 · arXiv:1710.01260.

Preprints

  1. Miguel Esparza, Aydin Ayanzadeh, Ahmad Mousavi, and Ali Mostafavi. Modular Deep Learning Mechanisms for Auditable Next-Day Wildfire Spread Prediction. Under review · arXiv preprint arXiv:2609.17763 (2026) (under review).
  2. Indrit Nallbani, Aydin Ayanzadeh, Reyhan Kevser Keser, Nurullah Çalık, and Behçet Uğur Töreyin. Representation learning using graph autoencoders with residual connections. arXiv preprint arXiv:2105.00695 (2021).
  3. Aydin Ayanzadeh, Shokoufeh Yazdanian, and Ehsan Shahamatnia. A New Class of Scaling Matrices for Scaled Trust Region Algorithms. arXiv preprint arXiv:1904.09209 (2019).
  4. Aydin Ayanzadeh and Sahand Vahidnia. Modified Deep Neural Networks for Dog Breeds Identification. Preprints (2018), doi:10.20944/preprints201812.0232.v1.

Abstracts, figures and BibTeX are in the publication library.

Talks and posters

  1. Aydin Ayanzadeh, Prakhar Dixit, Sadia Kamal, Milton Halem. WildfireVLM: AI-Powered Analysis for Early Wildfire Detection Using Satellite Imagery. IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2026. Slides (PDF)
  2. Aydin Ayanzadeh, Tim Oates. LLM-Based Indoor Navigation System for Individuals with Blindness or Low Vision. STARS Celebration Conference 2024; CMD-IT/ACM Richard Tapia Conference 2025. Poster.

Teaching

Graduate Teaching Assistant, University of Maryland, Baltimore County · Spring 2022 – Present

  • CMSC 313Computer Organization and Assembly Language ProgrammingSpring 2025, Fall 2024, Spring 2024, Spring 2022
  • CMSC 104Problem Solving & ProgrammingSummer 2024
  • CMSC 433Scripting LanguagesSummer 2024
  • CMSC 671Principles of Artificial IntelligenceFall 2023
  • CMSC 304Social & Ethical Issues in ITSummer 2023
  • CMSC 691Introduction to Data ScienceSpring 2023, Fall 2022
  • CMSC 341Data StructuresSummer 2022
  • Supported undergraduate and graduate sections across systems, AI, data science, scripting, ethics, and intro programming
  • Ran labs and discussion support, held office hours, and graded assignments and exams

Honors and awards

  • International Alumni Endowed Scholarship University of Maryland, Baltimore County (UMBC), USA
  • Research Fellowship Vodafone FutureLab, Turkey
  • Top 1% Ranking Nationwide Universities Entrance Exam, Iran

Certificates

  • AI for Medicine (3-course specialization), deeplearning.ai on Coursera
  • Deep Learning (5-course specialization), deeplearning.ai on Coursera
  • Image and Video Processing, Duke University on Coursera
  • Generative Adversarial Networks (GANs), DeepLearning.AI
  • Digital Image and Video Processing, Northwestern University

Service and memberships

Journal reviewer

  • Expert Systems with Applications ElsevierJan 2024
  • Neurocomputing ElsevierNov 2024
  • Scientific Reports NatureMay 2024
  • Multimedia Systems Springer NatureMay 2024
  • International Journal of Machine Learning & Cybernetics Springer NatureJune 2024
  • Signal Processing: Image Communication ElsevierJune 2024

Memberships

  • IEEE Graduate Student Member (since 2022)
  • ACM Graduate Student Member (since 2022)
  • AccessComputing Member (since 2023)

Leadership

  • Orientation Advisor, UMBC (present)
  • Secretary of the Scientific Association, Computer Science Department, University of Tabriz (2014–2015)
  • Executive Secretary, International Symposium on Computer Science and Software Engineering, University of Tabriz (2015)

Technical skills

Languages
Python · MATLAB · C/C++ · SQL
Frameworks & libraries
PyTorch · TensorFlow · Keras · OpenCV · Scikit-Learn · Pandas · NumPy · Hugging Face Transformers · PyTorch Lightning · ONNX
Tools & platforms
Git/GitHub · Google Cloud Platform · AWS · Linux · ImageJ/Fiji · Docker · Jupyter

Languages

English (fluent) · Turkish (fluent) · Persian (native) · Azerbaijani (native)