Designed and implemented machine learning pipelines for feature extraction and model evaluation on structured and unstructured data, supporting research contributions published in venues and workshops associated with ICML, CVPR, ACL, and NeurIPS 2026.

Developed and optimized deep learning architectures, contributing to national R&D projects and research manuscripts under review at leading AI venues, including NeurIPS 2026. Worked with interdisciplinary research teams to design and evaluate AI-based solutions for practical and societal challenges.

Investigated multimodal explainable AI methods by integrating causal reasoning into CNN-based models for improved interpretability and bias analysis. Proposed novel deep learning and computer vision methodologies, including adaptive feature-gated LSTM networks, deep spectral–epipolar representations for dense light-field reconstruction, and hierarchical spatial quantization algorithms for high-resolution imaging.

• Contributed to machine learning research on educational outcomes using large-scale data from 800,000+ marginalized learners; findings supported evidence-based education initiatives in Bangladesh.
• Developed and evaluated machine learning pipelines for early identification of at-risk students, achieving 85% prediction accuracy.
• Assisted in the design of intrusion detection frameworks for educational infrastructure, addressing severe class imbalance in cybersecurity datasets.

Supervised by Tapu Sarwar.

• Founded an early-stage research startup developing explainable AI systems for healthcare and education.
• Secured U.S.–ASEAN STIC and BeVisioneers grants to support prototyping and applied research in interpretable machine learning.

Deployed enterprise ML pipelines on multi-cloud infrastructure, achieving a 25% throughput improvement.

Architected cloud-native AI infrastructure, reducing operational latency by 30%; recognized in the top 0.1% of elite talent.

Best Employment Award (Top 1%); Community Outreach Award (Top 0.1%).

Best Employment Award (Top 1%); Community Outreach Award (Top 0.1%).

Contributed to networking, mentoring, and community-building initiatives during ICML, fostering collaboration and inclusion among researchers in artificial intelligence and machine learning.

Founded and leading an AI startup dedicated to trustworthy artificial intelligence, machine learning research, and the development of innovative AI-driven technologies.

Mentor students, support AI workshops and seminars, and contribute to technical education and community engagement at Istanbul Technical University.

Supported the coordination of international technology events and organizational activities within Türkiye's defence, aerospace, and space ecosystem.

Organized technical workshops, delivered educational talks, mentored students, and promoted artificial intelligence, cloud computing, and open-source technologies.

Selected by Microsoft as a sponsored mentor to provide technical guidance, career mentorship, and project support to participants during North America's largest student hackathon.

Served as a Microsoft-sponsored mentor, advising student teams on artificial intelligence, cloud technologies, software engineering, and hackathon project development.

Led a student team in a citizen science initiative promoting STEM education, space science, scientific outreach, and collaborative research.