I’m Ayush Mishra, a Computer Scientist and AI Researcher based in Bengaluru, India. My research centers on Multimodal Deep Learning, Vision Transformers, and High-Performance Machine Learning Systems for automated information integrity and cross-modal reasoning.
Currently, I serve as an Academic Researcher & Faculty Mentor at Dayananda Sagar College of Engineering (DSCE), Bengaluru (Department of Information Science and Engineering), where I mentor engineering students and guide applied deep learning initiatives.
I completed my M.Tech in CSE (Data Science) at SVNIT Surat (CGPA 8.42/10). My research paper on multimodal fake news detection using BERT–BiGRU and Vision Transformers (ViT-B/16) was accepted and presented at IC2NS2 2026 (Springer), achieving 90.18% accuracy and a 0.9485 ROC-AUC on the Fakeddit benchmark.
Beyond academic research, I design production-grade machine learning pipelines (DVC, MLflow, Docker, FastAPI, AWS) and scalable web platforms including GPUCalc, AllAgeCalculators.com, CalculadoradeIdade.com, and PDFAfy.
Core Research & Engineering Focus
Multimodal Deep Learning & Semantic Alignment
Investigating cross-modal fusion mechanisms connecting dense visual representations (Vision Transformers) with contextual language models (BERT/RoBERTa/LLMs) to detect semantic dissonance, cross-modal discrepancies, and deceptive narratives in multi-source media.
Vision Transformers & Spatial Representation
Analyzing patch-level self-attention dynamics (ViT-B/16, Swin) for dense feature extraction, global spatial reasoning, and transfer learning in computer vision pipelines, benchmarking empirical bounds across large-scale vision-language benchmarks.
High-Performance MLOps & Edge Infrastructure
Architecting modular, reproducible machine learning pipelines utilizing DVC, MLflow, Docker, and FastAPI, coupled with serverless edge runtimes (Cloudflare Workers) engineered for zero-latency execution, localized SEO, and absolute client-side privacy.
