I am a researcher in analytic number theory, specializing in the theory of automorphic forms and L-functions. My research focuses on deep arithmetic properties of modular forms, Hecke eigenforms, and their connections to Galois representations and twisted L-functions. I have contributed to proving results related to the sign changes in Fourier coefficients, non-vanishing properties of shifted products, and the infinitude of zeros in Koecher–Maass series. My research also explores the interplay between modular forms, representation theory, and algebraic geometry, revealing new insights into long-standing problems in number theory.

For the past five years, I have been working as a Professor of Mathematics, teaching and mentoring students in various mathematical disciplines, ranging from abstract algebra and topology to advanced topics in number theory and analysis. My goal has been to inspire curiosity in mathematical research and provide deep theoretical insights into fundamental problems in modern mathematics.

Recently, I have developed a strong interest in Machine Learning and Data Science and am actively exploring applications of mathematical principles in ML and Deep Learning. My expertise in mathematics, optimization, and probabilistic modeling provides me with a strong foundation for transitioning from academia to industry. I am particularly interested in areas like Bayesian Deep Learning, and optimization techniques.

I am currently preparing to enter the industry, leveraging my skills in ML, DL, and mathematical modeling to solve real-world problems. I am proficient in statistical learning, distributional regression, uncertainty quantification, and hybrid AI algorithms. My focus is on machine learning applications in finance, healthcare, and AI-driven automation.

• 🌍 I'm based in Delhi
• ✉️ You can contact me at manishmmat0906@gmail.com
• 🧠 I'm learning Reinforcement learning (RL) and Stochastic calculus
• 🤝 I'm open to collaborating on Any real life problems realted finance such as interest rate, option pricing, and understanding different models

• Expertise: Analytic Number Theory, Modular Forms, Automorphic Representations, L-functions
• Published Research: Multiple papers in top journals on sign changes in Fourier coefficients, non-vanishing results, and SLAM applications
• Years of Teaching: 5+ years as a Mathematics Professor
• Workshops Conducted: 150+ students trained in mathematical methods and Python for research

• Applications: Bayesian Deep Learning, AI for Healthcare, Patent Search Optimization, SLAM & LiDAR
• Transitioning to Industry: Applying ML/DL techniques in finance, healthcare, and AI-driven solutions
• Technical Stack: Python, PyTorch, TensorFlow, Scikit-Learn, Bayesian Models, GANs, Vision Transformers
• Ongoing Work: Building a Grey Wolf Optimization-based AI agent for patent analysis

• Ph.D. in Mathematics with focus on Automorphic Forms & L-functions
• Journal Reviewer & Research Fellow Memberships
• Research Collaborations: Interdisciplinary projects spanning mathematics, AI, and scientific computing
• HPC & GPU Computing: Using an 80GB NVIDIA 4080 GPU for deep learning research

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