Syed Mohamad Tawseeq
About Me
I am a 3rd-year undergraduate student at the Indian Institute of Technology, Kharagpur, pursuing my bachelor's degree in Chemical Engineering with a minor in Mathematics & Computing, specializing in Artificial Intelligence & Applications. My primary interests lie in Multimodal Learning, with a particular focus on the Reasoning abilities of AI systems. I am keen on exploring how different modalities like text, images, and videos can be integrated for enhanced AI capabilities. As a dedicated student passionate about artificial intelligence, I am eager to embark on a research career focused on advancing reasoning and explainability in AI systems and ensuring their responsible development.
Research Interests
- Artificial Intelligence: Natural Language Processing, Computer Vision, Multimodal Learning, AI Reasoning, Statistical ML
- Mathematics: Probability, Bayesian Statistics, Sequential Analysis, Calculus, Numerical and Complex Analysis
Experience
-
Adobe MDSR Lab
I will be working as a research intern at Adobe MDSR Lab (Media, Data Science, and Research) in Summer 2025.
-
Student Researcher - IIT Kharagpur
Currently working at Tr2AIL research group under the guidance of Professor Somak Aditya to enhance the reasoning capabilities of Multimodal Large Language Models (LLMs) with a specific focus on video interpretation. This project involves developing innovative methodologies for counterfactual reasoning in videos, enabling the models to understand and predict alternate scenarios. The work aims to push the boundaries of how AI can analyze and reason about events in a visual context, opening up new possibilities for applications in various fields.
-
Student Researcher - Nanyang Technological University, Singapore
I worked under the guidance of Dr. Farhan Ali to identify cognitive distortions using Natural Language Processing (NLP). We delved into the realm where language, mental health, and AI intersect. Using a vast Reddit dataset of over 31 million posts and comments, we investigated cognitive distortions among students and teenagers. Our approach involved analyzing patterns in sequences of 1-to-5-grams (n-grams), as outlined in the Bollen paper, through time series analysis, NLP techniques, and LLMs. This project has the potential to reshape our understanding and approach to cognitive distortions in the digital era.
Coursework
Computer Science: Machine Learning Foundations & Applications* (A), Programming & Data Structures* (A), Machine Learning Specialization (O), Deep Learning Specialization (O), Natural Language Processing with Deep Learning (O), Deep Learning for Computer Vision (O)
Math: Linear Algebra, Numerical Analysis, Complex Analysis, Theory of Partial Differential Equations, Advanced Calculus, Transform Calculus
Other Engineering Courses: Computer Aided Process Engineering, Process Control Engineering
[A- Academic, O- Open Source, * Practicum Included]
Contact
You can contact me via my institutional email