* Python/C++: Built low-latency ML models (e.g., EV range prediction at Trickce, 92% accuracy) and optimized algorithms (40% speedup in Brain Tumor Segmentation, LOR Nihar.Rhythm Agrawal.pdf ).
* Quantitative Modeling: Statistical analysis of socio economic drivers of Kala Azar Disease (logistic regression) and derivatives pricing coursework (Columbia Financial Engineering certification, Certificates_List_Nihar_Mahesh_Jani.docx ).
* Internships: Researched accessible tech solutions (Birmingham City University, BCU Offer Letter.pdf ) and engineered computer vision pipelines (Kalindi Engineering).
3. Academic Rigor:
* I scored an impressive 99.17th percentile in JEE Mains Mathematics( LETTER OF RECOMMENDATION-Nihar.pdf ), ranking among the top 0.83 percentile out of 12 lakh students. This achievement is particularly noteworthy as JEE Mains serves as a crucial entrance exam for prestigious NITs and IITs. Additionally, I have secured certifications in Machine Learning from Stanford University and have completed coursework in Applied Linear Algebra, Probabilistic Graphical Models, and Human-Computer Interaction (HCI).
I also possess excellent communication and teamwork skills. I served as the Secretary of the IEEE Ahmedabad University Student Branch for a year, from March 1, 2023, to March 2024. During my tenure, I spearheaded events related to Artificial Intelligence (AI), Machine Learning (ML), Cybersecurity, Deep Learning, Internet of Things (IoT), and career-related services. Additionally, I invited renowned personalities for their prestigious talks. Furthermore, I worked at two Non-Governmental Organizations (NGOs): Green Bhumi Foundation and Prabhat Education Foundation.
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