Nithin Kodipyaka

Analyzed consumer behavior and market trends to provide actionable insights and streamline business processes for enhanced operational efficiency and strategic decision-making.

• Analyzed consumer behavior using Power BI and Excel, providing actionable insights that enhanced operations and KPI dashboards.
• Conducted comprehensive market and financial research to support strategic decision-making through data gathering, synthesis, and interpretation.
• Coordinated with cross-functional teams to streamline business processes, managing SOP workflows and suggesting improvements.

Developed and refined predictive models for taxi trip duration and inventory forecasting, applying robust data processing and statistical methodologies.

• Built predictive models for taxi trip duration and inventory forecasting using TensorFlow, Python, and SQL, yielding accurate results through data processing.
• Conducted rigorous model training, cross-validation, and performance evaluation, meticulously analyzing errors and implementing problem-solving fixes.
• Applied advanced data transformation, feature engineering, and statistical methods using SAS and Python, adhering to standard operating procedures.

Represented IIT Delhi's annual technical festival, promoting events and engaging with students to foster participation.

• Promoted TRYST'23 events and initiatives to a broad student audience, increasing awareness and engagement.
• Facilitated communication between the organizing committee and student body, ensuring smooth information flow.
• Contributed to the successful outreach and participation goals of one of India's largest technical festivals.

Acted as a campus representative for Internshala, connecting students with internship opportunities and career resources.

• Guided peers on leveraging Internshala's platform for career development and internship searches.
• Organized workshops and promotional activities to raise awareness about available opportunities.
• Facilitated student engagement with Internshala, contributing to increased platform usage and successful placements.

Managed merchandise and marketing efforts for VIT's technical and cultural festivals, enhancing brand visibility and attendee experience.

• Coordinated the design, production, and distribution of merchandise for TechnoVIT and Vibrance'23.
• Executed marketing strategies to promote merchandise sales and festival attendance.
• Collaborated with various teams to ensure cohesive branding and successful event promotion.

Analyzed underwater acoustic data using signal processing techniques to differentiate shrimp feeding sounds from insect noise.

Designed CNN-based deep learning models using TensorFlow and Keras to create explainable AI for enhanced lung cancer diagnosis.

Engineered a real-time campus surveillance system utilizing computer vision for face recognition and ID card detection to enhance security.

Created a semantic retrieval and reasoning engine (RAG) using PyTorch, FAISS, and LLaMA 3.2B for advanced text data labeling and personalized recommendations.

Secured a position in the top 10 teams for the Drone-based Intelligent Magnetic Sensing and Metallic Anomaly Detection - SIH1414.

Granted patent for a novel system and method facilitating personalized cross-domain recommendations, published in The Official Journal of The Patent Office.

Awarded for outstanding academic performance and overall proficiency.

Comprehensive research on customer behavior analysis and predictive modeling techniques applied to supermarket retail environments.

Introduced a novel Z-K-R framework for intrusion detection systems, enhancing security through advanced techniques.