Akash Abbigeri
Southampton,STH
Summary
Personable and analytical with a deep understanding of machine learning algorithms and data analysis techniques. Proficient in Python and TensorFlow, with coursework and projects demonstrating capability in developing AI models. Committed to leveraging skills to drive innovative solutions and contribute to cutting-edge projects.
Overview
1
1
Certification
Work History
AI Intern
JMedia Corp.
10.2023 - 02.2024
- Enhanced customer support by 25% by developing a chatbot using Google Gemini API for Q and A prompts.
- Increased accessibility by 15% by incorporating a speech engine for spoken responses in the chatbot.
- Incorporated a speech engine enabling the chatbot to provide responses in speech format.
- Created virtual cloud machines using VMware and Hyper-V to support project requirements.
Education
MSc - Artificial Intelligence
University of Southampton
09.2026
B.Tech - Computer Science and Engineering
Vellore Institute of Technology
06.2025
Skills
- Scikit-learn
- Python programming
- Data analytics
- Machine learning
- Natural language processing
- Sentiment analysis
- Image processing
- Reinforcement learning
- AI ethics awareness
- Deep learning
- Artificial intelligence research
- Neural networks
Certification
- IBM - IBM Data Engineering
- PL100 - Microsoft Power Platform App maker Associate
- GCP - Google Cloud Computing Foundations
- IBM - Enterprise Design Thinking Practitioner.
- NPTEL - Safe and Responsible AI Systems
Timeline
AI Intern
JMedia Corp.
10.2023 - 02.2024
B.Tech - Computer Science and Engineering
Vellore Institute of Technology
MSc - Artificial Intelligence
University of Southampton
Projects
ChirpSense
- Developed a CNN-based model for bird audio classification, improving identification accuracy by 15%.
- Published patent work on enhanced model robustness and conservation impact.
SIMS - Smart Inventory Management Systems
- Optimised stock management using predictive models, reducing holding costs by 15% and improving accuracy by
35%. - Integrated Arduino-based hardware and time-series forecasting for automated sales and inventory control.
Publications
- ChirpSense: A Deep Learning Approach to Automated Bird Song Classification Patent (Feb. 2025)
- Shivam Boda, , Yash Sawrikar
- Application Number: 202541023487
- Predictive Stock Management System: An ML-Based Approach to Inventory Optimization Patent (Feb. 2025)
- Shivam Boda, Akash Abbigeri, Yash Sawrikar
- Application Number: 202541023323
- Classification of Cetacean Species Using Liquid Neural Networks Research Paper (Apr. 2025)
- Hriday Shah, Akash Abbigeri, Dr. Misha Chander, Dr. Abirami
- Fifteenth International Conference on Advances in Computer Engineering (ACE2025)