Exploration of Generative Adversarial Networks (GANs): Conducted in-depth studies and experiments on GANs, contributing to advancements in image generation and unsupervised learning.Investigated Reinforcement Learning Algorithms: Developed and tested new reinforcement learning algorithms for optimization problems, enhancing decision-making processes in dynamic environments.Collaboration on Multi-Agent Systems: Collaborated with experts to advance the understanding and development of multi-agent systems

Worked there as a generative AI engineer and, after one month, was promoted to lead generative AI engineer. Developed a strategic plan for the next 2 years of development, aligning with recent generative AI industry trends. Managed their cloud platforms (AWS, Azure) and reduced the cost and increased productivity by utilizing many innovative GenAI technologies.- Revolutionized podcast creation with an advanced prompt-to-podcast service combining bark TTs, elevenlabs, GPT-4o, and LangChain LCEL; boosted production efficiency by 85%, generating high-quality podcasts in 3 minutes- Created an AI auto email reply agent service using CrewAI and live data-based tweet generation and 10+ others service, Scaled cost using langsmith and other toolsImplemented custom diffusion-based models with a 93.3% accuracy rate and fine-tuned them using LORA, enhancing performance and precision.- Delivered scalable and cost-effective AI solutions utilizing new technologies, and led the team in managing all related projects and initiatives.

Developed Custom Python-Based Telegram Bots: Designed and sold customized Telegram bots for various purposes, including automation, customer support, and engagement, enhancing client communication and interaction.Created Dynamic Websites Using Django and Flask: Built and deployed dynamic, responsive websites for clients using Django and Flask frameworks, ensuring robust back-end functionality and seamless user experiences.Optimized and Improved Existing Codebases: Analyzed, refactored, and optimized existing Python codebases, enhancing performance, maintainability, and scalability of client projects.Integrated APIs and Third-Party Services: Successfully integrated various APIs and third-party services into client applications, enabling enhanced functionality and interoperability.Automated Business Processes with Python Scripts: Developed and implemented Python scripts to automate repetitive business processes, saving clients time and increasing operational efficiency.Provided Technical Support and Consultation: Offered expert consultation and ongoing technical support for Python-related projects, ensuring client satisfaction and successful project delivery.Developed Data Analysis and Visualization Tools: Created custom data analysis and visualization tools using Python libraries such as Pandas, NumPy, and Matplotlib, aiding clients in making data-driven decisions.Implemented Machine Learning Solutions: Built and deployed machine learning models to solve client-specific problems, utilizing libraries like Scikit-learn, TensorFlow, and PyTorch.Ensured High Code Quality and Best Practices: Adhered to coding best practices, including writing clean, well-documented code and performing thorough testing to ensure high-quality deliverables.Customized E-commerce Solutions: Developed and customized Python-based e-commerce solutions, integrating payment gateways, inventory management, and user authentication systems to meet client needs.

Developed a facial recognition and emotion detection system using OpenCV, YOLO V9, PyTorch, Keras, and NumPy, achieving an accuracy rate of 95.4%.Trained a classifier with Scikit-learn, using K-means Clustering, SVM, and Random Forest on extracted features, improving prediction success rate by 71.2%.

Developed an AI Desktop Assistant for the company CEO using Python, NumPy, Open AI, and Bard AIAdded more than 20+ features including generative voice assistant that learns from feedback, auto remainder and auto email writer.Utilized prompt engineering technologies to optimize AI model performance, reducing token usage and enhancing response accuracy.Integrated IoT devices with AI systems for real-time data collection and analysis, contributing to more informed decision-making processes.Optimized cloud resource usage, achieving significant cost savings while maintaining high performance of AI systems.