Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

Aspiring AI Engineer with hands-on experience in Python development and a strong interest in Agentic AI systems. Skilled in building automation tools, integrating APIs, and exploring emerging AI technologies. Currently expanding knowledge in generative AI models and voice communication protocols like SIP trunking. Passionate about creating intelligent systems that bridge web research, email integration, and conversational AI. Eager to contribute to innovative projects that push the boundaries of AI capabilities.…Aspiring AI Engineer with hands-on experience in Python development and a strong interest in Agentic AI systems. Skilled in building automation tools, integrating APIs, and exploring emerging AI technologies. Currently expanding knowledge in generative AI models and voice communication protocols like SIP trunking. Passionate about creating intelligent systems that bridge web research, email integration, and conversational AI. Eager to contribute to innovative projects that push the boundaries of AI capabilities.

shahidiani13788195

Add your roles





Aspiring AI Engineer with hands-on experience in Python development and a strong interest in Agentic AI systems. Skilled in building automation tools, integrating APIs, and exploring emerging AI technologies. Currently expanding knowledge in generative AI models and voice communication protocols like SIP trunking. Passionate about creating intelligent systems that bridge web research, email integration, and conversational AI. Eager to contribute to innovative projects that push the boundaries of AI capabilities.…Aspiring AI Engineer with hands-on experience in Python development and a strong interest in Agentic AI systems. Skilled in building automation tools, integrating APIs, and exploring emerging AI technologies. Currently expanding knowledge in generative AI models and voice communication protocols like SIP trunking. Passionate about creating intelligent systems that bridge web research, email integration, and conversational AI. Eager to contribute to innovative projects that push the boundaries of AI capabilities.

Available to hire

Aspiring AI Engineer with hands-on experience in Python development and a strong interest in Agentic AI systems. Skilled in building automation tools, integrating APIs, and exploring emerging AI technologies. Currently expanding knowledge in generative AI models and voice communication protocols like SIP trunking. Passionate about creating intelligent systems that bridge web research, email integration, and conversational AI. Eager to contribute to innovative projects that push the boundaries of AI capabilities.

Skills

Python

Experience Level

Python

Expert

Work Experience

Add your work experience history here.

Education

Bachelor of computer engineering at Shahrood university of technology

September 21, 2018 - January 2, 2023

Master's degree at Bologna university

September 7, 2024 - March 2, 2025

Now I am a student in the field of artificial intelligence at Bologna University

Qualifications

Deep learning specialization

June 1, 2022 - September 14, 2022

Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow Build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data Build and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering

Industry Experience

Software & Internet

Question Answering

Perform extractive Question Answering Fine-tune a pre-trained transformer model to a custom dataset Implement a QA model in TensorFlow and PyTorch Problem Statement: Question answering (QA) is a task of natural language processing that aims to automatically answer questions. The goal of extractive QA is to identify the portion of the text that contains the answer to a question. For example, when tasked with answering the question 'When will Jane go to Africa?' given the text data 'Jane visits Africa in September', the question answering model will highlight 'September'.…Perform extractive Question Answering Fine-tune a pre-trained transformer model to a custom dataset Implement a QA model in TensorFlow and PyTorch Problem Statement: Question answering (QA) is a task of natural language processing that aims to automatically answer questions. The goal of extractive QA is to identify the portion of the text that contains the answer to a question. For example, when tasked with answering the question 'When will Jane go to Africa?' given the text data 'Jane visits Africa in September', the question answering model will highlight 'September'.

Programmer

Art Generation with Neural Style Transfer

Implement the neural style transfer algorithm Generate novel artistic images using your algorithm Problem Statement: Neural Style Transfer (NST) is one of the most fun techniques in deep learning. As seen below, it merges two images, namely: a "content" image (C) and a "style" image (S), to create a "generated" image (G). The generated image G combines the "content" of the image C with the "style" of image S.…Implement the neural style transfer algorithm Generate novel artistic images using your algorithm Problem Statement: Neural Style Transfer (NST) is one of the most fun techniques in deep learning. As seen below, it merges two images, namely: a "content" image (C) and a "style" image (S), to create a "generated" image (G). The generated image G combines the "content" of the image C with the "style" of image S.

Programmer

Face Recognition

Differentiate between face recognition and face verification Implement one-shot learning to solve a face recognition problem Apply the triplet loss function to learn a network's parameters in the context of face recognition Explain how to pose face recognition as a binary classification problem Map face images into 128-dimensional encodings using a pretrained model Perform face verification and face recognition with these encodings Problem statement: Face recognition problems commonly fall into one of two categories: Face Verification "Is this the claimed person?" For example, at some airports, you can pass through customs by letting a system scan your passport and then verifying that you (the person carrying the passport) are the correct person. A mobile phone that unlocks using your face is also using face verification. This is a 1:1 matching problem. Face Recognition "Who is this person?" For example, the video lecture showed a face recognition video of Baidu employees entering the office without needing to otherwise identify themselves. This is a 1:K matching problem…Differentiate between face recognition and face verification Implement one-shot learning to solve a face recognition problem Apply the triplet loss function to learn a network's parameters in the context of face recognition Explain how to pose face recognition as a binary classification problem Map face images into 128-dimensional encodings using a pretrained model Perform face verification and face recognition with these encodings Problem statement: Face recognition problems commonly fall into one of two categories: Face Verification "Is this the claimed person?" For example, at some airports, you can pass through customs by letting a system scan your passport and then verifying that you (the person carrying the passport) are the correct person. A mobile phone that unlocks using your face is also using face verification. This is a 1:1 matching problem. Face Recognition "Who is this person?" For example, the video lecture showed a face recognition video of Baidu employees entering the office without needing to otherwise identify themselves. This is a 1:K matching problem

Programmer

Gradient Checking

result of the project: Implement gradient checking to verify the accuracy of your backprop implementation Problem Statement: You are part of a team working to make mobile payments available globally, and are asked to build a deep learning model to detect fraud--whenever someone makes a payment, you want to see if the payment might be fraudulent, such as if the user's account has been taken over by a hacker. You already know that backpropagation is quite challenging to implement, and sometimes has bugs. Because this is a mission-critical application, your company's CEO wants to be really certain that your implementation of backpropagation is correct. Your CEO says, "Give me proof that your backpropagation is actually working!" To give this reassurance, you are going to use "gradient checking."…result of the project: Implement gradient checking to verify the accuracy of your backprop implementation Problem Statement: You are part of a team working to make mobile payments available globally, and are asked to build a deep learning model to detect fraud--whenever someone makes a payment, you want to see if the payment might be fraudulent, such as if the user's account has been taken over by a hacker. You already know that backpropagation is quite challenging to implement, and sometimes has bugs. Because this is a mission-critical application, your company's CEO wants to be really certain that your implementation of backpropagation is correct. Your CEO says, "Give me proof that your backpropagation is actually working!" To give this reassurance, you are going to use "gradient checking."

Programmer

Hire a Freelancer

We have the best experts on Twine. Hire a freelancer in Bologna today.

Find a Freelancer