Soheil Koohi Email & Phone Number
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Soheil Koohi is listed as Technical Team Lead at Snapp!, a with 949 employees, based in Iran, Islamic Republic of. AeroLeads shows a matched LinkedIn profile for Soheil Koohi.
Soheil Koohi previously worked as Senior Computer Vision Engineer at Neoxi and Head of Machine Learning at Uvea. Soheil Koohi holds Bachelor’S Degree, Electrical And Electronics Engineering from University Of Tehran.
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About Soheil Koohi
With a distinctive blend of technical proficiency and strategic understanding, I am a seasoned Computer Vision and Deep Learning Engineer who goes beyond merely developing high-performance Machine Learning and Computer Vision models. I delve deep into the specific needs of a project, ensuring alignment between the envisioned goals and technical execution.Leveraging my expertise in TensorFlow, PyTorch, and other pivotal ML tools, I devise testable, maintainable solutions that serve as the backbone for data preparation and model training. I am skilled at refining and fine-tuning models to optimal performance, employing a meticulous approach and a keen eye for detail.I possess comprehensive knowledge of MLOps and deployment tools such as TensorRT, TFLite, TFX, KubeFlow, and DeepStream, which I utilize to deploy models on Edge Devices or Cloud Services. Balancing technical insight with a human-centric approach, I'm passionate about empowering individuals and businesses to solve their most pressing challenges in Computer Vision.But my contributions are not confined to the technical side alone. Recognizing the paramount importance of effective communication in the tech industry, I act as a bridge between technical and non-technical stakeholders. I have a proven track record in articulating complex technical scenarios, aiding talents in highlighting their competencies, and assisting hiring managers in navigating the intricacies of Computer Vision.
Listed skills include Algorithms, C, Lean Startup, Matlab, and 15 others.
Soheil Koohi's current company
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Soheil Koohi work experience
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Senior Computer Vision Engineer
At Neoxi, I've been pivotal in driving a computer vision project aimed at bolstering the security of various facilities. My contributions spanned from creating innovative multi-camera object tracking and tiny object detection functionalities to maintaining a bird's-eye view of the project's needs.I orchestrated the development of an extensive MLOps pipeline, thereby streamlining data labeling, ongoing training, and assessment of the object tracker and detector models. This rigorous approach facilitated the continuous improvement of our models, ensuring they stayed relevant and consistently delivered peak performance.Taking the helm during deployment, I oversaw the integration of our final models into the customer's existing infrastructure. I meticulously ensured seamless deployment on each client's device while prioritizing compatibility and efficient execution. My holistic understanding of project needs and technical prowess led to effective solutions that not only met but often exceeded project requirements.
Head Of Machine Learning
I joined UVEA as a remote Machine Learning Engineer and worked on Computer Vision applications for edge devices like Edge-TPU and Nvidia Jetson Family. After a few months, I was promoted to Computer Vision Team Lead. In our team, we worked on diverse computer vision projects, including:• Social Distancing Detection: Developed an AI-assisted application to detect social distancing violations in real-time using CCTV cameras. We utilized TensorFlow's SSD MobileNet V2 object detector, calculated distances between people, and deployed the model on Edge-TPU and Jetson devices. This AI engine was embedded in a SaaS product using Docker and Kubernetes. This product provides a panel to configure the cameras and models and render output video footage.• Face Mask Detection: UVEA's Face Mask Detector applies state-of-the-art computer vision algorithms to detect if people are wearing a face mask or not. To reach an accurate model that can work with cheap and low-quality cameras, we gathered a comprehensive dataset. Then tried multiple approaches to detect the faces in a scene and applied many experiments and training in TensorFlow that led us to a model with high accuracy. The final engine has been containerized using Docker.• Real-Time Pose Estimation on Edge: We optimized a PyTorch-based pose estimation model for deployment on Jetson edge devices using TensorRT. This optimized model outperforms existing solutions when applied to real-world CCTV data. Additionally, we designed an Edge-friendly pose estimation architecture in TensorFlow and trained it using the COCO dataset, further enhancing its performance and versatility.• Label-Free Object Detection Engine: UVEA offers the Label-Free Edge vision API, a service that allows for the training of specialized models tailored to specific environments. This SaaS product was deployed on AWS, utilizing Docker and Docker Compose to ensure seamless delivery of the AI engine.
Machine Learning Consultant
Fanavard is an HR and recruitment company focused on connecting job seekers with suitable job positions. With a team comprising highly talented employees, the company aimed to empower its workforce by incorporating AI and ML concepts and tools into their skill set.During my time at Fanavard, I held the role of AI mentor for a group of young, gifted employees. Together, we tackled several company challenges, one of which involved developing a job position recommendation system for job seekers. Leveraging Keras and NLTK, we successfully designed and implemented an effective solution that provided personalized job recommendations based on individual preferences and qualifications.Through this project and my mentorship, I helped foster a deeper understanding of AI and ML among the employees, equipping them with the knowledge and expertise to tackle complex business problems. By integrating AI and ML into Fanavard's operations, we enhanced their recruitment processes and optimized the job matching experience for job seekers, ultimately leading to greater efficiency and satisfaction for all parties involved.
Computer Vision Engineer
At IREEN, I took the lead in developing an innovative automated real estate price estimation service using state-of-the-art deep learning techniques. As the principal architect of the project's AI engine, I had a varied range of responsibilities. This began with data collection from diverse sources like Google Maps and Google Street View and transitioned into designing and implementing robust models utilizing TensorFlow.Throughout this process, an iterative cycle of experimentation and refinement allowed us to fine-tune these models for superior accuracy and performance. Our AI-driven service consistently outperformed conventional methods and produced remarkably precise estimations.One of our team's proudest accomplishments was the successful deployment of the final model on the Google Cloud platform. This milestone signaled a notable achievement for our nascent startup venture, IREEN. Presently, the project is in the fundraising phase, and we are continually working towards its advancement. Given its promising trajectory, IREEN is well-positioned for future growth and success.
Co-Founder
Bamboo is a data analytics platform for marketing companies to monitor and manage their marketers performance.
Machine Learning And System Identification Researcher
At ISENSE, a prominent structure's health monitoring company, my primary responsibility was to create state-of-the-art data-driven models for diverse structures, such as bridges and gas pipelines. By leveraging advanced methodologies like subspace identification and Transfer Function identification methods, I successfully predicted their behavior in response to seismic activities, bolstering the overall understanding of their performance and ensuring enhanced safety measures.In addition to my technical role, I also took charge of training employees who lacked a background in data science. I effectively conveyed complex data science concepts and methodologies to enable them to contribute confidently to our projects. Through my guidance, four individuals acquired valuable skills that empowered them to excel in their roles within the company.
Research Assistant
Teacher Assistant
I was teaching assistant in various courses each semester such as Engineering Mathematics,Signals and Systems,Communication systems.
Colleagues at Snapp!
Other employees you can reach at snapp.ir. View company contacts for 949 employees →
Parisa Abchehr
Colleague at Snapp!Tehran Province, Iran, Islamic Republic Of
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Mohammadsajjad Hafizi
Colleague at Snapp!Iran, Islamic Republic Of
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Omid Afraki
Colleague at Snapp!Iran, Islamic Republic Of
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Saeed Chaman
Colleague at Snapp!South West Community Development Council, Singapore
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Lida Sadr
Colleague at Snapp!Iran, Islamic Republic Of
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Homy Tab
Colleague at Snapp!Iran, Islamic Republic Of
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Benyamin Khodadadi
Colleague at Snapp!Karaj, Alborz Province, Iran, Islamic Republic Of
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Hanif Habibi
Colleague at Snapp!Alborz Province, Iran, Islamic Republic Of
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Parham Sadri
Colleague at Snapp!Tehran Province, Iran, Islamic Republic Of
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Danial Moafi
Colleague at Snapp!Taverne D’Arbia, Tuscany, Italy
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Soheil Koohi education
Frequently asked questions about Soheil Koohi
Quick answers generated from the profile data available on this page.
What company does Soheil Koohi work for?
Soheil Koohi works for Snapp!.
What is Soheil Koohi's role at Snapp!?
Soheil Koohi is listed as Technical Team Lead at Snapp!.
Where is Soheil Koohi based?
Soheil Koohi is based in Iran, Islamic Republic of while working with Snapp!.
What companies has Soheil Koohi worked for?
Soheil Koohi has worked for Snapp!, Neoxi, Uvea, Fanavard, and Ireen.
Who are Soheil Koohi's colleagues at Snapp!?
Soheil Koohi's colleagues at Snapp! include Parisa Abchehr, Mohammadsajjad Hafizi, Omid Afraki, Saeed Chaman, and Lida Sadr.
How can I contact Soheil Koohi?
You can use AeroLeads to view verified contact signals for Soheil Koohi at Snapp!, including work email, phone, and LinkedIn data when available.
What schools did Soheil Koohi attend?
Soheil Koohi holds Bachelor’S Degree, Electrical And Electronics Engineering from University Of Tehran.
What skills is Soheil Koohi known for?
Soheil Koohi is listed with skills including Algorithms, C, Lean Startup, Matlab, Tensorflow, Data Analytics, Digital Marketing, and Signal Processing.
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