Harnessing the Power of Deep Learning to Revolutionize Technology
January 22nd, 2024 (CST)
ITM Department, Illinois Institute of Technology, USA
Dr. Omar's Academic career has consistently focused on applied, industry-relevant cyber security, Data Analytics, machine learning, application of AI to cyber security and digital forensics research and education that delivers real-world results. He brings a unique combination of industry experience as well as teaching experience gained from teaching across different cultures and parts of the world. He has an established self-supporting program in machine learning application to cyber security. He has established a respectable research record in AI and cyber security exemplified in the dozens of published papers and book chapters that have gained recognition among researchers and practitioners (more than 272 Google scholar citations thus far). He is actively involved in graduate as well as undergraduate machine learning education including curriculum development and assessment.
Dr. Omar has recently published two books with Springer on Machine Learning and Cyber Security and has also published research with IEEE conference on Sematic Computing. Additionally, Dr. Omar holds numerous industry certifications including Comptia Sec+, ISACA CDPSE, EC-Council Certified Ethical Hacker, and SANS Advanced Smartphone Forensics Analyst.
Dr. Omar has been very active and productive in both academia as well as the industry and he is currently serving as an associate professor of cyber security at Illinois Institute of Technology.
The Deep Learning Workshop is an immersive and comprehensive program designed to introduce participants to the fascinating world of deep learning and its applications. This workshop aims to provide attendees with a solid understanding of the fundamental concepts, techniques, and practical implementation of deep learning algorithms.
During the workshop, participants will embark on a hands-on journey through the foundations of deep learning, exploring topics such as artificial neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). Through a combination of interactive lectures, real-world case studies, and guided coding exercises, attendees will gain the necessary skills to tackle complex problems using deep learning techniques.
The workshop will delve into various aspects of deep learning, including data preprocessing, model architecture design, optimization techniques, and evaluation methodologies. Participants will also learn about popular deep learning frameworks such as TensorFlow and PyTorch, enabling them to build and deploy deep learning models effectively.
By the end of the workshop, participants will have acquired a solid foundation in deep learning, enabling them to leverage neural networks for tasks like image recognition, natural language processing, and recommendation systems. They will gain insights into the latest advancements in deep learning research and understand how to apply this cutting-edge technology to solve real-world challenges across various domains.
The Deep Learning Workshop is suitable for data scientists, machine learning practitioners, software engineers, and anyone interested in expanding their knowledge of artificial intelligence and deep learning. Whether you are a beginner or have some experience in machine learning, this workshop will provide you with the necessary tools and expertise to take your understanding of deep learning to the next level.
Join us for an engaging and transformative Deep Learning Workshop, where you'll unlock the potential of neural networks and revolutionize your approach to solving complex problems with the power of deep learning.
Goals of the Deep Learning Workshop:
1. Fundamentals: The workshop aims to provide participants with a solid understanding of the foundational principles and concepts underlying deep learning. By grasping the core concepts of neural networks, attendees will develop a strong foundation to explore and build upon more advanced deep learning techniques.
2. Practical Skills: The workshop seeks to equip participants with practical skills in designing, implementing, and evaluating deep learning models. Through hands-on exercises and coding sessions, attendees will gain the ability to apply deep learning algorithms to real-world problems, enabling them to make informed decisions regarding model architecture, data preprocessing, and optimization.
3. Application Awareness: The workshop focuses on showcasing the diverse applications of deep learning across various domains such as computer vision, natural language processing, and recommendation systems. Participants will understand the potential of deep learning techniques in solving complex problems and identifying opportunities for their practical implementation.
4. Tools and Frameworks: The workshop aims to familiarize attendees with popular deep learning frameworks like TensorFlow and PyTorch. By gaining hands-on experience with these tools, participants will be able to efficiently develop and deploy deep learning models, thereby accelerating their productivity and effectiveness in real-world scenarios.
5. Knowledge Exchange: The workshop fosters a collaborative environment where participants can engage in knowledge sharing and networking. By connecting with peers and industry experts, attendees can exchange ideas, best practices, and experiences related to deep learning, creating a vibrant learning community.
6. Empowerment: Ultimately, the goal of the workshop is to empower participants with the knowledge and skills needed to harness the power of deep learning. By the end of the workshop, attendees should feel confident in their ability to apply deep learning techniques and explore further advancements in the field, thereby enabling them to drive innovation and make informed decisions in their respective domains.
Scope and Information for Participants:
The Deep Learning Workshop covers a wide range of topics related to deep learning, providing participants with a comprehensive understanding of this rapidly evolving field. The workshop delves into fundamental concepts such as neural networks and progresses to advanced topics like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). It encompasses practical aspects including data preprocessing, model architecture design, optimization techniques, and evaluation methodologies. Furthermore, the workshop explores the applications of deep learning in areas such as computer vision, natural language processing, and recommendation systems. With a focus on hands-on exercises and using popular deep learning frameworks like TensorFlow and PyTorch, attendees gain practical skills to implement and deploy deep learning models effectively.
The Deep Learning Workshop is an immersive program designed to provide participants with a comprehensive understanding of deep learning and its practical applications. Through a combination of interactive lectures, hands-on exercises, and real-world case studies, attendees will delve into the core concepts of deep learning, including neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs).
The workshop focuses on equipping participants with practical skills in designing, implementing, and evaluating deep learning models. Attendees will gain expertise in areas such as data preprocessing, model architecture design, optimization techniques, and evaluation methodologies. Popular deep learning frameworks like TensorFlow and PyTorch will be utilized to facilitate effective model development and deployment.
Throughout the workshop, the diverse applications of deep learning across domains such as computer vision, natural language processing, and recommendation systems will be explored, enabling participants to identify opportunities for its practical implementation.
By the end of the workshop, attendees will have a strong foundation in deep learning, empowering them to leverage neural networks to solve complex problems and make informed decisions in their respective fields.
Illinois Institute of Technology, 10 W 35th St, Chicago, IL 60616, USA
In order to ensure the information is correct and up to date, there may be changes which we are not aware of. And different countries have different rules for the visa application. It is always a good idea to check the latest regulations in your country. This page just gives some general information of the visa application.
The B-1/B-2 visitor visa is for people traveling to the United States temporarily for business (B-1) or for pleasure or medical treatment (B-2). Generally, the B-1 visa is for travelers consulting with business associates; attending scientific, educational, professional, or business conventions/conferences; settling an estate; or negotiating contracts. The B-2 visa is for travel that is recreational in nature, including tourism; visits with friends or relatives; medical treatment; and activities of a fraternal, social, or service nature. Often, the B-1 and B-2 visas are combined and issued as one visa: the B-1/B-2.
If you apply for a business/tourist visa, you must pay your $160 application fee and submit the following:
In addition to these items, you must present an interview appointment letter confirming that you booked an appointment through this service. You may also bring whatever supporting documents you believe support the information provided to the consular officer.
Should your application be denied, the organizing committee cannot change the decision of visa officer, nor will CONF-CIAP engage in discussion or correspondence with the visa application center on behalf of the applicant. The registration fee CANNOT be refunded when the VISA application of individual being denied.
If you want to attend the workshop on-site, please email the Conference Committee: email@example.com.