
Cem Dilmegani
Cem has been the principal analyst at AIMultiple for almost a decade.
Cem's work at AIMultiple has been cited by leading global publications including Business Insider, Forbes, Morning Brew, Washington Post, global firms like HPE, NGOs like World Economic Forum and supranational organizations like European Commission. [1], [2], [3], [4], [5]
Professional experience & achievements
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider. [6], [7]
Research interests
Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity (including network security, application security), data collection including web data collection and process intelligence.
Cem's hands-on enterprise software experience contributes to his work. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.
Education
He graduated as a computer engineer from Bogazici University in 2007. During his engineering degree, he studied machine learning at a time when it was commonly called "data mining" and most neural networks had a few hidden layers.
He holds an MBA degree from Columbia Business School in 2012.
Cem is fluent in English and Turkish. He is at an advanced level in German and beginner level in French.
External publications
- Cem Dilmegani (September 28, 2017). Post-AI Banking: Millions of jobs at risk as banks automate their core functions. International Banker
- Cem Dilmegani, Bengi Korkmaz, and Martin Lundqvist (December 1, 2014).Public-sector digitization: The trillion-dollar challenge.McKinsey & Company
Conference & other event presentations
- Real Estate and Technology, presented by Hofstra University’s Wilbur F. Breslin Center for Real Estate Studies and the Frank G. Zarb School of Business in 2023 and 2024.
- Radar AI session (June 22, 2023): "Increasing Data Science Impact with ChatGPT".
- Generative AI Atlanta meetup (March 10, 2023): Generative AI for Enterprise Technology.
Sources
- Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
- Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
- Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
- Science, Research and Innovation Performance of the EU, European Commission.
- EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
- Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
- We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.
Latest Articles from Cem
Future of Deep Learning according to top AI Experts
Deep learning is currently the most effective AI technology for numerous applications. However, there are still differing opinions on how capable deep learning can become.
How to Implement Proxy Scraping Services
Websites track the IP address of every incoming request, and a high volume of traffic from a single IP is the signal of an automated bot. The solution is a proxy. A proxy server is an intermediary that stands between your scraper and the target website, forwarding your requests while masking your real IP address.
Top 10 Applications of Deep Learning in Manufacturing
Deep learning, a subset of artificial intelligence and machine learning, uses predictive analytics to extract insights, improve productivity, reduce defects and maintenance costs, and accounts for approximately 40% of the annual value generated by all analytics approaches.
Deep Learning in Healthcare: 12 Real-World Applications
The computing capability of deep learning models can enable fast, accurate, and efficient operations in patient care, R&D, and insurance. Key deep learning in healthcare includes: IDC claims that: Patient Care 1.
Deep Learning in Finance Top 11 Use Cases
Based on our analysis of deep learning applications in finance, we’ve identified 11 key use cases where AI-driven models are making an impact. These examples are drawn from real-world implementations across financial institutions and cover areas such as fraud detection, risk assessment, and investment strategies.
Top 10 Healthcare Analytics Use Cases with Examples
The $28 billion healthcare analytics marketis transforming how providers, payers, and life sciences organizations compete, and companies that move now can seize the advantage. By delivering solutions that drive predictive care, reduce costs, and optimize operations, analytics unlocks new revenue streams and strengthens customer loyalty in a healthcare industry racing toward data-driven performance.
Quantum Software Development Kits
Quantum Software Development Kit is a tool for developing quantum algorithms that can be used in quantum computers or simulators and emulators. See what quantum SDKs are in detail and what some examples of them are.
Quantum Entanglement: What is it & Why is it Important ?
Various industries are trying to solve time and processing power consuming problems using quantum computers to unlock valuable applications of quantum computing. The phenomena of quantum entanglement comes useful to cut down on the time and computing power to process information transfer between qubits. Entanglement enables tasks such as quantum cryptography, superdense coding, and teleportation.
Top 50 Deep Learning Use Case & Case Studies
Deep learning is a machine learning technique using artificial neural networks. When trained on large, high-quality datasets, it achieves high accuracy. This makes it useful in areas with abundant data where accurate predictions are valuable. Please see deep learning capabilities and its applications based on industry and function.
How to Protect Your Business from Website Cloning / Mirroring
Your business may be a mundane B2B business like ours, and you may think that you do not have to protect your website from attacks like cloning. You would be wrong. Eventually, your site may get cloned; it happened to us.
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