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Chan Naseeb

AI Thought Leader at IBM

Munich, Germany

Thought Leader in AI, Data Science, Quantum, Digital Transformation, Cloud, Agile, BlockChain, IoT
Author, Public Speaker, Moderator.

I am an internationally experienced, highly motivated professional and an executive data scientist who can design end-to-end innovative solutions for clients. I lead, plan and realise the strategy by actively contributing to it through thought leadership and my professional experience. I have about 13+ years of experience in design, implementation, and testing of systems using different languages, platforms, and technologies with a particular focus on ML, DL, Data Science, and Python. I am passionate about realising solutions using modern tech stack. I enjoy working with teams and leading them in agile way.

With an impeccable track record of well-honed communication skills, I cultivate relationships with stakeholders and motivate colleagues to implement complex solutions to deliver objectives effectively.

Key Competencies:
-Data Analytics, Data Science, AI, Intelligent Automation, Blockchain, IoT
-Digital Transformation, Data & AI Strategy
-Industry 4.0
-Project and Program Management, Product Development Management, Risk and Change Management.
-Design, Delivery, and Implementation
-Agile and Design Thinking

Technologies and Methodologies:
Data Science, AI, Machine Learning, Cloud Computing, and Block Chain. ML, DL, Watson, AWS, Microsoft Azure, Hadoop, MapReduce, Spark, Kafka, Flume, Python, SPSS Modeler, Alteryx, Kylo, Ethereum, Solidity, HyperLedger, Mist, SQL and NoSQL-based technologies
Scaled Scrum, Scrum Master, Python

Available For: Authoring, Consulting, Influencing, Speaking
Travels From: Munich
Speaking Topics: AI, Quantum, Data Science, Blockchain, IoT, Industry 4.0, Digital Transformation etc

Speaking Fee $8,000

Chan NaseebPoints

Points based upon Thinkers360 patent-pending algorithm.

Thought Leader Profile

Portfolio Mix

Company Information

Company Type: Enterprise

Areas of Expertise

AI 39.52
Digital Transformation 30.42
Quantum Computing 41.95
Future of Work 30.33
IoT 30.14
Social 30.17
5G 30.12
Business Strategy 34.35
Digital Disruption 34.81
Leadership 31.24
Sales 38.62
Blockchain 34.58
Predictive Analytics 32.29
Change Management 31.33
Emerging Technology 30.51
Big Data 31.53
Agile 32.25
Culture 31.45
Design Thinking 31.00

Industry Experience

Agriculture & Mining
Federal & Public Sector
Financial Services & Banking
Higher Education & Research
Travel & Transportation

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1 Adjunct Professor
Dr Chan Naseeb
September 21, 2017
Organise several lectures and workshops on Data Science and its applications

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Tags: AI, Blockchain, Predictive Analytics

12 Article/Blogs
AI and ML driving, exponentiating sustainable and quantifiable transformation
September 09, 2020
AI is a major transforming technology impacting every sector of life. AI is not a force to deprive humans and take over the control, rather a real enabler and lever for digital transformation. The former view aligns with Hollywood need to be undressed with the latter, which is realistic and becoming tangible over time as more organizations, and communities are leveraging AI’s potential. Developing a practical understanding of AI, its capabilities, the challenges, and opportunities that it brings is fundamental to get the maximum out of its envisaged potential.

The objective of this paper is to highlight how technology and industry have developed, discuss the role of AI in driving intelligent transformation concentrating on an applicable understanding of AI and related technologies. We introduce a new conceptual framework: AI's multi-dimensional role, to highlight its transformative power in multiple aspects and to support that with facts across different industry verticals.

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Tags: AI, Digital Transformation, Digital Disruption

Activity Recognition for locomotion and transportation dataset using deep learning
UbiComp/ISWC 2020
September 01, 2020
Worked on a broad, real-life dataset to classify transport-related activities in a user and location-independent manner. Since deep learning architectures have now received great attention on achieving promising results on time series classification tasks, we focused our experiments on some recent state-of-the-art deep learning architectures such as CNN, Resnet, and InceptionTime. A considerable amount of time was spent on the preprocessing pipeline, which turned out to be a critical phase that impacted most of the results. At the end and after many experiments and hyperparameter tuning, we were able to achieve a 79% F1 score on the validation dataset using InceptionTime architecture. The objective of this paper is to present the technical description of the Machine Learning processing pipeline, the algorithms used, and the results achieved during the development/training phase.

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Tags: AI, Big Data, Predictive Analytics

Becoming a Data scientist: which path to take?
Import from
June 08, 2020
What are the options out there for you to become a data scientist?Continue reading on Towards Data Science »

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Tags: AI, Big Data

AutoAI: Your buddy (trusted partner) to speed up time to market for your AI and ML Models.
Import from
June 04, 2020
Automating different steps of the ML LifecycleContinue reading on Towards Data Science »

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Tags: AI, Big Data

Work space Complexity and dealing it with AGILE.
Import from
May 16, 2020
Agile can help you deal with today’s business complexities.Continue reading on ILLUMINATION »

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Tags: AI, Big Data

Inhibitors to Writing
Import from
May 15, 2020
Things that keep us from bloggingContinue reading on ILLUMINATION »

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Tags: AI, Big Data

Your stories, Your Publication:Diversified Knowledge
Import from
May 15, 2020
Do not stop sharing your experience, and your knowledgeContinue reading on Diversified Knowledge »

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Tags: AI, Big Data

Industry 4.0 or Internet 4.0?
Import from
May 15, 2020
Understanding Industry 4.0Continue reading on Towards Data Science »

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Tags: AI, Big Data

Impact of Covid-19 Lockdown on our planet(Blessings in the disguise)
Import from
May 11, 2020
What our planet has gained as a result of the lockdown?Continue reading on ILLUMINATION »

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Tags: AI, Big Data

Blessings in the disguise. An invitation for Invention and Innovation
Import from
May 07, 2020
Lockdown, and Seclusion means more personal time and an invitation for invention and innovation: what could we gain?Continue reading on ILLUMINATION »

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Tags: AI, Big Data

Future Children - Can IoT Devices Help Save the World
IEEE IT Professional
November 08, 2019
Gave a unique perspective of how AI and IoT can be sued to better serve the society at large, reducing the water waste and causing less CO2 emissions.

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Tags: AI, IoT, Social

5G - Fifth Generation of Mobile Networks
December 04, 2018
We are hearing a lot about 5G these days, but the question is what is it and how it will change our life? 5G is not something that will replace 4G completely at once, and will continue to exist, rather it is organic phenomenon that will evolve and change over time. This should also clarify the perspective that why there are already some efforts going on for 6G. We need to recognise the fact that there are more promising developments to come ahead of this. All smartphone companies are doing their level best to launch 5G enabled devices and connections. These devices will operate in different frequency bands such as from 3 to 300 GHz. Let's put these promising opportunities aside for now and start with actually introducing 5G and how the mobile technology has evolved from 1G to where it stands today. Before, concluding, I will also discuss advantages of 5G and some limiting factors / disadvantages of 5G (as of now).

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Tags: 5G, AI, Digital Transformation

1 Book
Cognitive Enterprise: An End to End AI Strategy (to be Published)
July 31, 2020
In this book, I take the readers, the decision makers for a journey of how to transform their enterprises using AI. What are the critical decisions and choices they need to take and what are the steps to be implemented that will lead to a fully transformed and cognitive enterprise.

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Tags: AI, Digital Disruption, Business Strategy

1 Founder
January 01, 2018
Developing high quality business strategies and plans ensuring their alignment with short-term and long-term objectives
Leading and motivating RemiNet team to advance employee engagement and develop a high performing managerial team
Overseeing all operations and business activities to ensure they produce the desired results and are consistent with the overall strategy and mission
Act within its powers as Company’s executive in-charge;
Set up and achieve the business targets;
and much more

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Tags: Business Strategy, Leadership, Sales

2 Industry Certifications
Scaled Scrum Master
May 19, 2016

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Tags: Agile, Change Management, Culture

Scrum Master
April 29, 2016

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Tags: Agile, Culture, Design Thinking

2 Keynotes
Augmented Human Intelligence: Collaborative Intelligence
EuroEvents, AI & Analytics: The power of AI in Business conference
November 13, 2018
Humans and Machines working together

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Tags: AI, Digital Transformation, Quantum Computing

Data Monetozation
October 18, 2017
How to make your organisation as data monetised enterprise using AI and other modern technologies.

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Tags: AI, Change Management, Emerging Technology

1 Media Interview
Data Driven Future
November 24, 2018
Data Driven Future
What is holding companies to become truly data and AI driven enterprises?

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Tags: AI, Digital Transformation, Future of Work

1 Panel
Role of Data Science in Transforming the Industry
March 23, 2018
Discussed the transformation role of AI and Data Science in changing different industry verticals

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Tags: AI, Digital Transformation


1 Article/Blog
2021 Predictions for Quantum Computing
October 08, 2020
[Image by Gerd Altmann from Pixabay]

I think 2021 will be the year when QC becomes more democratized and goes mainstream. While technologies like IoT, hybrid cloud, and data analytics — will still strongly have their position in the business landscape —, I see an expanding usage of AI, fifth-gen networks (5G), and above all, quantum computing. Besides its applications in cybersecurity, drug development, financial modeling, better batteries, traffic optimization, climate change, materials discovery, simulation, AI, etc., it can take our understanding of nature and chemistry to a level that has never been feasible before.

I expect the following quantum trends to accelerate in 2021.

1. Quantum Machine Learning- AI and Machine Learning. As AI has seen many applications already, it is the next realistic step to leverage quantum machine learning for easy and realistic QC usage.

2. Covid-19 and Beyond: QC could play a pivotal role in use cases like vaccine development and identifying and managing the spread of viruses. Potential applications of QC include predicting the evolution of COVID-19 using quantum machine learning. Quantum sensors, including NV-diamond sensors, have the potential to detect COVID-19. Quantum plasmonic sensors with considerably less noise could be utilized in blood protein analysis, chemical detection, and atmospheric sensing.

3. Quantum Algorithms: The development of new Quantum Algorithms and conversion from classical algorithms into quantumized algorithms.

4. Performance improvement and Optimization of Quantum Noise.

5. Development of new (or advancements in) Real-Time architectures for QC.

6. Use Cases: Expanding Industrial Use Cases suitable for Quantum Computing.

7. Conventional cum Quantum: Hybrid computing approach to problem-solving. This new paradigm of computation with a hybrid approach will result in the emergence of novel ways to solve the existing business problems and bring new opportunities, which were inconceivable earlier.

8. Adoption: Quantum computing enterprise adoption at scale, dependent on advances in storage, integrations, deployments, and security of quantum applications.

9. Advances in Quantum cryptography and Quantum-safe cryptography

10. QCaaS: QC as a Service will be a natural choice for organizations to tap into the experiments.

As we move forward with ongoing research and innovation in Quantum technology, the need for products and platforms that support diverse algorithms, frameworks, and hardware with unified development and deployment experience to the developers will start gaining traction. We saw some initial efforts in this area in the 2019–20 that will get a further impulse in 2021. Though the adoption of Quantum at scale might seem to be a faraway reality, the work in the next 1–2 years will determine the speed at which industry will start strategizing, building, and deploying quantum applications.

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Tags: Quantum Computing


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