ayush-aggarwal-data-scientist

Geoinformatics has complex location and image data for data scientist to solve. – Ayush Aggarwal

Ayush Aggarwal
Senior Machine Learning Engineer
IIT Kanpur, Geoinformatics
New Delhi, India

Q1. Please share your educational and professional journey?

I did my dual degree (B.Tech and M.Tech) 5 year from IIT Kanpur in Civil Engineering (Geoinformatics).

I have experience in applying industry frameworks on different types of data-oriented applications using open source development. I worked on social media data, satellite images, location data, shapefile datasets, quantitative data for churn calculation, and landslide prediction. I have a wide technical skillset including data science, data engineering (Google Cloud), machine learning models, Google Map API, Image Processing, Gamification, Web, and Mobile Development.

I am also an Online Consultant and Mentor specialized in Geoinformatics, Data Science, and Development for Students. Consulted around 100+ Students

https://ayushaggar.wordpress.com/2015/11/26/career-opportunities-in-geoinformatic-in-india/

https://ayushaggar.wordpress.com/2020/08/15/geoinformatics-career-guide-series-part-1/

Worked in different sectors –

-> Company – Practo Technologies

-> Startup – OYO Rooms, Transerve Technologies

-> Research Institute – University of Hanover, Germany

-> NGO – Who Am I

Q2. You did Civil Engineering (Geoinformatics) from IIT Kanpur then why did you choose Data Science Domain for your career?

From the start of my B. Tech, I love to solve real-life problems through programming. During my M.Tech. thesis I chose a topic which is the inter-discipline of Data Science and Geoinformatics. My topic was ‘Landslide prediction using machine learning problems’. After that, I chose to work more on the Data Science domain to strengthen my skills in Machine Learning and Data Science.

Similarly, I am consulting students for a career through my Linkedin Page to transform their journey in geoinformatics and data science.

Linkedin Page -> https://www.linkedin.com/company/geospatial-data-science-consulting

Q3. How do you handle stress in this fast and competitive life?

In this competitive life, we have to be self-driven and have a goal to enrich with diverse experiences. For me, programming, geospatial data, and data science motivate me to learn end to end architecture to solve real-life problems at scale.

Besides, I do vlogging with my GoPro to relieve my stress

Youtube -> https://www.youtube.com/user/ayushaggar

Instagram -> https://www.instagram.com/ayushaggar/

Q4. Which Machine Learning Model have you used maximum in your career?

I have worked on various Machine Learning models – linear regression, linear mixture model, random forest, neural network. My goal is to play with different models and find the best for the given data after transformation.

I worked on NLP, Image processing, Forecasting, and various other ML problems

Ayush Aggarwal (Senior Machine Learning Engineer)

Q5. What is the use of Geoinformatics in the real world?

Geoinformatics is a technology that uses information infrastructure to address the problems of geography and geosciences. Here our data set is location data and satellite images. The data set is very complex and spatial queries are required to fetch any important information through it.

Geoinformatics is useful for urban planning, land use management, navigation, public health, environmental modeling, military, transport network planning, climate change, business location planning, telecommunications, and crime simulation

Q6. Which one thing do you want to change in Data Science Domain and why?

Data science is a very diverse topic. It includes different skills – visualization, data architecture, programming, storytelling, and so on. In my view to know about the problem which we are trying to solve we should have an end to end understanding of data science so that we can know all constraints and options which we can implement. If more focus will be on end to end things rather than learning new models it would be great.

Q7. Which one is the hardest working part of any Data Science Project?

The hardest working part is to understand the project and break it into smaller tasks to find which models, transformation, or visualization is required to solve the project. It requires experience to solve complex problems with various constraints and outcome

Q8. Where do you want to see yourself after 10 years in your career?

As we know location is an important component of any real-life problem so I believe there will be more complex geospatial data science problems in future to solve at scale. I would love to contribute to that sector through my consulting job and help students to grow in this field.

Get more about Ayush Aggarwal @

Website[20k + Views] -> https://www.ayushaggarwal.in/
Blog [25k + Views] -> https://ayushaggar.wordpress.com/
Linkedin -> https://www.linkedin.com/in/ayushaggar
Linkedin Page -> https://www.linkedin.com/company/geospatial-data-science-consulting
Youtube Channel -> https://www.youtube.com/user/ayushaggar
Instagram -> https://www.instagram.com/ayushaggar/
Email -> ayushaggar@gmail.com
Join his Newsletter (350+ Subscribers) regarding Geoinformatics, Machine Learning & Travel -> https://cutt.ly/newslettersubscribe

Data Scientist Interviews : Abhishek Thakur Interview, Krish Naik Interview and many more.

Leave a Reply

Your email address will not be published. Required fields are marked *