
Tehseen Dahya
I'm Building
Using Machine Learning to Optimize Internet Networks in rural areas
Bio
Tehseen Dahya, a young technical builder based in Toronto, Canada, is known for his work in navigating unconventional paths to achieve remarkable outcomes. He received funding from the 1517 Fund to develop a project using machine learning to optimize internet networks in rural areas, a testament to his dedication to addressing technological disparities. Previously, Tehseen impressed by securing a meeting with the co-founder of LinkedIn and landing an internship at BloXroute through creative hustling efforts, showcasing his ability to leverage opportunities effectively.",.
Other Grantees
Discover other builders in the community working on exciting projects.

Pavitra Kalpesh Patel
I'm building India's first commercially available reusable rocket engine specifically designed for students and educational institutions.
Dima Yanovsky
I’m building an affordable, human-like robotic arm with dexterous hands for under $2000. The problem is that current robotic arms and hands are prohibitively expensive—costing $50,000–$100,000 (e.

Srijon Sarkar
To research protein design for defining a VIP receptor antagonist for pancreatic cancer and for general career development too.
Livingstone Livingstone Adeyemi
My aim is for it to be a faster, seamless, and better alternative to the current manual paper-based method of recording attendance (which is done on paper where we write our name, matric number, and sign) in my university, which is prone to errors like lost papers and manual transcription mistakes.

Hrishikesh Kalyanaraman
Accelerating conceptual design workflows by 2x using AI

Ivoine Strachan
Full-body VR suit

Prabhjot Sodhi
MunchPal - Helping grocery shopping with dietary requirements easier

Sam Waitathu
A group buy platform for essential medication in Kenya.

Akshat Singhania Singhania
I am developing SightSense, affordable and effective assistive smart glasses for the visually impaired, targeting a price of $115 – a cost 17 times lower than comparable assistive tech on the market.