Hardik Bansal
Chief Technology Officer at GatherGov
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolHardik Bansal is a data-driven technology leader and CTO based in New York with 13 years of experience building AI-first products and teams, currently shaping real-time intelligence for real estate development at GatherGov. Trained as a computer scientist at IIT Kanpur, he blends quantitative research chops from WorldQuant with hands-on machine learning engineering—his open-source TensorFlow CycleGAN implementation shows early ML engineering depth. As a founder of FRND and a former head of engineering, he pairs product-minded leadership with the ability to implement core models and production pipelines. Hardik’s background in theoretical research and numerical optimization gives him a rare comfort moving between convex optimization proofs and pragmatic system design.
13 years of coding experience
7 years of employment as a software developer
Indian Institute of Technology KanpurHigh School, High School at D.A.V. Public school.kota
Stackoverflow
1reputation
0reached
0answers
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Github Skills (9)
computer-vision10
machine-learning10
tensorflow10
generative-adversarial-network10
image-processing9
resnet9
python9
convolutional-neural-networks8
neural-network8
Programming languages (2)
Github contributions (5)
hardikbansal/CycleGAN
Apr 2017 - Dec 2017
Tensorflow implementation of CycleGAN
Role in this project:
ML Engineer
ML EngineerContributions:81 commits, 1 PR, 37 pushes in 8 months
Contributions summary:Hardik implemented the foundational code for a CycleGAN model, a type of generative adversarial network (GAN) used for image-to-image translation. They added the core components for the generator and discriminator networks within a TensorFlow implementation, defining key parameters, building the network architecture, and including functions for training and displaying the results. The initial commit established the basic structure and subsequent commits refined it by adding convolutional layers, normalization, ReLU activation, and ResNet blocks, and also incorporated image loading and training loops.
deep-learningcyclegantensorflowtensorflow2
hardikbansal/Qlearning
Aug 2017 - Oct 2017
Contributions:71 commits, 67 pushes, 1 branch in 1 month
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