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First-year CS PhD student at Stanford University
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Stanford
Data Scientist
June 25, 2026 – Present
data_dump_for_ui
November 3, 2022 – November 5, 2022
data_dump_for_ui — GitHub repository
View Projectensemble_gms
October 22, 2020 – October 22, 2020
Undirected graphical models are compact representations of joint probability distributions over random variables. To solve inference tasks of interest, graphical models of arbitrary topology can be trained using empirical risk minimization. However, to solve inference tasks that were not seen during training, these models (EGMs) often need to be re-trained. Instead, we propose an inference-agnostic adversarial training framework which produces an infinitely-large ensemble of graphical models (AGMs). The ensemble is optimized to generate data within the GAN framework, and inference is performed using a finite subset of these models. AGMs perform comparably with EGMs on inference tasks that the latter were specifically optimized for. Most importantly, AGMs show significantly better generalization to unseen inference tasks compared to EGMs, as well as deep neural architectures like GibbsNet and VAEAC which allow arbitrary conditioning. Finally, AGMs allow fast data sampling, competitive w
View Projectscene-generation-from-novel-viewpoints-gens
November 24, 2019 – December 19, 2019
Scene generation from novel viewpoints - Graph element networks
View Projectevolving-robotic-gripper
November 23, 2019 – November 23, 2019
Optimizing the morphology of robotic fingers for increased object grasping accuracy on adversarially-shaped objects
View Projectparallel_gripper_simulation_pybullet
November 23, 2019 – November 23, 2019
Parallel WSG-32 Gripper Simulation with a GUI wrapper and a Grasping-Routine wrapper
View ProjectNLP-Transfer-Learning-Domain-Adaptation
December 9, 2017 – December 16, 2017
Using LSTM and CNN trained on the stack exchange Ubuntu dataset for the question similarity task on the Android dataset, using transfer learning for domain adaptation.
View ProjectPytorch-Deep-Learning
October 10, 2017 – October 11, 2017
Implementations of Machine Learning Algorithms in PyTorch
View ProjectAugmented-Reality-Google-Glass-Safari-Game
October 3, 2017 – October 3, 2017
An augmented reality that places cute running animals all around your room. Gotta photograph 'em all!
View ProjectAbc-Music-Player
December 22, 2015 – December 23, 2015
Software parses musical pieces in abc notation (.abc files) and plays them
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards personal, research-oriented projects, which suggests a self-driven and curious individual. However, the lack of team-based or collaborative projects in the provided data makes it difficult to fully assess cultural fit in a team environment. The single listed work experience at Stanford as a Data Scientist is current but lacks details on responsibilities or achievements, limiting insight into professional cultural alignment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The psychometric test score is 0, indicating no assessment was completed or results are unavailable.