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IIIT Hyderabad
Data Scientist
June 13, 2026 – Present
Viking
March 29, 2025 – March 29, 2025
Viking is a high-speed zero-knowledge proof system, a cryptographic primitive that enables a prover to prove a mathematical statement to a verifier without revealing anything besides the validity of the statement. This repository is a Rust library that implements a zkSNARK (zero-knowledge proof system with short proofs & fast verification times)
View ProjectOptimal_Transport_Aggregation_For_Robust_Textual_Descriptors
December 23, 2024 – December 23, 2024
This project enhances text encoders' global descriptors by implementing advanced aggregation techniques from computer vision literature, to improve sentence-level representations. We utilize models such as BERT, RoBERTa, and CLIP, and benchmark performance using datasets like MTEB, SemEval24 and Quora Question Pairs.
View ProjectRestoring_Classics_to_4K
November 18, 2024 – December 23, 2024
Developed an image colorization pipeline utilizing Non-Local Means, Total Variation, and Wavelet Denoising for noise removal, with SIFT and ResNet backbones for feature extraction on ImageNet-1k, and enhanced spatial consistency through joint bilateral filtering and 4K upscaling via bilinear interpolation.
View ProjectParameter_Efficient_Fine_Tuning
October 21, 2024 – October 26, 2024
Implementation of the following parameter-efficient fine-tuning methods on GPT-2 for summarization: Soft prompt tuning by optimizing prefix embeddings, LoRA, and fine-tuning only the last classifier layer while keeping the rest of the model frozen
View ProjectAttention_Is_All_You_Need_From_Scratch
September 16, 2024 – October 2, 2024
Implementation of the NeurIPS 2017 paper "Attention is All You Need" from scratch
View ProjectCamera_LiDAR_Calibration
July 30, 2024 – July 30, 2024
Implemented an end-to-end calibration pipeline starting with an uncalibrated camera. Utilized checkerboards along with Zhang's camera calibration method to calibrate the camera. Applying the PnP algorithm between manually annotated correspondences between LiDAR maps of the checkerboard and the corresponding images gives the extrinsic parameters
View ProjectUNet_Segmentation
July 30, 2024 – July 30, 2024
Segmentation pipeline that uses a U-Net backbone to perform segmentation on the Cityscapes dataset. Conducted experiments to analyse the impact of the skip connections of the U-Net on the quality of the segmentation masks. These masks are also qualitatively analysed using the Intersection-over-Union (IoU) metric
View ProjectStatistical-Methods-In-AI-M23
January 9, 2024 – January 9, 2024
Coursework done as part of the Statistical Methods in AI course offered in Monsoon 2023 by Prof. Ravi Kiran Sarvadevabhatla, IIITH. Topics covered include KNNs, Decision Trees, Dimensionality Reduction, Gaussian Mixture Models, Bagging, Boosting, MLP Classifiers and Regressors, Logistic Regression, Kernel Density Estimation and Hidden Markov Models
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards research and academic projects, which aligns with a role that values continuous learning and exploration. The diversity of projects, from computer vision to NLP and even cryptography, indicates a broad intellectual curiosity. However, the candidate's experience level is listed as 0, and the only listed 'experience' is a future role at IIIT Hyderabad, which suggests a lack of professional industry experience. This might impact immediate cultural fit in a fast-paced industry environment without significant mentorship.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are clear but do not provide insights into collaboration, problem-solving approach, or communication style in a team setting.