Sanskriti Gupta
Hi, I’m Sanskriti — a computer science student who enjoys building things, solving problems, and understanding how they work under the hood.
My work sits at the intersection of software engineering and AI. I work with machine learning, deep learning, and data structures & algorithms, and I enjoy taking an idea from a problem statement to something that actually works. I’ve also been exploring research through hands-on work in deep learning, where I’ve worked with real-world data, model architectures, feature extraction, and experimentation.
I’m particularly interested in opportunities where I can combine strong problem-solving with engineering and research — whether that means building reliable software, working on intelligent systems, or digging into a problem that doesn’t have an obvious solution.
I like learning things deeply, I’m comfortable figuring things out on my own, and I’m always looking for problems that are a little harder than what I already know.
Outside of AI research, I write poetry and short stories, solve data structures and algorithms problems, and I am always looking for the next meaningful challenge.
“The thread that runs through everything I do is curiosity. I ask why until I reach the bottom of it. That question is what drove me from competitive programming to deep learning research to writing poetry. All of it is the same thing: trying to understand.”
Work & Research
Developed a non-intrusive speech intelligibility prediction framework using self-supervised speech representations from Whisper and Wavelet Scattering Transform features.
Engineered acoustic feature extraction pipelines with Gammatone filterbanks, Whisper embeddings, and PyTorch-based deep learning models for intelligibility assessment.
Built a machine learning pipeline to detect fraudulent job postings using structured job attributes and textual features extracted from job descriptions and company profiles.
Performed data preprocessing, text cleaning, feature engineering, and TF-IDF vectorization across multiple classification models including Logistic Regression and Naive Bayes.
Wrote technical content on AI and ML topics, including Large Language Models and their real-world applications.
Write poetry, humor pieces, and short stories. FrameFlicks is a creative outlet that keeps my writing sharp and my thinking flexible.
Education
SGPA: 8.20
91.6%
95.8%