Pratham Gandhi

I build assistive computing and safe autonomy. My work spans haptic‑audio interfaces for non‑visual programming (HACI), contract‑based design with Signal Temporal Logic (COASTL), and accessible no‑code ML tools (AnaLazy). I’m a data scientist at Dell Technologies, working on human‑centered AI for global sales planning.

Email  /  CV  /  Google Scholar  /  GitHub  

profile photo

Work

HACI haptic-audio glove prototype
♿ Accessibility & HRI 🎓 EdTech
HACI: A Haptic‑Audio Code Interface for Non‑Visual Programming
Honors Thesis, University of Chicago, 2024

A browser IDE + Arduino glove that combines structured speech with finger‑localized haptics to reduce cognitive load in non‑visual code navigation and debugging.

Runtime: Ace Editor with AST‑aware guidance (Acorn), Web Speech + non‑speech cues, Web Serial to an Arduino Mega driving six DRV2605L vibrotactors via I²C multiplexer.

Pilot highlights: improved structural wayfinding and clear next steps around cue consistency and customization.

paper / code / slides

COASTL toolkit graphic
🛡️ Safe Autonomy ∑ Formal Methods
COASTL: Contract Operations & Signal Temporal Logic for Safe CPS
USC DesCyPhy Lab — Python library

A design‑by‑contract toolkit that parses STL into syntax trees and composes assumptions/guarantees to enforce requirements early in CPS design.

Encoding: prototype translation from STL specs to mixed‑integer constraints for behavior synthesis; supports illustrative examples and poster artifacts.

poster / code

AnaLazy app screenshot
🧰 Data Tools ⚙️ No‑Code ML
AnaLazy: No‑Code ML with Built‑In Data Quality
GUI app for spreadsheet‑to‑model workflows

A graphical app that ingests CSV/XLS data, runs quick data‑quality checks, then guides feature/target selection and model training (classification/regression).

Emphasis on responsible defaults: quality checks first, clear evaluation views, approachable UX for non‑programmers.

Flow demo: import → checks → select → train → evaluate → export.

write‑up / demo / code

Earlier work (Toksik, Space Walk, TIPP&SEE, SSI)
Toksik classifier visualization
🗣️ Responsible AI & NLP
Toksik: Classifying Harmful Language in Social Media
Supervised NLP baseline (NB vs. LR) with error analysis

Transparent pipeline with feature engineering, confusion matrices, and thresholding; Naive Bayes ~92% vs. Logistic Regression ~87% on held‑out data.

paper / code

Space Walk game concept art
🎮 Learning Game
Space Walk: A Game Metaphor for Quantum Entanglement
Two‑player collaborative web game for conceptual understanding

Coupled mechanics mirror entanglement’s state correlations; formative prototyping and play‑testing.

report / code

TIPP&SEE manuscript graphic
🎓 Learning Sciences
How Middle‑Schoolers Use TIPP&SEE in CS
Unpublished manuscript (4th–7th grade; Scratch; metacognition)

Behavior analysis across TIPP&SEE phases; implications for prompt sequence and scaffolding.

manuscript

SSI causal model diagram
🔗 Causal Inference
Education → Health: A Cross‑Country Causal Pathway
SSI project: OLS per indicator country with socio‑economic controls

Education → Employment → GDP → Medical Care → Life Expectancy, with paired countries to interpret heterogeneity in the mechanism.

research design slides / paper

Miscellanea

Academic Service

Volunteer Computer Science Teacher, Amar Jyoti School (Delhi), 2014–2019
Mentor, Data4All High School Bridge Program, 2022

Teaching

Teaching Assistant, UChicago CS23210 Usable Security & Privacy (Spring 2024)
Teaching Assistant, UChicago CS13600 Data Engineering (Spring 2024)
Graduate Teaching Assistant, UChicago STAT11900 (Winter 2024)
Graduate Teaching Assistant, UChicago DATA22700 (Spring 2023, Fall 2023)