Syed Shaheer Salahuddin

Syed Shaheer Salahuddin

Data Scientist & Chemistry Researcher | Bridging Scientific Rigor with Machine Learning

Based in: Karachi, PakistanMost recently: Researcher (Electrocatalysis), Department of Chemistry LUMSExperience: 1 year

Hire me

B.S. Physics student at LUMS with a deep technical toolkit spanning electrochemical analysis and advanced data science. Proven track record in building predictive models (XGBoost) and causal inference pipelines, alongside high-impact research in electrocatalysis. Experienced in translating complex datasets into actionable business insights through interactive visualizations.

Experience

Researcher (Electrocatalysis)

Department of Chemistry LUMSLahore, PakistanworkSep 2025 – Jun 2026

Summary

Developing earth-abundant transition metal-based electrocatalysts for water/seawater electrolysis

What I did

  • Designed and fabricated four bifunctional NiFe foam electrocatalysts for alkaline water splitting via sonochemical surface modification, investigating the effect of HCl etching and noble metal (Ru, Ir) doping on HER and OER performance
  • Optimized synthesis parameters including sonication time, temperature, and precursor concentration through systematic electrochemical screening in 1 M KOH
  • Characterized catalyst kinetics via Tafel analysis (HER: 36.6 mV dec⁻¹, OER: 56.1 mV dec⁻¹), interfacial charge transfer via EIS (R_ct = 0.4 Ω cm⁻² HER, 2.0 Ω cm⁻² OER), and active surface area via ECSA (141.4 cm², roughness factor 566)
  • Performed SEM imaging before and after electrochemical testing to correlate surface morphology with catalytic activity trends

Results

  • Achieved HER and OER overpotentials of 76 mV and 176 mV at 10 mA cm⁻² for the best-performing catalyst (NiFeF@Ru), representing a 50% and 28% reduction relative to the pristine foam baseline
Electrochemical analysisCVCALSVEISECSASEMNiFe foamRuIr

Teaching Assistant

LUMS Learning InstituteLahore, Pakistanpart timeSep 2025 – Dec 2025

Summary

Managed and executed all logistical and technical support for executive education workshops.

What I did

  • Managed and executed all logistical and technical support for executive education workshops (30-50 industry participants), spanning agenda finalization, material preparation, and room/online setup.
  • Handled pre-session preparation and technical setup (AV, Zoom, recordings) and provided live participant support (check-in, Q&A, troubleshooting) to facilitate programs on topics like AI adoption.
AVZoom

Teaching Assistant - Linear Algebra with Differential Equations (Math-120)

Department of Mathematics, LUMSLahore, Pakistanpart time2025 – May 2025

Summary

Ran weekly tutorial sessions for a large cohort of 300+ students.

What I did

  • Ran weekly tutorial sessions for a large cohort of 300+ students, working through problem sets and clarifying core linear algebra and differential equations concepts.
  • Co-designed and reviewed quiz questions with the professor to align assessment difficulty with lecture content.
Linear AlgebraDifferential Equations

Skills

Technical

LSV
NumPy
Pandas
PythonPython
Electrochemical analysis
CV
SEM
scikit-learn
C++C++
ECSA
CA
Power BI
SciPy
EIS
OriginPro
PyTorchPyTorch
Raman
XRD
MATLAB
ImageJ
PostgreSQLPostgreSQL
TensorFlowTensorFlow
EDS
Quantum Espresso
Stata
ACE

Projects

Fourier Optics and Fraunhofer Diffraction Experiment

Student Researcheracademic
Implemented an advanced Fraunhofer (far-field) diffraction configuration by positioning apertures at D>100cm (up to 500 cm), contrasting the standard Fresnel (near-field) lab setup. Designed and aligned a multi-lens (f=35 mm, f=100 mm) Fourier Transform system to map the diffraction grating's spatial pattern directly into its frequency spectrum at the focal plane. Validated the Fourier analysis physically by introducing a second multi-lens system to reconstruct the original concentric diffraction pattern at the observation plane.
Fourier OpticsFraunhofer DiffractionMulti-lens system

Lahore Real Estate Market Analysis

Data Scientistacademic
Engineered a custom Python scraping pipeline to aggregate and clean 5,000+ Lahore property listings into a robust, structured dataset, addressing local market data scarcity. Trained an XGBoost price prediction model with Grid Search hyperparameter tuning, achieving an R2 of 0.826 and confirming that spatial location is the primary driver of price variance (Feature Importance analysis). Applied Propensity Score Matching (PSM), a causal inference technique, to estimate a PKR 1.45 Crore location-driven price premium for North-East Lahore, effectively controlling for property size and amenities.
PythonXGBoostGrid SearchPropensity Score Matching (PSM)Scraping

Education

B.S. Physics

Lahore University of Management SciencesPhysics/Chemistry/Computer ScienceSep 2022 – Jul 2026

Coursework

Fundamentals of AI and Machine Learning

Recognition

Awards

Dean's Honour List: Spring 2025

Lahore University of Management Sciences2025

Dean's Honour List: Spring 2023

Lahore University of Management Sciences2023
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Syed's twin is AI, it can make mistakes.