Academic
Nine years finding structure in noisy data — and the enterprise engagements that ran alongside it.
Dec 2015 – Sep 2024
Nine years in academia, most of it spent finding signal in messy biological and health data. As Principal Investigator of the Data Analytics Lab I led applied machine-learning research — molecular docking, drug–target interaction, and computational work that turned into peer-reviewed publications still cited today.
Alongside the research came the teaching: mentoring a generation of MS students through funded projects, and building the lab that made the work possible. A PhD in Informatics from the University of Greenwich sits underneath all of it.
The line to banking is direct. The skills that find structure in noisy data are the same ones that build AI you can trust in a regulated setting.
Principal Investigator, Data Analytics Lab · Jan 2021 – Sep 2024
Tenured Assistant Professor · Dec 2015 – Sep 2024
22 publications · 528 citations · h-index 7 · i10-index 6 · 25+ MS students mentored · 15+ funded projects (PKR 40M+ in grants)
Source: Google Scholar (as of Sep 2026)
Chimera + AutoDock Vina, written for non-bioinformaticians
A practical tutorial taking life-science researchers from raw structure files to docked complexes without prior bioinformatics training. Cited 290 times — the most-cited paper of the lab and a primary teaching reference for early-career researchers entering computational structural biology.
JMIR Bioinformatics & Biotechnology · 2020 · 290 citations
Pro-apoptotic potential, computationally and in vitro
A combined computational and wet-lab evaluation of taxifolin's pro-apoptotic potential against hepatocellular carcinoma. Network analysis identified candidate targets; downstream assays validated the strongest hits. Representative of the lab's translational-bioinformatics output during the NUST years.
PeerJ · 2021 · 36 citations
Jan 2023 – Sep 2024
Independent consultant — 18 enterprise clients across finance, health-tech and HR-tech. Architecture and data-maturity reviews, platform decisions, and production builds where the maths worked.
Designed and built for a US consultancy
End-to-end design and build of an AWS-native data lakehouse on S3, Glue, Redshift, and Lambda. ISO 27001-aligned. Delivered USD 250,000 in annual savings and a 30% infrastructure cost reduction. The same architecture pattern was reused across several client engagements.
US consultancy · 2023–2024
Deployed for an HR-tech startup
A churn-prediction model for an HR-tech startup, deployed in production. AUC 0.91 on held-out data; downstream the company reported a 35% lift in engagement on targeted retention workflows. Feature engineering and threshold calibration were the load-bearing decisions; the model itself was deliberately simple.
HR-tech startup · 2023–2024