A glimpse of recent engagements.
Work across energy, mobility, finance, public health, and travel. Senior staff lead every engagement.
A Custom Portfolio Optimizer, Up to 40% More Risk-Return Efficient Than Standard Heuristics
We built swissQuant a custom portfolio optimizer for risk-contribution-constrained allocation, a non-convex problem standard MIP solvers cannot solve to certified optimality. On real five-year MSCI World data, the heuristic alternative is up to 40% less risk-return efficient than our optimizer on 33-asset portfolios; in the most non-convex regime it drifts so far it returns a positive objective where the true optimum is negative.
Day-Ahead Bidding That Adds €0.9M of Realized Profit on a 900 MW Pumped-Storage Plant
We co-developed the optimization framework behind Alpiq's day-ahead bidding for the 900 MW Nant de Drance pumped-storage plant. Across 4 months of real cleared prices (Jan, Apr, Jun, Oct 2022) the stochastic version adds €0.9M (+3.2%) of realized profit over the deterministic approach Alpiq's traders use today. Enable the CVaR risk knob and the same engine trades ~2.5% of expected profit for ~70% lower tail risk.
A City-Scale Activity Scheduler That Reproduces the Swiss Microcensus on an Open-Source Stack
We co-authored the activity-based scheduling framework that turns the temporal layer of SBB's travel-demand work from rule-based heuristics into a real optimization problem. On a 46,970-schedule synthetic population of Lausanne workers, the simulated activity profiles reproduce every empirical signature of the Swiss microcensus, morning peak, lunch dip, evening leisure ramp, without any rule-based patching.
68 Behavioral Parameters of Swiss Worker Schedule Flexibility
We co-authored the open-access journal paper that estimates, from 10,110 real Swiss microcensus schedules, how flexible Swiss workers actually are about lunch, work timing, leisure, shopping, and the home day. All 68 behavioral parameters land statistically significant at 5%; the resulting calibration plugs into any activity-based travel-demand model. One memorable finding: workers are roughly 350× more averse, per hour, to a short lunch than to a short workday.
A Live Itinerary Engine That Picks the Best 3-Day Tour Out of 200M+ Google Places in Under 90 Seconds
We architected and shipped the optimization engine that turns 200M+ Google Places and a traveler's preferences into a personalized 3-day itinerary in under 90 seconds end-to-end. The optimizer closes a 1163% initial gap to under 10% inside that window. Engine, Google Places ingestion pipeline, and reference UI all live in Unki's traveler-facing app — benchmarked across Geneva, Paris, London and Lausanne.
Targeted Pandemic Restrictions That Cut ~22% of Infections at the Same Economic Cost
We delivered a 15-policy Pareto frontier of pandemic restrictions for the Vaud canton's 814,000-agent synthetic population, each policy paired with its full 60-day simulated epidemic trajectory. The headline finding: smarter age targeting cuts roughly 22% of infections at the same economic cost (72M vs 69M CHF) — restrict the 30–39 work cohort and you control the spread; restrict the 40–49 cohort and infections rise by 100,000 over two months. That kind of age-resolved decision is exactly what a coarse SEIR model cannot deliver, and exactly what a public-health response needs.