From 6-22 February, the 2026 Winter Olympics in Milan-Cortina d’Ampezzo, Italy will feature not just the world’s top winter athletes but also some of the most advanced sports technologies today. At the first Cortina Olympics in 1956, the Swiss company Omega—based in Biel/Bienne—introduced electronic ski starting gates and launched the first automated timing tech of its kind.

At this year’s Olympics, Swiss Timing, sister company to Omega under the parent Swatch Group, unveils a new generation of motion analysis and computer vision technology. The new technologies on offer include photofinish cameras that capture up to 40,000 images per second.

“We work very closely with athletes,” says Alain Zobrist, CEO of Swiss Timing, Omega’s sister company within the Swatch Group, who has overseen Olympic timekeeping since the winter games of 2006 in Torino “They are the primary customers of our technology and services, and they need to understand how our systems work in order to trust them.”

Using high-resolution cameras and AI algorithms tuned to skaters’ routines, Milan-Cortina Olympic officials expect new figure skating tech to be a key highlight of the games. Omega

Figure Skating Tech Completes the Rotation

Figure skating, the Winter Olympics’ biggest TV draw, is receiving a substantial upgrade at Milano Cortina 2026.

Fourteen 8K resolution cameras positioned around the rink will capture every skater’s movement. “We use proprietary software to interpret the images and visualize athlete movement in a 3D model,” says Zobrist. “AI processes the data so we can track trajectory, position, and movement across all three axes—X, Y, and Z”.

The system measures jump heights, air times, and landing speeds in real time, producing heat maps and graphic overlays that break down each program—all instantaneously. “The time it takes for us to measure the data, until we show a matrix on TV with a graphic, this whole chain needs to take less than 1/10 of a second,” Zobrist says.

A range of different AI models helps the broadcasters and commentators process each skater’s every move on the ice.

“There is an AI that helps our computer vision system do pose estimation,” he says. “So we have a camera that is filming what is happening, and an AI that helps the camera understand what it’s looking at. And then there is a second type of AI, which is more similar to a large language model that makes sense of the data that we collect”.

Among the features Swiss Timing’s new systems provide is blade angle detection, which gives judges precise technical data to augment their technical and aesthetic decisions. Zobrist says future versions will also determine whether a given rotation is complete, so that “If the rotation is 355 degrees, there is going to be a deduction,” he says.

This builds on technology Omega unveiled at the 2024 Paris Olympics for diving, where cameras measured distances between a diver’s head and the board to help judges assess points and penalties to be awarded.

At the 2026 Winter Olympics, ski jumping will feature both camera-based and sensor-based technologies to make the aerial experience more immediate and real-time. Omega

Ski Jumping Tech Finds Make-or-Break Moments

Unlike figure skating’s camera-based approach, ski jumping also relies on physical sensors.

“In ski jumping, we use a small, lightweight sensor attached to each ski, one sensor per ski, not on the athlete’s body,” Zobrist says. The sensors are lightweight and broadcast data on a skier’s speed, acceleration, and positioning in the air. The technology also correlates performance data with wind conditions, revealing environmental factors’ influence on each jump.

High-speed cameras also track each ski jumper. Then, a stroboscopic camera provides body position time-lapses throughout the jump.

“The first 20 to 30 meters after takeoff are crucial as athletes move into a V position and lean forward,” Zobrist says. “And both the timing and precision of this movement strongly influence performance.”

The system reveals biomechanical characteristics in real time, he adds, showing how athletes position their bodies during every moment of the takeoff process. The most common mistake in flight position, over-rotation or under-rotation, can now be detailed and diagnosed with precision on every jump.

Bobsleigh: Pushing the Line on the Photo Finish

This year’s Olympics will also feature a “virtual photo finish,” providing comparison images of when different sleds cross the finish line over previous runs.

Omega’s cameras will provide virtual photo finishes at the 2026 Winter Olympics. Omega

“We virtually build a photo finish that shows different sleds from different runs on a single visual reference,” says Zobrist.

After each run, composite images show the margins separating performances. However, more tried-and-true technology still generates official results. A Swiss Timing score, he says, still comes courtesy of photoelectric cells, devices that emit light beams across the finish line and stop the clock when broken. The company offers its virtual photo finish, by contrast, as a visualization tool for spectators and commentators.

In bobsleigh, as in every timed Winter Olympic event, the line between triumph and heartbreak is sometimes measured in milliseconds or even shorter time intervals still. Such precision will, Zobrist says, stem from Omega’s Quantum Timer.

“We can measure time to the millionth of a second, so 6 digits after the comma, with a deviation of about 23 nanoseconds over 24 hours,” Zobrist explained. “These devices are constantly calibrated and used across all timed sports.”

MVK Chari, a pioneer in finite element field computation, died on 3 December. The IEEE Life Fellow was 97.

Chari developed a finite element method (FEM) for analyzing nonlinear electromagnetic fields—which is crucial for the design of electric machines. The technique is used to obtain approximate solutions to complex engineering and mathematical problems. It involves dividing a complicated object or system into smaller, more manageable parts, known as finite elements, according to Fictiv.

As an engineer and technical leader at General Electric in Niskayuna, N.Y., Chari used the tool to analyze large turbogenerators for end region analysis, starting with 2D and expanding its use over time to quasi-2D and 3D.

During his 25 years at GE, he established a team that was developing finite element analysis (FEA) tools for a variety of applications across the company. They ranged from small motors to large MRI magnets.

Chari received the 1993 IEEE Nikola Tesla Award for “pioneering contributions to finite element computations of nonlinear electromagnetic fields for design and analysis of electric machinery.”

A career spanning industry and academia

Chari attended Imperial College London to pursue a master’s degree in electrical engineering. There he met Peter P. Silvester, a visiting professor of electrical engineering. Silvester, a professor at McGill University in Montreal, was a pioneer in understanding numerical analysis of electromagnetic fields.

After Chari graduated in 1968, he joined Silvester at McGill as a doctoral student, applying FEM to solve electromagnetic field problems. Silvester applied the method to waveguides, while Chari applied it to saturated magnetic fields.

Chari joined GE in 1970 after earning his Ph.D. in electrical engineering. He climbed the leadership ladder and was a manager of the company’s electromagnetics division when he left in 1995. He joined Rensselaer Polytechnic Institute in Troy, N.Y., as a visiting research and adjunct professor in its electrical, computer, and systems engineering department. Chari taught graduate and undergraduate classes in electric power engineering and mentored many master’s and doctoral students. His strength was nurturing young engineers.

He also conducted research on electric machines and transformers for the Electric Power Research Institute and the U.S. Department of Energy.

In 2008 Chari joined Magsoft Corp., in Clifton Park, N.Y., and conducted advanced work on specialized software for the U.S. Navy until his retirement in 2016.

Remembering a friend

Chari successfully nominated one of us (Hoole) to be elevated to IEEE Fellow at the age of 40. He helped launch Haran’s career when Chari sent his résumé to GE hiring managers for a position in its applied superconductivity lab.

Chari’s commitment to people came from his family background. His father—M.A. Ayyangar—was known throughout India as a freedom fighter, mathematician, and eventually the speaker of the Indian Parliament’s lower house under Prime Minister Nehru. Chari’s wife, Padma, was a physician in New York.

From Chari’s illustrious family, he was at the peak of South India (Tamil) society.

Chari would fondly and cheerfully tell us the story behind his name. Around the time of his birth, it was common in Tamil society not to have formal names. He went by the informal “house name” Kannah (a term of endearment for Krishna). When it was time for Chari to start school, an auspicious uncle enrolled him. But Chari had no formal name, so the uncle took it upon himself to give him one. He asked Chari if he would like a long or short name, to which he said long. So the uncle named him Madabushi Venkadamachari.

When Chari moved to North America, he shortened his name to Madabushi V.K.

He could also laugh at himself.

A stellar scientist, he also was a role model, guide, and friend to many of us. We thank God for him.