2026-06-10 02:41:14
This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!
Early in my career, I walked into a shared office space on my first day as a full stack software developer and sat down between the CTO and the CEO to get onboarded. There were four of us in total. Before the day was over, I received my first assignment.
This was one of the most formative—and most stressful—experiences of my professional life. In the decade since, I have worked at half a dozen companies including Fortune 100 firms, mid-size startups, and companies you’ve probably never heard of. I have also spoken with roughly a thousand developers at various stages of their careers.
Most engineers entering the field are obsessed with landing at Google, Meta, or Amazon. But those roles represent approximately 0.6 percent of software engineering positions. For most of us, the real choice is between a small startup, a mid-size company, and a large enterprise. Each comes with tradeoffs, and your experience will differ from mine. What follows is an honest account of what you might reasonably expect.
The Small Startup
Pros
Your work actually matters. A feature you build might determine whether the company closes its next funding round. You gain exposure to the full spectrum of the business, from deployment pipelines to sales and operations and everything in between. You wear many hats out of necessity. For engineers who want to grow quickly and understand how a product is built end to end, few environments move faster.
Cons
Everything is on fire, always. Work-life balance is difficult to maintain when every release feels critical. Priorities shift without warning and culture tends to reflect the personality of whoever has the most influence in a small room. Startups optimize for speed over craft which means engineers learn to move fast but don’t always learn to build well, and that gap can follow you into your next role.
The Mid-Size Company
Pros
“So this is how a real business works.” There is process, documentation, a quality assurance function, and some form of career structure. The team is large enough to offer a diversity of experience and perspective. Stability is a myth, especially nowadays, but it is considerably more predictable than an early-stage startup.
Cons
“So this is how a real business works?” Processes that enable quality also produce friction. Access controls, approval workflows, and cross-team dependencies slow things down. The career ladder exists but it might stop at senior engineer. Without significant organizational growth, your salary and title can plateau early.
The Large Enterprise
Pros
That badge on your LinkedIn profile just bought you credibility for the next five years. Compensation at this level can be meaningfully higher, particularly when equity is included. The career ladder is long and clearly defined. Engineering practices at mature organizations tend to be more rigorous, and a well-known employer carries market value in future job searches.
Cons
It’s slow. Technology stacks often lag industry trends by several years. Political dynamics shape advancement as much as technical ability does. Skill atrophy is a risk when you spend years on a narrow slice of a legacy system. You are now a small fish in a big pond and it will be harder to get noticed.
The Roadmap I Would Take If I Could Start Over
According to a recent Stack Overflow survey, 47 percent of professional developers work at companies with fewer than 100 employees. This may surprise you because social media is dominated by engineers who work at the most well known companies on the planet.
The path most engineers imagine for themselves and the path most engineers actually walk are two very different things.
If I could do it again, here’s the path I’d take: Start at a small company to build breadth and learn how a business works across functions. This also provides some room to experiment within different roles. Next, move to a mid-size organization with a clear goal of reaching a senior or leadership role. Making a lateral move is easier than trying to get up-leveled at the next company. Finally, target a more mature company where a leadership position opens the door to meaningful equity and long-term growth (aka stocks and bonuses).
Each stop builds something the others cannot. The startup gives you range. The mid-size company gives you a taste of how larger orgs operate. The enterprise gives you leverage, credibility and maybe even some stability.
Your path will not look like mine. At a five person startup, I had no idea what I was in for. Looking back, I would not trade it. Just know what you are signing up for before you sign.
—Brian
“Social engineering” is a concept that has become associated with phishing, in which scammers manipulate people into disclosing personal information. But shaping human behavior in this way doesn’t have to have such negative effects. Systems engineer Guru Madhavan argues that we need to reclaim the term and govern the practice to defend ourselves from bad actors and benefit from social engineering’s good side.
Smartphone apps are increasingly used to help manage medical conditions, but many of these have not been verified by any regulatory agencies. To help ensure these apps are credible, the IEEE Standards Association recently launched a directory listing apps that have been vetted by experts for technical soundness, ethical design, data security and privacy, and clinical efficacy. The registry will be publically available at no cost, and developers can now apply for approval.
A veteran chip designer reflects on what he learned when moving from academia to industry, where the goal changes from proof of concept to ensuring a design works reliably at scale. Differences in risk tolerance, he discovered, lead to varying approaches in the rapidly growing semiconductor industry.
2026-06-10 02:25:12
This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!
I’ve changed jobs more times than I ever imagined I would. In the past 12 years, I’ve worked at seven different organizations. Some of those moves were forced by layoffs. Others were deliberate bets on my own trajectory.
Job hopping, done strategically, is one of the fastest ways to accelerate your compensation and reinvent your professional identity. Engineers who understand when to move and when to stay tend to out-earn and out-rank their peers who simply wait for internal recognition.
Unfortunately, most engineers either job hop too much or not enough, and both mistakes are expensive. Here are the pros and cons of job hopping as an engineer, and when to make a leap.
Pro: It’s the fastest way to grow your salary
Internal raises and external offers operate on completely different logic, and most engineers don’t fully appreciate this until they make their first move.
Within a company, compensation is anchored to your existing salary and capped by organizational pay bands. A strong performance review might get you 5 to 8 percent.
An external offer is a clean slate. The company is bidding for your market value, not adjusting from your current baseline.
My first deliberate job hop doubled my salary in a single year. A later move, at the same job title, pushed my compensation floor to a level that I never would have reached by staying put. Neither outcome was available internally. The math simply does not work in your favor when you stay.
Pro: It lets you reinvent yourself
Every new company is a chance to walk in as a slightly updated version of yourself: the version that learned something from the last place. The version that does not carry the baggage of whatever decision you made two years ago that all your coworkers still remember.
Especially when you’re early in your career, this matters. You get to reframe your experience, take on a different scope, and establish a new reputation from scratch. That kind of reset is difficult to manufacture inside the same organization.
Con: You don’t see the long-term outcome of your work
This is the part nobody talks about, and it took me years to fully appreciate it.
When I joined one company, I built a component library for a website from scratch. Starting projects from scratch is exciting, and the initial implementation held up well for the early use cases. But as the organization scaled, the limitations of my original design became apparent.
I stayed long enough to address them rather than handing that problem to someone else. That experience taught me more about software architecture than any new project ever had.
Engineers who move every 18 months only ever experience the exciting part of building something. They never experience the part where their original decisions stop working. They just repeat the exciting part on a loop, never realizing the debt they are leaving behind.
Con: You cannot job hop your way to a promotion
Above a certain level, things can change significantly.
A new employer can evaluate your past performance through interviews, portfolios, and references. What they cannot do is evaluate your future potential the way a manager who has watched you grow over two or three years can. If you arrive as a senior engineer, you will almost certainly be hired as one.
The promotions that actually changed my career trajectory—from senior to staff engineer, then engineering manager—all happened at one organization over four years. Those transitions required someone to observe my growth over time and make a bet on where I was headed next. That kind of credibility cannot be transferred on a resume.
So when should you actually leave?
The threshold I use is straightforward. If I have produced at least one measurable, clearly definable outcome at an organization, I have a reasonable basis for leaving. Impact, not tenure, is my unit of measure.
I personally think that moving deliberately while early in your career will build a strong compensation baseline.
Then become selective.
Find an environment where real growth is available and stay long enough to build the credibility that job hopping cannot manufacture. Neither constant movement nor blind loyalty is the answer. The question worth asking at every stage is simple: Have I produced something meaningful here yet? If the answer is no, stay. If yes, it might be time to decide what’s next.
—Brian
What if robots didn’t just help us with physical tasks? USC Professor Maja Matarić helped define the era of socially assistive robotics, designed to provide personalized therapy and care through social interactions. Despite her influence in the field now, the award-winning roboticist didn’t see herself as an engineer at first.
Steve Jobs is best known as the co-founder and CEO of Apple. But the 12 years he spent away from the company taught him the lessons necessary for his success. A new book tells the forgotten story of Jobs’ “wilderness” years and what he learned while at NeXT Computer. IEEE Spectrum spoke to the book’s author about Apple’s most iconic CEO and the company’s future as it prepares for new leadership under John Ternus.
Cybersecurity consultants have never been more in demand, with data breaches and attacks costing organizations more than US $10 trillion annually to repair. To help you find the skills you need to stand out in the cybersecurity job market, the IEEE Computer Society offers a “What Makes a Great Cybersecurity Consultant” guide. It includes advice from experts, a list of certifications to pursue, and information on key cybersecurity conferences.
2026-06-10 02:02:32
This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!
There is no shortage of people telling recent engineering graduates that their degree was a mistake and that AI is coming for their jobs before they even land one. I respectfully disagree.
I have been a software engineer for 12 years, done well over 100 interviews on both sides of the table, and run Parsity, an AI engineering program. A few patterns emerge consistently in who actually breaks through in today’s job market. Here’s why I think the job market isn’t as dire as it looks, and what I would do if I were looking for my first tech job.
The Federal Reserve Bank of New York recently placed unemployment for recent CS graduates in the United States at 6.1 percent, with computer engineering graduates at 7.5 percent. Compared to philosophy majors at 3.2 percent and art history graduates at 3.0 percent, those figures look alarming. They require more context than most headlines provide.
When researchers factor in underemployment (graduates working jobs that don’t require a college degree), then engineers are doing relatively well, coming in below 20 percent, against a 42 percent average across all recent graduates. Many majors reporting lower unemployment are achieving that figure by accepting work entirely unrelated to their field. Scored across unemployment, underemployment, and early-career earnings together, CS and computer engineering still rank among the top fields for overall labor market outcomes.
The degree is not the problem. The hiring pipeline is. Job postings labeled “entry-level software engineer” grew roughly 47 percent between late 2023 and late 2024, while actual hiring into those roles dropped approximately 73 percent in the same window. So-called “ghost jobs,” used to create an illusion of company growth, are everywhere. This makes the front door harder to find, but it exists.
Do a broad search of your (real-life) network. Roughly 26 percent of job offers come through referrals. Look at your actual network—classmates, professors, past internship contacts, relatives—and identify people at companies that might be hiring. The goal is a warm introduction to someone who is or knows a decision maker. One introduction carries more weight than a hundred cold applications through a portal.
Find symmetric risk. A junior engineer is a risky hire by definition. A startup carries a matching risk profile, meaning potentially lower compensation, no certainty of longevity, and higher performance expectations. But that shared risk creates mutual interest. The learning curve is steep, the exposure is broad, and the track record transfers directly. For engineers whose longer-term goal is a large organization, a startup is not a detour. It can be how you build the experience those organizations eventually want to see. The first job is for validation and learning. It is not a life sentence.
Manufacture experience rather than waiting for it. Employers want experience but will not hire you to get it. The way through is to create it: a deployed project, an open-source contribution, building something real for a small business or family member. Recruiters are skeptical of toy projects. A deployed application solving a real problem, combined with the ability to talk clearly about the decisions you made and why, still moves the needle.
Gain practical AI engineering skills, not just AI tool fluency. Using Cursor or Copilot is now a baseline expectation. What differentiates candidates is going one level deeper. Most working engineers, including senior ones, have not built a RAG pipeline or designed a multi-agent system. Understanding how to chunk documents, generate embeddings, store and query them from a vector database, and wire it into a production application puts a candidate ahead of a significant portion of the market on a skill in rapidly growing demand. AI and data science roles grew 163 percent in job postings in 2025. The engineers who understand how these systems actually work, not just how to prompt them, are in the shortest supply.
Stop optimizing around conditions you cannot predict. Nobody anticipated the 2021 hiring boom. Nobody predicted this correction. Build durable skills. The demand for engineers who can reason clearly about systems is not going away. Where you start is not where you end.
—Brian
More major workforce reductions are on the horizon at Big Tech companies: Meta announced it will cut 10 percent of its workforce, or about 8,000 employees, and Microsoft plans to offer buyouts for 7 percent of its U.S. employees in a voluntary retirement program. The cuts are understood by many to be linked to AI. But is AI really to blame? For The Conversation, two academics at the University of Sydney give their two cents.
Tom Burick got his start as a roboticist. But when a financial downturn forced him to close his robotics business, he thought of the effect teachers had on his life and decided to pay it forward. Burick now works as a technology instructor at a school for students with autism, where he recently led a project building a full-scale replica of ENIAC, an historic computer celebrating its 80th anniversary this year.
Across several industries, the United States has been moving toward limiting the use of sensitive technology made in China. Now, legislation has been introduced to extend the trend to ground robots, including humanoids, dogs, and crawlers. This could benefit some U.S.-based robotics firms—but many of these companies still rely on Chinese-made components. “The U.S. robotics industry is in a pickle,” writes Spectrum tech policy editor Lucas Laursen.
2026-06-09 20:51:03
This article is brought to you by AGILINK.
Throughout the exhibition hall at the 2026 IEEE International Conference on Robotics (ICRA), in Vienna, one demonstration seemed to attract a disproportionate amount of attention.
Two robotic hands were making a balloon dog. Slowly and deliberately, the robot twisted a long balloon into loops, bends, and joints without popping it. Visitors stopped, watched, and often returned with colleagues to watch again.
AGILINK’s balloon dog demonstration draws a crowd at ICRA 2026.AGILINK
At first glance, the demonstration appeared almost playful. Among roboticists, however, balloon twisting is widely recognized as an unusually difficult manipulation task.
A balloon is lightweight, highly deformable, slippery, and extremely sensitive to force. Every twist changes its geometry and internal pressure, turning a seemingly simple activity into a continuously changing physical interaction problem.
Humans navigate those changes almost intuitively. While making a balloon animal, people rarely think consciously about force regulation, slip prevention, or contact stability. They simply adjust.
For robots, those adjustments remain remarkably difficult. The challenge is not merely moving fingers to the right positions. The harder part is maintaining stable interaction while the object itself is changing.
Highlights from AGILINK’s ICRA 2026 demonstrations, including visuotactile sensing, in-hand manipulation, balloon-animal shaping, and other contact-rich tasks enabled by the company’s latest OmniHand platform.AGILINK
That distinction helps explain why the balloon dog drew so much attention in Vienna. What appeared to be a dexterity demonstration was, in many ways, a demonstration about contact itself.
As robotic manipulation continues to advance, a growing number of researchers are arriving at a similar conclusion: many of the hardest problems in robotics begin only after contact occurs.
Balloon twisting combines two challenges that robotics has traditionally struggled to solve simultaneously: long-horizon task execution and contact-rich manipulation.
The first concerns motion.
A balloon dog is not created through a single grasp or twist. It emerges through a carefully ordered sequence of manipulations, each setting the conditions for what follows. A small rotational error introduced early may appear insignificant at first, yet several steps later it can prevent the final structure from forming altogether.
In that sense, balloon twisting is a long-horizon task. Success depends not only on performing individual actions correctly, but also on preserving the future feasibility of the entire manipulation process.
To address this challenge, AGILINK began by collecting demonstrations from professional balloon artists. Human actions were mapped onto robotic hands to establish an initial manipulation policy. But successful demonstrations alone were insufficient.
In practice, some of the most valuable learning occurred when execution began to drift toward failure. Whenever instability emerged, human operators intervened and corrected the manipulation in real time. Those interventions were recorded and incorporated into reinforcement-learning cycles, allowing the system to learn not only how successful demonstrations unfold, but also how experienced operators recover when things start to go wrong.
Through this process, the robot gradually acquired the capabilities required for long-horizon task execution—a collection of abilities that AGILINK groups under the term motion intelligence: the ability to generate actions, coordinate bimanual behaviors, and execute extended manipulation sequences under real-world uncertainty.
OmniHand 3 Ultra-M on display at ICRA 2026.AGILINK
Yet motion alone does not explain why balloon twisting remains difficult. The second challenge is contact.
The robot must continuously regulate force, adjust contact locations, and respond to subtle changes in the object’s state. These decisions are difficult to encode through explicit rules. Even skilled human operators often rely on tactile intuition developed through experience rather than consciously articulated strategies.
Analysis of those interventions revealed that many failures did not originate from incorrect action sequences, but from the breakdown of contact itself.
To better capture those interaction dynamics, AGILINK collected contact-centric intervention data and incorporated those interactions into reinforcement-learning training. Rather than learning only which motions to perform, the system also learned how humans maintain stability when contact conditions begin to deteriorate.
AGILINK describes this capability as contact intelligence: the ability to establish, maintain, and adapt physical interaction as force distribution, friction, deformation, and contact geometry continuously evolve.
The distinction between the two capabilities is subtle but important. Motion intelligence determines what the robot intends to do. Contact intelligence determines whether it can continue doing it. For balloon twisting, both are necessary. One provides the sequence of actions. The other keeps those actions physically viable.
YouTuber KhanFlicks follows OmniHand’s motions while learning to fold a balloon dog at the AGILINK booth.AGILINK
Between a balloon slipping away and a balloon bursting lies a narrow region of stability. Successful manipulation depends on finding that region—and remaining within it throughout the task.
The balloon dog demonstration showcased a manipulation capability. It also revealed a broader question. How much contact intelligence can be achieved through learning alone? A robot can only regulate what it can perceive. It can only respond as quickly as its hardware allows.
As manipulation tasks become increasingly complex, researchers are finding that progress depends not only on better policies, but also on richer sensing and faster physical response.
That realization formed the backdrop for AGILINK’s second major announcement at ICRA 2026. Alongside the balloon dog demonstration, the company introduced the OmniHand 3 Ultra-M.
OmniHand 3 Ultra-M closely matches the size of an adult human hand.AGILINK
The two exhibits represented different stages of the same technological trajectory. If the balloon dog demonstrated what contact intelligence can already accomplish today, Ultra-M was designed to explore what contact intelligence may require next.
Roughly the size of an adult human hand, the OmniHand 3 Ultra-M integrates 20 active degrees of freedom within a human-scale form factor.
Its most distinctive feature is a fully direct-drive architecture. By adopting direct-drive actuation throughout the system, the hand is designed to enable faster and more transparent force regulation and higher force-control bandwidth, enabling faster response as contact conditions change. For contact-rich manipulation, responsiveness can be as important as sensing itself.
By adopting direct-drive actuation throughout the system, the OmniHand 3 Ultra-M is designed to enable faster and more transparent force regulation and higher force-control bandwidth, enabling faster response as contact conditions change.
The platform also incorporates tactile sensing across nearly the entire hand. Each fingertip contains a miniature vision-based tactile sensor, while more than 300 three-dimensional tactile sensing points are distributed throughout the palm. Together, they provide information not only about where contact occurs, but how contact is evolving.
The system is designed to estimate pressure distribution, shear forces, local deformation, slip tendencies, and other interaction dynamics that often remain invisible to conventional position-based control systems.
According to AGILINK’s tests, individual sensors achieve force resolution of approximately 0.005 N—roughly equivalent to detecting the weight of a sheet of paper resting on a fingertip. Spatial resolution reaches approximately 0.04 mm, while sensing density approaches 50,000 sensing points per square centimeter.
OmniHand 3 Ultra-M recognizes feather texture through vision-based tactile sensing.AGILINK
For dexterous robots, contact has traditionally been a largely hidden process. Ultra-M is designed to make that process more observable.
Rather than simply detecting that contact has occurred, the system attempts to resolve where interaction is happening, how forces are distributed, whether instability is beginning to emerge, and how manipulation strategies should adapt in response.
The balloon dog offered a glimpse of what contact intelligence can already accomplish. Ultra-M explores a different question: what capabilities may be required to push contact intelligence further?
The significance of contact intelligence extends far beyond balloon animals. Many tasks that continue to resist automation involve unstable or deformable interaction: cable insertion, garment handling, flexible packaging, delicate assembly, connector mating, tool use, and household manipulation.
These tasks are difficult not because robots cannot reach the correct location, but because maintaining stable interaction after contact begins remains extraordinarily hard.
For decades, robotics achieved many of its successes by reducing uncertainty. Factories were engineered to make robotic motion predictable, repeatable, and highly structured. The physical world behaves differently.
A growing share of robotics research is shifting toward interaction itself—understanding how robots can establish, maintain, and adapt physical contact within environments that remain fundamentally unpredictable.
Objects shift. Materials deform. Friction changes. Contact evolves. Real environments rarely follow scripts. Seen through that lens, the balloon dog was never really about the balloon dog. What attracted attention at ICRA was not simply a visually impressive demonstration, but what it revealed: intelligence in the physical world is ultimately measured through interaction.
As motion generation continues to mature, a growing share of robotics research is shifting toward interaction itself—understanding how robots can establish, maintain, and adapt physical contact within environments that remain fundamentally unpredictable.
For robots moving beyond structured environments and into less predictable real-world settings, managing contact may become as important as motion itself.
2026-06-09 02:00:02
New York City was the backdrop of this year’s IEEE Honors Ceremony, held on 24 April.
The event celebrates engineering pioneers who have developed technologies that have changed how people connect and learn about the world. This year’s celebrants included the engineers behind innovations such as text-to-donate technology, AI-powered diagnostic tools, and the graphics processing unit, among many others.
Prior to the Honors Ceremony, IEEE hosted a forum on 23 April for a select group of early-career achievers to exchange ideas and experiences with laureates and awardees, speakers, and IEEE leaders. Attendees from around the world, working in a variety of technical areas, shared their journeys and explored the intersections of technologies, disciplines, and missions.
The event culminated in Friday evening’s black tie Honors Ceremony, where IEEE celebrated medal laureates, including Jensen Huang, who received IEEE’s highest recognition, the IEEE Medal of Honor. Huang is a cofounder of Nvidia and its chief executive.
“IEEE has always been a home to those who see the future before others see it,” Mary Ellen Randall, IEEE president and CEO, said in her welcome speech.
Video highlights and photos from the event are available on the IEEE Awards website.
Friday morning began with a conversation between Randall and Marian Croak, the recipient of this year’s IEEE Founders Medal. Croak was honored for “leadership in communication networks, including acceleration of digital equity, responsible artificial intelligence, and the promotion of diversity and inclusion.”
Croak, who serves as vice president of engineering at Google, headquartered in Mountain View, Calif., pioneered Voice over Internet Protocol (VoIP) technologies. When a person speaks into a telephone, VoIP converts their voice into digital signals that are transmitted over the Internet rather than traditional phone lines. Her work enabled audio and video conferencing. She also developed text-to-donate technology to raise money for those affected by Hurricane Katrina, which devastated New Orleans in 2005. The technology enables customers to donate money to a charity via their mobile service provider, which then bills them.
“Empathy has always been a driving force in the engineering that I’ve done,” she said.
She shared advice on how to stay creative: “Get out of the office. Go to an art museum, exercise, or play with children.” Croak said her grandchildren inspire her.
During Friday evening’s Honors Ceremony cocktail hour, attendees explored the history of microchips at the IEEE Global Museum’s Microchips That Shook the World exhibit. The Global Museum, an IEEE History and Heritage program, develops traveling and digital exhibits focused on the history of technology. The museum’s mission is to promote awareness of how technological progress unfolds over generations and how engineers and researchers build on past achievements to benefit humanity.
Drawing from IEEE Spectrum’s Chip Hall of Fame, the Microchips That Shook the World exhibit conveys the roles integrated circuits play in fields such as signal processing, audio engineering, and telecommunications.
Co-curators Stephen Cass, Spectrum’s special projects editor, and Daniel Mitchell, the IEEE senior historian, served as onsite docents for guests. The Commodore 64, one of the artifacts on display, brought up many treasured childhood memories for guests who used the home computer. The exhibit also featured a preview of IEEE’s immersive video project “Inside the Microchip,” which delves beneath the silicon surface of the Nvidia NV20 microchip thanks to forensic photography and sophisticated computer-generated renders. The video, which will be released later this year, aims to teach preuniversity students about the technology.
Microchips that Shook the World is possible thanks to donations from semiconductor company ASML, the Bill and Dianne Mensch Foundation, and the IEEE Electron Devices and IEEE Electronics Packaging societiesThe daytime program also spotlighted AI’s use in the visual arts. Kathleen Kramer, the 2025 IEEE president, interviewed artist Refik Anadol, who is scheduled to open an AI art museum on 20 June in Los Angeles. Dataland’s exhibits are powered by an open-access model developed by Anadol’s studio.
For the museum’s first exhibition, “Machine Dreams: Rainforest,” the model collected visual data about the natural world from the Smithsonian National Museum of Natural History, London’s Natural History Museum, and the Cornell Lab of Ornithology, with their permission. The information, including up to a half billion images, will form the basis for a variety of AI-produced art, Anadol said.
Anadol said he was inspired to mix AI with art by the movie Blade Runner. He said he believes “machines can become collaborators,” as “data is a form of pigment.”
Data also plays an important role in the work of artist and author Giorgia Lupi. The artist is a partner at design firm Pentagram.
Lupi said she uses data to tell stories, including chronicling her struggles with a chronic illness.
“Data is an abstraction of our reality,” she said.
One of her recent projects, “A Data Love Letter to the Subway,” was shown last year in the Dey Street Passageway in New York City. The video was made using data from the Metropolitan Transportation Authority about each train line, including timetables, ridership, and people’s travel habits. Based on the information Lupi gathered, she documented how commuters traveling on different subway lines encountered one another without realizing it.
By exploring data on this year’s IEEE award recipients, she collaborated with IEEE to create an animated video illustrating the shared pathways and collaborations among the honorees. It debuted at the Honors Ceremony.
The Honors Ceremony, held at Cipriani 42nd Street, recognized more than 20 laureates and innovators.
More than 92 million selfies are taken worldwide every day, PhotoAiD estimates. A selfie wouldn’t be possible without Eric Fossum’s invention of the CMOS image sensor. Developed at NASA’s Jet Propulsion Laboratory, in Pasadena, Calif., the “camera on a chip” was intended for use in space, but it is now found in smartphones, medical devices, and vehicles. Fossum, an IEEE Life Fellow, received the IEEE Jun-ichi Nishizawa Medal, which recognizes outstanding contributions to materials and device science and technology.
“Engineering is a pursuit of what must be possible. [IEEE is] the spirit, the conscience, of our profession.” —Jensen Huang, founder and CEO of Nvidia
The medal, he said, “is at the top of the IEEE staircase of being recognized by your peers.”
The IEEE Holonyak Medal for Semiconductor Optoelectronic Technologies went to Steven P. DenBaars, a professor of materials and electrical and computer engineering at the University of California, Santa Barbara. DenBaars was honored for his work in semiconductors, which laid the foundation for high-resolution LED and laser displays, modern solid-state lighting, and more.
“This work has always been a team effort...I’m excited and curious about the role gallium nitride micro LEDs will play in optical communications,” he said in his acceptance speech.
The ceremony ended with the Medal of Honor presentation to Huang, who received a standing ovation. He was recognized for his “leadership in the development of graphics processing units and their application to scientific computing and artificial intelligence.”
The IEEE honorary member donated his cash prize to IEEE TryEngineering, which provides teachers with a library of lesson plans and offers educational summer camps. The Jen-Hsun and Lori Huang Foundation matched his gift, and the additional donation is destined to fund scholarships for new graduates.
“Engineering is a pursuit of what must be possible. [IEEE is] the spirit, the conscience, of our profession,” Huang said.
2026-06-06 02:00:01
The Institute is celebrating its 50th anniversary this year. Launched in 1976, the publication was designed to keep members informed about IEEE and what its constituents were doing, as well as to report on the organization’s initiatives, technical standards, products, and services.
That directive expanded over the years to include our reporting on key historical technical achievements recognized as IEEE Milestones and support for young professionals with career-guidance articles and information about educational resources.
The Institute has gone through many iterations in the past 50 years. What began as a monthly four-page insert in the print edition of IEEE Spectrum became a separate newspaper published six times a year and mailed along with Spectrum in 1977, and then a monthly publication the following year.
Today we publish all of The Institute’s articles online, with a curated selection appearing in our 16-page quarterly printed in the March, June, September, and December Spectrum issues.
To provide members with a quick summary of the latest online news, in 2003 a bimonthly newsletter, The Institute Alert, began appearing in your inbox. You also can stay up to date by following our Facebook, Instagram, and LinkedIn pages.
Although much has changed, an original subsection from 1976—“IEEE People”—has been maintained for the past five decades. We continue to celebrate IEEE members from around the world through our profiles, which are among our most popular articles.
As the longest-serving editor in chief for The Institute, it is a privilege for me and my staff to chronicle the stories of remarkable IEEE individuals. They are often-unseen visionaries and problem-solvers who work tirelessly behind the scenes on technologies that are reshaping the world. By highlighting their careers and how IEEE has played a role in their professional growth, we hope to inspire the next generation of engineers and technologists to continue a legacy of innovation and service to humanity.