Every year, thousands of skilled foreign workers in tech apply for the H-1B visa in the United States, hoping for one of the tens of thousands of slots available. Many, despite strong credentials and deep expertise, are shut out. The H-1B visa lottery system is unpredictable — even for those with master’s degrees or deep experience. For some, repeated failures are demoralizing.
This was the story of Tanush Sharanarthi. Originally from Bangalore, India, with a master’s degree in information systems and artificial intelligence, and a job at IBM, he applied for H-1B three times — each time unsuccessful. But rather than giving up, he pivoted to another visa route: the O-1 visa, often referred to as the “Einstein visa.” Based on his work in AI — publications, peer reviewing, hackathon judging — he demonstrated “extraordinary ability” and secured the O-1 in just 12 business days with premium processing.
His journey reveals much about the cracks in the H-1B system, the advantages and challenges of the O-1/“Einstein” route, and what people in STEM fields must do to qualify. This article unpacks his path, the visa systems, criteria, challenges, and lessons for others who may find H-1B blocked but believe in their own stars.
The H-1B Visa System: Promise and Pitfalls
What Is H-1B and Why It Matters
The H-1B visa is a non-immigrant work visa that allows U.S. companies to employ foreign workers in “specialty occupations” — typically roles requiring highly specialized knowledge or a bachelor’s degree or higher. Tech companies, research labs, universities, and engineering firms rely heavily on H-1B to bring in talent.
The number of H-1B visas is capped annually. As of recent years, about 85,000 regular H-1B slots are available, with an additional 20,000 reserved for those with U.S. master’s degrees or higher. Because demand far exceeds supply, USCIS runs a lottery to decide who gets selected. This makes the process highly uncertain, even for candidates with excellent credentials.
Limitations and Frustration
For many applicants, the H-1B path feels like playing slots:
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Unpredictability: You can have excellent qualifications — advanced degrees, strong job offers — and still lose the lottery.
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Dependence on Employer: The visa is employer-sponsored. Changing jobs or employers involves legal and administrative hurdles.
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Cap Limits and Timing: The annual cap and fixed application windows mean you sometimes have to wait a full year or more if you miss.
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Cost: Employer fees, legal fees, time delays add up. Even after getting it, renewals and extensions bring further uncertainty.
Tanush applied three times with IBM under Optional Practical Training (OPT) status after his master’s. Despite being eligible, despite working in AI and publishing, he was never selected. It wasn’t lack of effort, but structural limits.
The O-1 Visa: The “Einstein Visa” Alternative
What Is the O-1 Visa
The O-1 visa is a nonimmigrant classification for individuals who show “extraordinary ability” in sciences, arts, education, business, or athletics. There are two primary subclasses relevant in STEM/AI:
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O-1A: For extraordinary ability in sciences, business, education, or athletics.
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O-1B: For arts, or extraordinary achievement in motion picture or television.
Unlike H-1B, the O-1 has no annual cap or lottery. Applications are accepted on a rolling basis, and with premium processing, can be adjudicated quickly. The visa typically grants stay for up to three years initially, and extensions are possible. Evidence must show sustained acclaim, recognition, and contribution at a high level in the field.
Criteria for O-1 and EB-1A (“Einstein Visa” vernacular)
“Oversimplified” or “popular-usage” descriptions often call both O-1 and EB-1A visas variations of the “Einstein visa.” But there are key differences:
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O-1 is nonimmigrant (you must renew or adjust status).
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EB-1A is an immigrant visa category (green card) — permanent residence — for those with extraordinary ability. Sometimes called the “Einstein visa” too.
Criteria for O-1 according to USCIS: you must collect evidence of extraordinary ability, which may include:
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Publications in respected journals or media.
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Judging the work of others or participating as peer reviewer.
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Receipt of awards, prizes, or recognition in your field.
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Original contributions of major significance.
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Roles of prominence in distinguished organizations.
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A high salary or remuneration relative to peers.
To qualify for EB-1A (green card), you either need a one-time major achievement (e.g., Nobel, major international award) or satisfy at least three of a similar set of criteria — often overlapping with O-1 ones — plus pass a final merits determination of whether your overall contributions show “sustained national or international acclaim.”
Tanush’s Journey: From Frustration to Accomplishment
Background and Early Struggles
Tanush Sharanarthi grew up in Bangalore, India. After completing a master’s degree in information systems and artificial intelligence at Johns Hopkins University, he worked under OPT (Optional Practical Training) which allowed temporary work authorization. His employer was IBM in the Bay Area. During this time, he applied for H-1B three times. He was not selected any time, even though he had qualifications that many would consider strong (master’s degree, relevant job, contributions to AI). He describes the lottery experience as akin to being at a casino: where chance, not merit, often determines outcome.
Realizing the O-1 Option
After his repeated lottery misses, Tanush heard about the O-1 visa from colleagues. He aligned things he was already doing with the O-1 criteria. Among these:
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Publishing research in AI.
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Reviewing academic papers.
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Judging hackathons.
These are not unusual for someone working in AI over several years, but combined they constituted strong evidence under the O-1 evidentiary standards. He had six years of contributions in AI by this point.
Application and Approval
Tanush applied for the O-1 visa in late August with premium processing. He carefully gathered the required documentation: letters from authorities in the field, proof of publications, evidence of judging, etc. About 12 business days later, the status of his petition changed from “Processing” to “Approved.” He felt mixed emotions: relief, satisfaction, and validation. The process cost him more than some H-1B costs (especially now with new fee hikes), but the speed, lack of lottery, and merit-based evaluation made it worthwhile.
Comparing O-1 vs H-1B: Trade-offs and Considerations
Advantages of O-1
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No lottery: You apply when ready; you don’t need to wait for a limited cap round.
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Faster processing with premium: Approximately 15 business days under premium service.
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Flexibility: More flexibility in roles, sometimes project-based work, multiple employers, not strictly tied to employer in the same way as H-1B (depending on agent-employer arrangements).
Challenges of O-1
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Stringent subjective criteria: You must convincingly demonstrate “extraordinary ability.” Quality of evidence, reputation of recommenders, clarity in documentation matter a lot. Vague or weak evidence often triggers Requests for Evidence (RFEs).
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Cost: Legal fees, documentation gathering, maybe more scrutiny. Also, premium processing adds cost. But still, in many cases, the total cost may be less or comparable to new costs of H-1B for some applicants.
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Renewals and permanence: O-1 is nonimmigrant. For permanent residency or green card, one may still need to go via EB-1A or other immigrant visa paths. Transition from O-1 to EB-1A is possible but not automatic.
What This Means Under Current H-1B Fee Changes
With recent policy changes increasing the H-1B fee dramatically for new applicants, the cost and uncertainty for H-1B have become even more burdensome. For people like Tanush, these changes make the O-1 route more attractive.
The “Einstein visa” path gains attention because it is merit-based, not cap-based. Applicants aren’t subject to random lottery if they meet the criteria. For those who are high achievers in their field, especially in STEM and AI, this option offers a way forward without being blocked by the limitations of H-1B.
Practical Advice: Building an O-1 or EB-1A Case
From Tanush’s experience and expert guidance, here are strategies for tech/AI professionals wanting this visa path:
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Document Early and Widely
Start publishing research, participate in peer reviews, judge academic or industry contests, contribute to open-source projects. -
Media and Visibility
Having media coverage (articles, mentions), speaking roles, or public presentations helps. Using your employer’s profile or joining visible projects adds credibility. -
Letters of Recommendation / Endorsements
Independent and authoritative letters from people recognized in your field are invaluable. They should describe your contributions in concrete terms. -
Show Original Contributions
Patents, algorithm improvements, software tools, research breakthroughs show you’re not just competent but making significant contributions. -
Salary / Compensation Comparisons
Showing that you are well-remunerated compared to peers, or expected to be due to your contributions, helps satisfy the “high salary or compensation” criterion. -
Work with Immigration Experts
Lawyers or consultants experienced in O-1/EB-1A applications can help frame your evidence well, avoid RFEs, and present to the right standard. -
Maintain Activity
Stay active in your field — continued contributions before and after submitting the petition strengthen your case.
Broader Implications: Talent, Policy, and Innovation
Tanush’s story is not unique, nor is it an anomaly. As the U.S. increases fees or adds obstacles for visa categories like H-1B, the O-1/EB-1A path becomes a lifeline for many in tech and AI. For companies, this means talent strategies may shift: recruiting may favor international candidates who already have extraordinary credentials, or who can move faster along merit-based routes.
For policy makers, there is tension: how to maintain fair and accessible immigration systems while preserving high standards. The O-1/EB-1A path is naturally more restrictive, benefiting those who already have visibility and achievements. That raises questions about equity: who gets access to the opportunities and recognition necessary to meet the criteria?
Still, expanding awareness of O-1 / EB-1A benefits both potential applicants and employers. As the demand for AI, machine learning, innovation grows, the U.S. remains in competition for global talent. Visa policy is a major factor.
Losing Lottery, Winning Merit
The lottery model of the H-1B visa has left many capable, passionate, and deserving individuals temporarily blocked from contributing in the U.S. But for Tanush and others like him, the “Einstein visa” path offered an alternative way – one rooted not in chance but in proven contribution.
Tanush’s journey shows that repeated failure at H-1B need not be the end. Instead, it can be a signal: refine your work, gather visible accomplishments, build in public, contribute to your field, and prepare. When the criteria align, recognition follows, and with it, visa pathways that were previously opaque become clear.
For AI professionals, researchers, engineers frustrated by H-1B’s randomness, Tanush’s story is a guide: merit, documentation, visibility, and persistence can unlock the doors that the lottery shuts.
