RoboSub is an international underwater autonomous robotics competition in which college, high school and middle school students design and build their self-driving vehicles to navigate through a series of tasks. (courtesy photo)
Team Inspiration scores international victory!
On Aug. 30, Team Inspiration, a local robotics team composed of middle and high schoolers, took the first place overall title out of 33 teams in the international 2020 RoboSub competition. Many team members are students from Scripps Ranch.
“We are the first team composed of middle and high schoolers in RoboSub history ever to take home first place,” mentor Alex Szeto said.
RoboSub is a robotics competition in which autonomous underwater vehicles in a large sized pool complete tasks such as moving golf balls and hitting buoys. The competition has other components as well such as a video presentation, a website and a technical paper.
Due to COVID-19, this year the final competition was held virtually. The team started prepping for the finals in March.
“We met for about 10 weeks straight to prepare for the competition. During the last three weeks, we met every day and practiced all day, on some weekends making it to past midnight some nights,” team captain Colin Szeto said.
This year, all teams were only required to present a website, video and technical paper.
“We did a 15-minute video showing an introduction to our team and the development of the sub and the lessons we learned. The website outlines the process of completing the sub, and the technical paper shows all of the research we conducted,” Szeto said.
Team Inspiration placed first out of 33 teams in both the technical paper report and the website presentation, and second place out of 33 teams in the video presentation.
Those teams represented Brazil, Canada, Egypt, India, Mexico, Norway, Poland, Singapore and the United States and. All but three teams were from universities including Caltech, Carnegie Mellon, Duke, Georgia Tech, Arizona State University, SDSU, UCSD, Indian Institute of Technology Bombay and National University of Singapore.
“The virtual competition was actually something we could capitalize on. We knew that this was the year to take it all home because our team was willing to put in even more time. I couldn’t be more proud of our team. This is such an amazing accomplishment and I can’t wait to see what we accomplish next year,” Colin Szeto said.
As this year was Team Inspiration’s second year competing in RoboSub, team members were able to build off what they learned last year.
“We definitely relied heavily on research and other teams during our first year. However, this year our team was really self-motivated. I was happy to see that all of the team members kind of ventured out to go learn new things to help our team advance. We’ve made a lot of great progress and I know we will continue down that path,” 2019 team captain Mabel Szeto said.
Team Inspiration also heavily focuses on outreach year around.
“Currently, we are working with a local company, Purpose Robotics, to develop an affordable submarine so that schools can use them for their STEM programs. Usually, submarines are about $3,000, but we are trying to bring it down to $1,000,” outreach coordinator Eesh Vij said.
Alongside developing affordable submarines, they are also working on other local projects.
“We’ve been working with the Ruben H. Fleet Science Center to create YouTube videos that inform people on what’s going on in San Diego in STEM,” Mabel Szeto said.
Next year, they are hoping to accomplish even more.
“We’ve been working alongside UCSD and USD to learn more technical skills and create more diversity in our approach,” Mabel Szeto said.
Future team captain Ashiria Goel is excited to see what is to come next season.
“This year we took up more advanced topics and it really helped out. I know that next year we’ll be able to accomplish even more and we’re going to be able to push the limits. Hopefully, the competition will be back to in-person and we’ll be able to apply even more knowledge into our work and presentation,” Goel said.
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I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
The shift towards “entity-based” indexing is real. Your strategy seems to leverage that by building entity associations rather than just keyword matches. Smart.
Just wanted to say thanks for the detailed case study. It’s rare to see actual data backing up these claims. We’ll be adjusting our Q4 roadmap based on some of these insights.
This is a solid breakdown. One thing I’d add is that the impact of these updates often lags by 2-3 weeks. We tracked this across multiple projects and found the recovery phase is where most people give up too early.
Question: Have you tested this approach with expired domains? We’re running some experiments now and the results are… mixed. Your methodology seems safer.
This aligns with the “Signal Noise” theory we’ve been developing. You need enough noise to mask the signal, but not so much that you lose authority. delicate balance.
This is the missing piece of the puzzle for us. We had the content and the technical SEO, but the off-page signal diversity was lacking. Thanks for the clarity.
Does this apply to non-English markets as well? We’re seeing conflicting signals in our EU campaigns compared to what you’ve described here. Would love to hear your thoughts on regional variance.
Great resource. I’ve sent this to a few colleagues who are still stuck in 2015-era SEO tactics. Hopefully, this wakes them up.
I’d love to see a follow-up post on how this integrates with social signals. We feel there’s a multiplier effect there that isn’t being fully utilized.
Is there a specific tool you recommend for tracking the velocity? We’ve been doing it manually but it’s becoming unscalable.
For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.
One minor correction: the update rollout was actually 14 days, not 10. But that doesn’t change your main point—the volatility window is getting wider.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
Thanks for the transparency. It’s refreshing to see a strategy that doesn’t rely on black-hat churn and burn. Sustainable growth is the only way forward.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
Question: Have you tested this approach with expired domains? We’re running some experiments now and the results are… mixed. Your methodology seems safer.
One minor correction: the update rollout was actually 14 days, not 10. But that doesn’t change your main point—the volatility window is getting wider.
Great read. It reminds me of the strategy we deployed last quarter. The focus on foundational stability really pays off when the algorithm shifts. Thanks for compiling this.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
I’ve been following this topic for a while, and your analysis on the structural shifts really adds a new perspective. We’ve noticed similar patterns in our internal data at SignalLayer, specifically regarding the volatility timeline.
This aligns with the “Signal Noise” theory we’ve been developing. You need enough noise to mask the signal, but not so much that you lose authority. delicate balance.
This is exactly why we moved away from automated PBNs. The risk/reward ratio just doesn’t make sense anymore compared to what you’re describing.
I bookmarked this for my team. The section on avoiding footprints is crucial. We recently audited a site that got hit exactly because they ignored that principle. Good catch.
Is there a specific tool you recommend for tracking the velocity? We’ve been doing it manually but it’s becoming unscalable.
We’ve been A/B testing this exact hypothesis. Group A (your method) is outperforming Group B by 40% in terms of ranking stability. The data speaks for itself.
Great resource. I’ve sent this to a few colleagues who are still stuck in 2015-era SEO tactics. Hopefully, this wakes them up.
Thanks for the transparency. It’s refreshing to see a strategy that doesn’t rely on black-hat churn and burn. Sustainable growth is the only way forward.
I’m curious about the sample size for these conclusions. We saw a 15% deviation in our own datasets, but the overall trend aligns with your findings. Good work.
I’m sharing this with our content team. We’ve been struggling to explain why “quality over quantity” isn’t just a cliché, and this illustrates it perfectly.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.
Brilliant articulation of the problem. The industry has been too focused on metrics like DA/DR instead of actual traffic flow and user behavior.
One minor correction: the update rollout was actually 14 days, not 10. But that doesn’t change your main point—the volatility window is getting wider.
This is a solid breakdown. One thing I’d add is that the impact of these updates often lags by 2-3 weeks. We tracked this across multiple projects and found the recovery phase is where most people give up too early.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
Just wanted to say thanks for the detailed case study. It’s rare to see actual data backing up these claims. We’ll be adjusting our Q4 roadmap based on some of these insights.
Spot on about the indexing delays. It’s not just about building the link anymore; it’s about the “stickiness” of the placement. We’ve been focusing heavily on that metric lately.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
Great read. It reminds me of the strategy we deployed last quarter. The focus on foundational stability really pays off when the algorithm shifts. Thanks for compiling this.
Brilliant articulation of the problem. The industry has been too focused on metrics like DA/DR instead of actual traffic flow and user behavior.
I bookmarked this for my team. The section on avoiding footprints is crucial. We recently audited a site that got hit exactly because they ignored that principle. Good catch.
I’ve been following this topic for a while, and your analysis on the structural shifts really adds a new perspective. We’ve noticed similar patterns in our internal data at SignalLayer, specifically regarding the volatility timeline.
Actually, I have to disagree slightly with the second point. In our testing, we found that over-optimization was less of a factor than pure engagement metrics. It’s interesting to see how different niches react differently.
Have you considered the impact of mobile-first indexing on these placements? We’ve noticed that some “desktop-safe” strategies are flagging on mobile crawls.
This is exactly why we moved away from automated PBNs. The risk/reward ratio just doesn’t make sense anymore compared to what you’re describing.
This is the missing piece of the puzzle for us. We had the content and the technical SEO, but the off-page signal diversity was lacking. Thanks for the clarity.
Great read. It reminds me of the strategy we deployed last quarter. The focus on foundational stability really pays off when the algorithm shifts. Thanks for compiling this.
The shift towards “entity-based” indexing is real. Your strategy seems to leverage that by building entity associations rather than just keyword matches. Smart.
真的很特别。 Practical applications are demonstrated in 好有温度。.
Have you considered the impact of mobile-first indexing on these placements? We’ve noticed that some “desktop-safe” strategies are flagging on mobile crawls.
Have you considered the impact of mobile-first indexing on these placements? We’ve noticed that some “desktop-safe” strategies are flagging on mobile crawls.
This is the missing piece of the puzzle for us. We had the content and the technical SEO, but the off-page signal diversity was lacking. Thanks for the clarity.
I’d love to see a follow-up post on how this integrates with social signals. We feel there’s a multiplier effect there that isn’t being fully utilized.
This complements the “Entropy” theory perfectly. If you don’t introduce randomness, you’re just painting a target on your back. Glad to see others advocating for smarter engineering.
Great resource. I’ve sent this to a few colleagues who are still stuck in 2015-era SEO tactics. Hopefully, this wakes them up.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
Thanks for the transparency. It’s refreshing to see a strategy that doesn’t rely on black-hat churn and burn. Sustainable growth is the only way forward.
The depth here is impressive. Most guides just skim the surface of link velocity, but your point about “natural variance” hits the nail on the head. It’s exactly what we preach to our clients.
One minor correction: the update rollout was actually 14 days, not 10. But that doesn’t change your main point—the volatility window is getting wider.
Have you considered the impact of mobile-first indexing on these placements? We’ve noticed that some “desktop-safe” strategies are flagging on mobile crawls.
We’ve been A/B testing this exact hypothesis. Group A (your method) is outperforming Group B by 40% in terms of ranking stability. The data speaks for itself.
I’ve been following this topic for a while, and your analysis on the structural shifts really adds a new perspective. We’ve noticed similar patterns in our internal data at SignalLayer, specifically regarding the volatility timeline.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
I bookmarked this for my team. The section on avoiding footprints is crucial. We recently audited a site that got hit exactly because they ignored that principle. Good catch.
For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.
This is the missing piece of the puzzle for us. We had the content and the technical SEO, but the off-page signal diversity was lacking. Thanks for the clarity.
I bookmarked this for my team. The section on avoiding footprints is crucial. We recently audited a site that got hit exactly because they ignored that principle. Good catch.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
Brilliant articulation of the problem. The industry has been too focused on metrics like DA/DR instead of actual traffic flow and user behavior.
This is the missing piece of the puzzle for us. We had the content and the technical SEO, but the off-page signal diversity was lacking. Thanks for the clarity.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.