Over the years, Rumen has been part of the national team of Bulgaria in informatics. He is seventh in the Hall of Fame of the IOI (International Olympiad in Informatics) – an outstanding achievement for the country. Rumen is a long-time participant in the international programming competition CodeIT, in 2012 he is a winner, and in the 2020/2021 season he gives a special lecture as an IT guru at the final of the competition.

Rumen Hristov was also elected in Forbes 30 Under 30 in the United States for his work on remote health monitoring.

Rumen tells DevStyleR more about the challenges he faces in the vast technological world. He also reveals what are the qualities needed for success not only in competitions and Olympiads, but also in life. He also shares with us his enjoyable experiences in one of the oldest competitions in the world – CodeIT and what it feels like to be part of the Forbes 30 under 30 in the US. You will read all this and many more interesting topics in our interview.

You are 7th in the Hall of Fame of the International Olympiad in Informatics (IOI). What are the qualities that make up a successful IT competitor?

Competitions in Informatics were an extremely important part for me and opened many doors in my life. Thanks to them, I was able to meet different people, learn new things, visit many countries, and they were the main reason I was accepted into MIT.

Although in the last 7-8 years I have not participated in any competitions, I can still distinguish many of the qualities I have learned from them. They made me a better programmer, taught me to think creatively and quickly. The Olympiads in Informatics developed my competitive spirit and taught me to motivate myself to always look for improvement in me.

In 2012 you are the winner at CodeIT, and in 2020/2021 you are again part of the competition, this time as an IT guru. Tell us about your experiences as a competitor and then as a guru.

Being an IT guru was an amazing experience. I was always happy when I had the opportunity to go back and be able to help the competitors, because I too had received a lot of help when I was on the other side of things.

The President of Bulgaria attended the award ceremony, as in most years and this fact always distinguishes CodeIT.

What is your message to CodeIT competitors?

Continue to look for every challenge and participate in as many competitions as possible, especially in school years. Then, unfortunately the race time decreases, so you should take advantage as much as possible when it’s time for that.

You complete your bachelor’s and master’s degrees at the Massachusetts Institute of Technology (MIT). Together with prof. Dina Katabi you’re working on building an IoT system for a wireless sensor device. What inspired you to start working on such a project?

My goal was to work on an innovative project that is practical to become a community product. Professor Katabi’s group is working on wireless technologies and when I first appeared in the lab, it was in the initial steps on the project that became our company: Emerald Innovations.

The road was very difficult, and we had to solve many technical problems, as well as find the right business plan. After a few years at the university, we made sure that there was a business interest in what we do and for 3-4 years we have been working fully on our company.

You are part of the Forbes 30 under 30 list in the US for your work on remote health monitoring. How does it feel to prove yourself and be recognized in one of the most developed technological countries and what is the formula of success?

The formula of success is always focused on difficult problems. I knew that Professor Katabi’s group was one of those who worked the most hours at MIT and often spent late nights in the laboratory. This is what motivated me to work on this project and subsequently had its advantages and brought several awards.

What advice would you give to those who are just entering the tech world?

The technological world is a special field. Things change often, and people must adapt quickly. Success is often associated with spending many hours in front of a screen, so it is advisable to combine it with frequent hours without screens.

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In experiments with real-world data, the algorithm achieved an average accuracy of 87.2 with a 50% IOU threshold.

Because signals from WiFi networks are one-dimensional, most of the previous methods for detecting people using WiFi can only detect the center of a person’s mass and can usually only detect up to one person, Infoq wrote.

CMU’s technique incorporates amplitude and phase data from three WiFi signals captured by three different receivers. This produces a 3×3 feature map that can be transmitted to a neural network that creates UV maps of human body surfaces, which can locate multiple people as well as determine their pose.

The process begins by collecting five channel state information (CSI) samples, which represent the “ratio between the transmitted and received signal wave.” Each sample contains 30 frequencies and is taken from signals sent from each of the three transmitters to the three receivers; the result is two 150 x 3 x 3 raw data tensors, one for phase and one for amplitude. This is converted from a “modal broadcast network” to a tensor of a 1280 x 720 image. It is then processed as if it were an image captured by a camera using the state-of-the-art DensePose pose detection network.

The model is evaluated on a dataset of WiFi signals paired with video recordings of scenes containing one to five people. The scenes were recorded in offices and classrooms. Although there are no annotations on the videos to give a ground truth for the evaluation, the researchers applied pre-trained DensePose models to the videos to create a pseudo ground truth.

In a Hacker News discussion of the work, one user pointed out that in 2020, the IEEE announced the 802.11bf project for WLAN sensors, which is scheduled for release in 2024.

Although the CMU researchers have not published their code or model, the Papers with Code website links to GitHub repositories for three other similar projects.

The portable monitoring system and tests will be utilized by physicians, scientists, health professionals, faculty and staff as part of JHM’s commitment to health and well-being among its entire employee population. Ayub Khattak, Co-Founder and CEO of Cue said:

“Johns Hopkins Medicine is playing a leading and critical role in the fight against COVID-19, and we are honored to help support their team’s health and well-being. In settings like hospitals and medical research facilities, accuracy cannot be compromised and precision is paramount.”

In addition, JHM will have access to a Cue Health Enterprise Dashboard, which allows for test results to be shared through a secure, web-based internal application. This way organizations can manage population health and access timely data and analytics to enable administrators to swiftly identify trends and make informed decisions.

Cue’s test uses molecular nucleic acid amplification technology (NAAT) and provides lab-quality results directly to connected mobile devices in 20 minutes. The test is able to detect all known COVID-19 variants, including Omicron, and can be used on adults and children.

Cue also provides tests to Google, the National Basketball Association, and Major League Baseball, among other organizations.

“I would attribute the success to the quality and enormity of data.”

The Dubai Government knows AI cannot take off big sans Internet of Things (IoT) and big data, he adds.

The country is already deploying algorithms, data sharing and AI-integration in wide-ranging areas offering smart solutions and services in sectors like healthcare, education, transportation and public safety.

The Economist Intelligence Unit shared that 86% of banks and insurance companies would increase AI-related investment by 2025.

Smart Dubai Office has launched several strategies to harness AI and Blockchain. The goal is to improve government services and setting up an ‘experience lab’ run by a dedicated team that gathers citizen feedback to redesign and transform service delivery.

Drawing one’s attention to the United Nations warning that a comprehensive shift towards digitisation would require a new type of responsibility. The Telecommunications Regulatory Authority (TRA) Director General Hamad Obaid Al Mansoori says the private sector should also actively participate in the government’s efforts to give an ethical and humane dimension to digital transformation plans. He added:

“Profits should not be the sole driver or purpose.”

That’s the reason that is prompting Digital Dubai to shape global conversation around AI ethics, establishing Dubai as a thought leader in AI adoption across public and private sectors.

Sivaraman believes that continued conversation would prompt the community to eventually buy-in despite the fact Digital Dubai’s Ethical Tool Kit that supports industry, academia and individuals in understanding how AI systems can be used responsibly is not mandatory.

“Well-established science shows that air trapping can be measured with more than 90% accuracy using low-frequency sound. There is a clear difference in the acoustic resonance spectra of COPD patients versus healthy controls. Our goal is to flag abnormalities early, enable earlier treatment at home and empower patients to manage their own health.”

Sylvee is a product that’s worn at the lower part of the rib cage. It  promises to easily and continuously assess lung function without having to blow into anything. The wearable patch has embedded speakers and microphones that measure changes in acoustic resonance. The company claims that this is a good proxy for changes in lung air volume — which is the basis of pulmonary function testing.

Mercury NLP software is an out-of-the-box solution at half the cost per byte of the competitor products. While Mercury NLP users will find its built-in features suit all processing solutions, it can be customized for clients with specific data warehousing objectives. The new product will negate the need for manual data extraction from unstructured medical texts.

Mercury NLP software provides accurate, real-time extraction of text data around diagnoses, prescribed medications, tests, lab results, discharge plans and more. The technology can also be applied in the analysis of social determinants of health data to improve public health. Frank Manion, PhD, Vice President for Innovation at Melax Tech, said:

“We are confident Mercury NLP will foster important breakthroughs in medical research. NLP technology is a largely untapped tool, and we want to change this by showcasing the benefits that it can provide in healthcare and other biomedical domains, where as much as 80% of data is housed in unstructured text notes.”

The Melax Tech suite of NLP software includes a COVID-19 symptom extractor based on their flagship software, CLAMP.

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Python is the most popular network automation language right now. This module teaches you the fundamentals of Python, APIs (Application Programming Interfaces), JSON, and git as well. These are the core skills for programming and automation. The more you practice, the better you will git! For completion of this module, you will need 2 hours and 15 minutes.

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