Every year, as winter approaches, the United States gets ready for a potential epidemic. This year, the country is preparing to handle two.

Influenza, or the seasonal flu, kills between 12,000 and 61,000 people in the U.S. annually, according to the Centers for Disease Control and Prevention. The current COVID-19 pandemic has already been responsible for more than 200,000 deaths in the U.S. this year.

Both viruses attack the respiratory system and can have similar symptoms. For researchers trying to track these viruses and predict their spread, untangling them will be a challenge.

“Something like this is completely unprecedented,” says Alessandro Vespignani, Sternberg Family Distinguished University Professor of physics, computer science, and health sciences, and director of Northeastern’s Network Science Institute. “Having a major pandemic and then trying to get insight on the seasonal flu—it’s a completely new game.”

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Physics Professor Louise Skinnari and her lab were recently awarded a multi-year grant from the United States Department of Energy. We caught up with her to discuss her experience at CERN, the transformative affect of funding on research, and her time at Northeastern.

You have just received a DOE grant awarded in the field of “high energy physics” can you explain to readers what this means?

“The field of “high energy physics” tries to understand how our universe works on the smallest and largest scales. We study the most fundamental building blocks of nature, tiny sub-atomic particles, and how they interact. It is called “high energy” physics because, at the single particle level, it involves very high energies. We use particle accelerators to produce these energies. At CERN, the Large Hadron Collider (LHC) accelerates protons (primarily) in a 17-mile ring and collides them head on at very very high (to the individual particles) energies.”

This grant is awarded over a five-year period. What do you plan on doing with it primarily?

“This grant enables me to carry out an extensive research program, together with a team of student and postdoctoral researchers! Specifically, this research program is centered around studying the heaviest of all known elementary particles – the top quark and the Higgs boson – using the Compact Muon Solenoid (CMS) experiment at CERN. The goal is to advance our understanding of how fundamental particles behave at high energies. In parallel, my research team will develop very fast (~µs) identification of electrically charged particles that traverse the CMS detector. This is key to improve how the CMS experiment selects in real-time which collisions to read out and save for later physics.”

Please briefly explain your work, and what role you play at CERN with the LHC and CMS

“I am a member of the CMS collaboration, which has about 4000 physicists, engineers, technicians, and students from all around the world working together. That may seem like a lot, but the experiment both involves a highly complex detector (the CMS detector is 50×70 feet large and weighs about 14000 tons!) and is used to study countless different physics processes and phenomena. CMS is one of four main experiments recording and analyzing the LHC collisions. My work recently has focused on physics involving top quarks, and upgrading the CMS “trigger system” that is responsible for deciding which collision events to store (only a small fraction of the LHC collisions are kept for later analysis).”

Can you discuss how Covid-19 has affected your researching? Is remote work possible, or even needed at the LHC?

“I have been in a highly fortunate position of being able to maintain my research despite the pandemic. The biggest change is that I, like most people, have been working from home for the past months. Since the CMS members are spread out at research institutes and universities around the world, we were already before the pandemic well-adapted to remote work. The collision data are accessible from anywhere, and research meetings always have a video conferencing option. The LHC was not in operation this year but instead planned maintenance and upgrade work was taking place. So some of my collaborators were more affected when this work had to be paused. One challenge has been that my immediate research group is spread out over three continents, so sometimes finding a time zone for meetings is difficult!”

What “big questions” are left to solve in physics? How might the solutions to these questions impact peoples’ lives?

“There are many big questions left to solve in high energy physics: What makes up “dark matter” (which is a large fraction of all matter in the universe)? Why do we not observe any antimatter in the universe? Are there more than three dimensions? Etc. Answers to these questions will per se not directly impact people’s everyday life, however, research at a place like CERN indirectly has important benefits. High energy physics research has e.g. led to proton therapy for cancer treatments, technologies used in PET scans came originally from particle detectors, the World Wide Web was developed by particle physicists. Etc.”

Considering these bigger harder questions, what role does the planned HL- LHC have in answering them?

“The High-Luminosity LHC (HL-LHC) will increase the intensity of the collisions, which in turn will result in an order of magnitude larger datasets compared to the “original” LHC. This lets us probe very rare physics processes. New detector technologies that are developed for HL-LHC can also enable entirely new physics studies, for e.g. certain type of long-lived particles that could be associated with dark matter.”

Working at CERN could be considered a pinnacle for a physicist. What goals do you have for the future?

“CERN really is a unique place to work and do research. I am excited about the years ahead – we have only analyzed a fraction of the expected data, and currently we are midst developing the detector systems that will be installed for the HL-LHC in ~2025. We have many years ahead of exciting physics research with the LHC.”

How much overlap does your role at Northeastern have with your role at CERN? How did you end up at Northeastern?

“There is complete overlap. The research that I do, which is an important part of my role at Northeastern, is carried out at CERN with the CMS experiment. Some of this research takes place physically at Northeastern (some detector development, data analysis, …), but it is fully connected to CERN.

I ended up at Northeastern rather randomly. Northeastern was hiring in my field of research when I was applying for faculty jobs, and it ended up being a great fit! Northeastern has a strong research group working on the CMS experiment – we are four faculty along with postdoctoral researchers and PhD/masters/undergraduate students!”

As part of your Northeastern role, you’re surrounded by the next generation of physicists. What kind of work do you think they will be doing?

“This is a great, and difficult, question! I think one clear theme is that both for academic research and in industry, more and more work is computational in some form. Using programming techniques, advanced machine learning, quantum computing, … I am sure will be an integral part of the work of the next generation physicists.”

What interests you about physics?

My interest in physics stems from a deep fascination with the universe – what is out there? How does it work? What is it made of? These are the type of fundamental questions that still excite me about my research.

The National Science Foundation (NSF) has announced a five-year grant to support a Physics Frontiers Center (PFC) headquartered at Rice University. This effort will include opening a satellite location this Fall at Northeastern under the direction of University Distinguished Professor of Physics and Bioengineering, Dr. Herbert Levine.

The Center for Theoretical Biological Physics (CTBP) was founded in 2002 at the University of California-San Diego and moved to Rice in 2011 when biophysicists Herbert Levine, José Onuchic and Peter Wolynes were recruited to join the faculty. Levine, a founding co-director of the Center, came to Northeastern in 2019 and facilitated the partnership to expand its reach to the Boston area. Baylor College of Medicine and the University of Houston round out this dynamic nationwide collaboration of scientists.

“The full integration of research across all of our locations has been critical to our success,” says Levine. “Formally expanding the program here at Northeastern, in the heart of the medical and scientific hub of Boston, brings even greater resources, talent and skills to our endeavors.

The research, focusing on the fundamental science needed to understand biological systems, will encompass a host of projects, including computational studies of the structure of the genome and how that structure couples to physiology through its effects on gene expression; dynamical systems of interacting molecules that enable biological systems to sense their surroundings and adjust their behavior accordingly; and the properties of non-equilibrium physical structures that make up biological cells (e.g. the mechanical properties of the cell’s cytoskeleton and its role in organizing cell structure and dynamics).

“In addition to the research, the Center creates an environment for broadly-focused training of graduate students and postdoctoral researchers, providing a framework for them to become leaders of the field in future years,” says Mark Williams, Chair of the Department of Physics at Northeastern. “This is a major accomplishment for our University.”

NSF’s Physics Frontiers Centers program supports the collective efforts of large group of researchers, enabling transformational advances in the most promising research areas. PFCs also include creative, substantive activities aimed at enhancing education, broadening participation of traditionally underrepresented groups, and outreach to the scientific community and general public.

“The Physics Frontiers Centers program enables major advances at the frontiers of physics,” said Jean Cottam Allen, NSF program officer who oversees the agency’s PFCs. “Researchers at the Center for Theoretical Biological Physics conduct innovative and forefront work at the intersection of physics and biology.”

One of only 10 such centers in the United States, the CTBP mission will continue to be devoted to the sophisticated analysis, computation, and quantitative experimentation needed for understanding the living world. The $12.9M grant will allow the center to continue to pursue its critical research, training and outreach efforts over the next 5 years. This is the third time the center has been awarded a renewal and makes them the longest running PFC in the nation.

Alumna Delia Mocanu is a double husky and 2014 PhD recipient in Physics. During her time at Northeastern, she developed a passion for network science, working on data projects with incredible scale. Now at Facebook, she finds herself working on one of the largest data systems in history— News Feed.

She participated in a written engagement with the Northeastern COS on going industry, why epidemiology works better in the dark, and the most important skill to succeed in data science.

Growing up, did you find that you were interested in physics? Or did that interest develop later in life?

I grew up in Romania and I did not like Physics much at the time because it was too formulaic. In a weird twist of events, as a freshman in college here in the US, I actually switched from Chemical Engineering to Physics/Math double major.. 

At some point I realized that Physics made a lot of sense for me and I just enjoyed pure science more than engineering. I liked the rush of solving problems from scratch.

Why Northeastern?

I jumped around a bit until I landed on what I wanted to do. I was originally curious about Astroparticle Physics and I wanted to know everything about how the universe worked. During my first year at NEU, it became clear that I was seeking something more fast-paced. [The irony is not lost on me, this was very antithetical to why I switched from Engineering to Physics four years earlier.]

At Northeastern, seeing the kind of work Barabasi and Vespignani were doing, I immediately recognized that this interdisciplinary field (Network Science/Complex Systems) was more aligned to my existing interests and personal values. 

Is there anything that stands out about your graduate/Phd experience?

My advisor really emphasized the idea of ownership, and I liked that we were held to very high standards. Looking back at it now, I always felt like what I was putting my time in truly mattered. Prof. Vespignani was very good at instilling energy to the group. 

Did your experience working in Professor Vespignani’s MOBS Lab and other research facilities shape your career decisions?

Absolutely. What I cherish about this PhD experience is that we felt very plugged in; we had well funded projects that were designed to solve real problems, in real time. 

We loved doing something that mattered. I was simultaneously learning something and solving a problem involving millions of people. Little did I know I was going to reach billions later.

You’re currently working at Facebook as a Data Scientist. What does your current role entail?

I work in News Feed, and I’ve been here since I started at Facebook. What makes this role especially stimulating is building solutions that work at scale. I still very much rely on the thought processes and models of the world that I adopted during my PhD. Right now, I couldn’t imagine a better place to apply these. 

However, my favorite part of my job is actually identifying opportunities. When I find something worth investing in, I put all my energy into making it a reality. That last part is the most rewarding and it is really more about general problem solving than it is about any specific math/engineering skill. 

Have you spoken to friends or colleagues about Professor Vespignani’s COVID-19 models and what they are trying to accomplish? Has it been a source of pride, frustration, or a little of both?

To my friends mostly, yes. I touched epidemiology models a bit during grad school. At the time I remember thinking ‘I hope this software makes a difference someday,’ but I never thought we’d see something like this. Healthy skepticism is good, but I’m quite surprised to see the amount of pushback against these predictions at large, so I would say this has caused a bit of frustration. 

Frankly, epidemiology is best when you don’t know that it exists and when the predictions don’t come true. Otherwise, it is not too dissimilar from weather forecasting; every modeling exercise comes with error bars, but one can tell the difference between a major hurricane and a light summer rain. However, in epidemiology you ‘can’ actually turn the would-be hurricane into a light summer rain. Taking action invalidates the original prediction, that’s really the goal. Whereas if your predictions come true, you have failed; that’s the curse of this field. 

Computational epidemiology has advanced so much in the past two decades, that it’s quite challenging to establish a common language even with other highly technical folks.

What do you find most rewarding about data science?

It’s the most rewarding job you can possibly imagine. It’s always changing and you are constantly learning new things or building new tools so that you can iterate faster. 

It’s not just about the act of doing the analysis, but more about where the data fits. A lot of data science is problem solving, which is what I liked about Physics in the first place. You don’t have a solution and no one has ever solved this problem before. There are no instructions and every single day feels like a journey. That dynamic aspect  is very important to me.

What was the most important thing you learned at Northeastern?

Professor Vespignani wanted nothing short of perfection. He would sometimes ask you to iterate on the same chart a dozen times before it felt right. It’s about communicating this data in the best way possible. If I have to repeat the same steps several times before I get it right, then I do it, and I think it’s worth it. As a result, I do notice when others take shortcuts.

I can’t stress this enough: the analysis is not an end in itself.

Is there advice you would give to students who are interested in this field or the type of work you’re doing now?

Don’t be afraid of change, your interests will continue to evolve over time. Look at your PhD program as a time in your life to discover what you like doing and work with your advisor through that process, as they should guide you in making the most out of your career. 

Your goal in academia is to publish papers and advance knowledge, while you may not necessarily implement them right away, and that’s ok. If you choose the industry path, your focus will be on the application itself. The optimal mathematical solution may need a 20-fold simplification so that you can enable the rest of the team to be part of it. 

Anything else you’d like to add?

I do want to acknowledge the fact that Northeastern did an incredible job bringing professors from other universities and building great research programs, and not just in network science.

It’s incredible. I do think that I was very lucky to be part of Northeastern because that sort of environment so focused on research is very, very important. I really loved it.