Lawyers, product managers, engineers and software designers credit Cornell Tech with teaching them the skills they need to be successful in their industries. Including teamwork, strategy, and what it takes to launch a product or business.
David Hachuel and Akshay Jha, Technion-Cornell Dual Degrees in Health Tech and Connective Media ‘19 respectively, recently received the MIT Ideas^2 Prize at the MIT Grand Hack, part of the university’s Hacking Medicine Initiative.
Jha and Hachuel’s team won a spot in the 6-8 month incubator program at MIT for their AI algorithms that can characterize human stool samples based on visual input. This can help manage and prevent certain aspects of chronic digestive disorders like Irritable Bowel Syndrome (IBS) and Inflammatory Bowel Disease (IBD) that affect over 60 million Americans.
Hachuel and Jha’s technology has potential to scale beyond IBS and IBD given the product is purely software based. One application that shows promise is helping drug developers and researchers collect higher quality data that is less subjective to patient reports.
In the coming months, they will focus their efforts in perfecting the technology and polishing the business plan leveraging resources both from Cornell Tech and MIT.
Eugene Bagdasarayan is a PhD student advised by Deborah Estrin at Cornell Tech. Prior to Cornell Tech, he received an Engineer’s Degree in Computer Science and a Bachelor of Science in Automatic Control Systems and Information from Bauman Moscow State Technical University and then worked for Cisco.
What are you currently working on?
I am currently working on a project that is based on the intersection of Machine Learning and Systems. We investigate ways for users to keep their data private but still access data-intensive services or contribute to training Machine Learning Models. Today, users produce multiple digital traces that can be extremely sensitive to exposure, however, these traces could possess great value for future progress like early disease detection or building next-generation chatbots.
What excites you most about your current research?
My current research tries to address important problems of data privacy that is now recognized as a critical issue when we try to build new services. Answering these questions would enable new types of applications that are based on the personal data and still preserve the privacy of users’ data.
What were you doing prior to Cornell Tech in terms of your research focus?
I was working for Cisco Systems R&D, where we were developing a new cloud platform — OpenStack — and configuring it for Cisco hardware. However, I always wanted to be one step closer to invention and prototyping which requires more creativity and deeper understanding of the subject. Cornell Tech offers the unique balance between academia and industry where your research project might find its way into a product that has tangible near termas well as long term value.
What’s surprised you most about Cornell Tech?
People. I never met such a talented and diverse set of people in my life. Being among students, faculty and staff inspires me every day and I try to satisfy this really high bar.
How do you think Cornell Tech differs from traditional academia?
Luckily, I see all ingredients from academia — research seminars, working style and student life. However the important difference is the mix of different research areas (CS, IS, ORIE, ECE, Business) that produce amazing cross-field projects and many collaborations established with startups and industry.
Computer Science PhD student Alane Surh, advised by Assistant Professor of Computer Science Yoav Artzi, recently received an NSF Graduate Research Fellowship Program (GRFP) award. According to a release from the NSF, the “program recruits high-potential, early-career scientists and engineers and supports their graduate research training in science, technology, engineering and mathematics (STEM) fields.”
In 2002, Blascovich et al. published a paper, Immersive Virtual Environment Technology as a Methodological Tool for Social Psychology, outlining a vision where Virtual Reality (VR) can address several long-standing methodological problems in social psychology, such as: non-representative samples of participants and lack of replication [2].
However, more than 15 years later, when we conducted a review of experiments conducted in VR, most participants were drawn from the college population and tend to be very WEIRD (Western, Educated, Industrialized, Rich and Democratic). Neither could any of the VR studies be easily replicated, due to scattered software and hardware differences, as well constraint of physical lab spaces.
Conducting Experiments Online, and in VR
There is tremendous value in being able to run large scale experiments online quickly. A/B testing, probably one of the best well known form of online experimentation, has transformed the web as we know it. In social sciences,conducting crowdsourced behavior experiments online has also been accepted as an important method. Key advantages include: (1) quick access to a diverse pool of subjects; (2) low cost; (3) faster theory/experiment cycle [3].
At the same time, social scientists have long been excited about the potential in VR technology when it comes to running experiments.
VR Experiments + Crowdsourcing
There is an urgent need to bring VR experiments truly online — participants should be able to join from anywhere around the world.
As researchers at Cornell Tech (see full team list in the end), we asked ourselves:
Can we use crowdsourcing techniques to run VR experiments on the web?
Such a mental experiment raises more questions:
Can we reach enough people with VR devices in the wild?
Are their demographics more diverse than the previous VR study participants (in terms of age, gender, education level, income, etc.)?
What technologies are available to developers to deploy and run crowdsourced experiments?
Can we develop VR experiments that run remotely and independently without an experimenter present?
We are happy to report that after a year of work, we can answer the questions above. What we learned is in an upcoming paper, Web-Based VR Experiments Powered by the Crowd, to be presented next week at The Web Conference 2018 (WWW) in Lyon, France (pre-print is available through arXiv.org.
In short, my research team designed a new recruitment method and created a panel of 242 VR-eligible crowdworkers through Amazon Mechanical Turk. We showed that this population is more diverse than the average college population in key demographic categories, and replicated (some successfully) three classic studies in VR (more details below).
We open sourced (GitHub repos coming online soon!) the experiment data log, as well as software (all in JavaScript) for easy replication and adaption for future studies.
Some Finding Highlights
Here we provide a few highlights in our findings, including VR devices distribution, demographics, and a brief summary of one of the experiments we replicated. For more details, please refer to the paper itself.
The Type of VR Devices
We recruited 242 VR-eligible workers through Amazon Mechanical Turk during a period of 13 days. Below is a breakdown of the type VR devices owned by crowdworkers.
Breakdown of the type VR devices crowdworkers own (N=242)
Demographics of VR-eligible Panel
We also surveyed the panel for their demographic information. We show that this panel is more diverse compared to the typical college participant population in terms of age, educational level, residential area, and household income. For example, the panel reported ages ranging between 18–78 (median 32); education level from some college (30%), bachelor’s (30%), to advanced degrees. Majority (56%) reported income level between $30k — $80k (for reference, the median US household income in 2016 was $56k).
Demographics of VR-eligible panel
Replicating Milgram in VR Online
One of the studies we replicated in VR was the Milgram et al.’s study on the drawing power of crowds [1].
In 1969, Milgram et al. conducted a study on the streets of New York, showing that crowd can influence people’s behavior and draw people into it [1]. In the study, the researchers hired actors as the stimulus crowd to look up to the sky, and recorded the number of passers-by who followed the crowd’s gaze.
We replicated the study in VR, by giving the participant a random object finding task, while placing ten static avatars in the environment as the stimulus crowd, facing different directions in VR. In the background, we log each participant’s head orientation as an approximation of their gaze direction five times per second.
We launched the study to Amazon Mechanical Turk and the study opened for seven days. We received 56 valid and unique submissions in total, and paid $5 per submission.
What we found was quite interesting — when more avatars face the back, participants spent more time exploring areas in 360 that is outside their default field of view — i.e., being drawn to gaze the direction of the avatars.
Distribution of the proportion of time participant gaze falls into each zone under different conditions
More concretely, the experiment had four conditions, Zero, Low, Medium and High — each indicating the number of avatars facing to the back of the participant (to Zone 3). The graph above shows as conditions change from Zero to High, each participant’s gaze lie more outside of Zone 1, and explore more of Zone 3 — following the stimulus crowd’s gaze.
Such observation has important implications for avatar designs and social VR applications — and having the ability to run these studies fast and cheaply on VR can greatly speed up the design and research cycle for the nascent social VR space.
Final Words
Despite our success in running the first crowdsourced experiments in VR, challenges remain. For the three experiments we replicated, we were only able to reproduce the results of Milgram et al. [1] fully. The first experiment on the restorative effect of natural and urban environments was partially reproduced. And we failed to reproduce the result from the original Proteus effect paper [4] in our second experiment.
In addition, the experiments we ran (roughly 60 participants per experiment) were still limited in scale, and it is hard to replicate these studies without quickly exhausting the eligible participant pool.
However, with the launch of more affordable, stand-alone devices, such as Oculus Go, as well as improvements and price-cut from other companies, it is reasonable to expect that people with access to VR devices from their own home will continue to grow — hinting on a future of large-scale VR experimentation online. We hope our work has set a good foundation for achieving such vision. And remember, data and software isopen sourced for your easy replication and adaption.
References
[1] Milgram, S., Bickman, L., & Berkowitz, L. (1969). Note on the drawing power of crowds of different size. Journal of personality and social psychology, 13(2), 79.
[2] Blascovich, J., Loomis, J., Beall, A. C., Swinth, K. R., Hoyt, C. L., & Bailenson, J. N. (2002). Immersive virtual environment technology as a methodological tool for social psychology. Psychological Inquiry, 13(2), 103–124.
[3] Mason, W., & Suri, S. (2012). Conducting behavioral research on Amazon’s Mechanical Turk. Behavior research methods, 44(1), 1–23.
[4] Yee, N., & Bailenson, J. (2007). The Proteus effect: The effect of transformed self-representation on behavior. Human communication research, 33(3), 271–290.
The tech industry’s severe lack of gender, ethnic, and racial diversity has an effect on company culture, profitability, and diversity of thought. Women in Technology and Entrepreneurship in New York (WiTNY) is working to positively alter the statistics by increasing the number of women majoring in tech fields and pursuing tech careers.
Members of the WiTNY community recently gathered at Cornell Tech to hear from Program Director Judith Spitz, Deputy Mayor for Housing and Economic Development of New York Alicia Glen, and Winternship alumni as well as a panel of distinguished women in the tech community.
Kicking things off, Spitz explained why gender equity in tech is so important, mentioning that teams with better gender diversity perform better and have a higher return on investment. “If you care about revenue and profitability, you want to have more women in tech,” Spitz said. She added that there aren’t enough people working in tech to fill the jobs, that it can help women get into a higher income bracket, and that not enough women advance to leadership positions.
Glen discussed how this lack of female leaders impacts the New York City economy specifically and why it’s critical to have more diverse leaders in the field. “The pipeline is more than leaking. We are going backward in a lot of ways so we need to push as many buttons as possible to launch women ahead in the tech sector because now is the time to start fighting for parity and seniority,” said Glen. “When it comes to technology and thinking about the future of the economy in New York City it has to be about being female. The future is female,” she said, adding that we are an inflection point.
Following introductions from Spitz and Glen, the panel — moderated by Cornell Tech’s Executive-in-Residence Denise Young Smith, formerly Apple’s Chief Human Resources Officer and Vice President of Inclusion and Diversity — discussed actionable ways to capitalize on the inflection point and create a more inclusive tech community. The panelists included Verizon’s Chief Network Engineering Officer and Head of Wireless Network Nicola Palmer, Accenture’s Senior Global Inclusion and Diversity Managing Director Nellie Borrero, and CUNY’s Professor and Dean Gilda Barabino.
From left to right: Denise Young Smith, Gilda Barabino, Nellie Borrero, Nicola Palmer.
Here were some of the key takeaways from the panel conversation:
Practice inclusive leadership:
Inclusive leaders are authentic, empathetic, transparent, and focused on relationship building, according to Smith. Inclusive leaders create a culture where collaboration, acknowledging diverse opinions, and avoiding favoritism are valued and rewarded. Although leaders help to set the values and expectations for the team, people at all levels must contribute by adopting the same values.
Palmer learned what makes someone an inclusive leader firsthand when she worked with a manager who fit the definition. When Palmer was out of the office for months with a significant health issue, her manager took over her role until she came back but still called her each week to ask her opinion and keep her informed.
“There was nothing he needed my advice on because he had done the job,” Palmer said. “But that man called me about once a week,” she said. “The reason he called was to keep me engaged and to keep my spirits up when I was feeling down,” she said, “It was a lasting lesson for me about being inclusive and caring about people and keeping that connection because, in the end, that’s what it’s about.” Now she incorporates those tenets into her own leadership style.
Build a supportive community and empower one another:
Foster inclusive leadership in your community so that you can all learn from one another and grow together. Barabino learned this from her experience as the first African American female to serve as engineering dean in the United States at a school that is not a historically black college. When she joined, people lined up outside her office every day to find out how she got where she was in a homogenous field. People talked about feeling isolated as the “only one” — for example, one of the few women or people of color in their class. Barbino started a group so the women would have a supportive community and a space to share their experiences and identify solutions to the inherent difficulties of being a minority in a male-dominated field.
One of WiTNY’s goals is to build a strong community of women in tech.
Develop the courage to challenge the status quo:
Many workplaces have an inherent “boys club” culture like the ones the women experienced at Barbino’s school. When asked how to survive and thrive in that type of culture, Borrero said that female leaders who need to survive and thrive in a white-male-dominated culture have to tell their story, be courageous, and ask for what they want, both in their careers and from their workplaces.
As she became a leader herself, she had the leverage to “challenge the status quo” and point out the lack of diversity during the hiring process. But she explained that people at all seniority levels can encourage change by finding advocates and sponsors who care about creating a change in the organization.
Humans draw on a multitude of impulse reactions while navigating surroundings. These signals, gestures, and movements — made without thinking — help people interact smoothly with one another; they prevent people from bumping into one another, for example. But what happens when humans and machines interact? Can humans automate impulse reactions in robots?
This question fascinated Dr. Wendy Ju, who joined the Jacobs Technion-Cornell Institute at Cornell Tech as Assistant Professor of Information Science last year. Ju is setting up a robotics research lab for human-and-robot interaction, where she will seek how to design machines that can easily and naturally interact with humans.
Watching what humans do
Dr. Ju has a PhD in mechanical engineering from Stanford and a master’s degree in media arts and sciences from MIT. She has spent years observing human interactions. “They’re basically very small conversations that enable everyday life: Who’s going to open the door? Who’s going to go in first or second? With cars we do it at four-way stops,” she said.
Watching what happens when things go wrong during these interactions can also be useful, she said. “I’m just a person that really likes to watch people. I really love looking at breakdowns, I like being in public places and seeing when these things get tripped up.”
Ju explained that machines do not automatically pick up cues that people use every day; rather, everything they do requires button pushing or explicit asking. Humans are constantly signaling to one another, so when a robot is added to the mix, how is it given the skills it needs to interact?
“I’m interested in that kind of interaction, knowing that is how people interact with one another, and thinking about what that means for how we design machines.”
According to Ju, these interactions are not always completely obvious to the people making robots because they work so invisibly that it’s not often noticed “I feel like I have an obligation, since I can see these things, to design the machines so that they work that way as well,” she said.
On the road with ghost drivers
One of Ju’s principal areas of research is autonomous cars. She’s carried out field experiments to see how people behave around them. To gauge these reactions, Ju and her team use what she calls “ghost drivers.” In light of a recent accident in Tempe, Arizona, where a woman was killed by an autonomous Uber car undergoing testing, Ju’s methods have particular significance. “We basically have a person dressed in a costume to look like a car seat driving on the road, and then we can do experiments to see how people react, but with the safety of an actual human controlling the car,” she said.
Through her work, Ju aims to answer specific questions about set scenarios. For example, how quickly will people react if a car hands control over to its passenger? What will people do when they encounter an autonomous car on the road? The results could be surprising. People tend to understand that autonomous cars and robots are learning, Ju said, and they often want to help. “People do different things to enforce norms about where the car’s supposed to be and when it’s supposed to stop,” she said.
The car seat costume used in Ju’s ghost driver experiment.
Ju’s other work on robot-and-human interactions is focused on everyday situations. The machines she deploys are not actually autonomous, they’re controlled by people. The point is to try to anticipate how people might behave around robots in the future. How will they react to a robot collecting trash, cooking food, or running on the sidewalk?
Some people test the robots to see what they are capable of, while others try to help them. “If the robot plays dumb, if it doesn’t pick up a signal, people will do different things to really exaggerate what they’re doing, like wave the garbage or point at empty spaces,” Ju said. These, she said, are implicit cues which people amplify to teach the robot the correct way to do something.
By observing all of the different cues and behaviors, Ju can then incorporate them into machine-learning algorithms. This way, robots can learn from the natural things that humans do.
A new context in NYC
To date, Ju has carried out most of her experiments around Stanford. She has found that people there are pretty nonchalant when they encounter robots. “A lot of people are very pro-technology and they also work in technology so they’re very much like, ‘Oh yeah, this is happening now,’” she said.
Having recently moved to New York City, she is curious to find out whether people will behave differently or the same way. One of her first projects at Cornell Tech will explore how people interact with a troupe of chair robots -— essentially chairs that can reconfigure themselves in a space. She will also carry out further on-road experiments with ghost drivers.
Ju relishes the opportunity to continue her work in this new context. The diverse department at the Jacobs Technion-Cornell Institute also really appealed to her. “There are so many people with shared interests in both technology and the social issues around that,” she said. The city played its part too, “New York City was a big draw because I’m so interested in observing people,” she said. “I’m working at the intersection of technology and design; New York City’s such a great place for that.”
For the first time, the Annual Cornell University High School Programming Contest teamed up with Cornell Tech to host simultaneous events on each campus.
The contest, the brain child of CIS faculty member Robbert Van Renesse, aims to encourage high school students interested in computer science and programming.
Teams of two to three students had three hours to solve as many of the 12 problems provided as possible. For each correct solution, a team received a color coded balloon.
On the Cornell Tech campus there were 38 teams representing 15 high schools from four boroughs, Long Island and New Jersey.
Awards for gold, silver, and bronze were awarded to the teams in each location who solved the most problems, as well as a trophy for the overall winner across both campuses.
The team from Princeton High School took home the overall award, solving 12 out of 12 problems. Teams from Trinity HS and Stuyvesant High School took home the NYC silver and gold, respectively.
The problem set was created by Daniel Fleischman, ORIE PhD ’15, who has helped run the competition with Van Renesse since its inception. Fleischman himself was an enthusiastic programming contestant as an undergrad and flew in to support the Cornell Tech event this year. His insider knowledge and joy played a huge role in the day’s success.
“It was really exciting to see this community of young coders come together to compete with so much talent and enthusiasm,” Sr. Director of K-12 Education at Cornell Tech, and the organizer of the New York City event, Diane Levitt said. “This is a perfect example of Cornell impact: when our campuses collaborate, the sum of the parts is greater than the whole.
In a recent essay to be published in a forthcoming edition of Georgetown Law Review titled “The Platform is the Message,” Professor of Law James Grimmelmann dissects recent internet phenomena like the Tide Pod Challenge and Fake News. Grimmelmann explores what these trends can teach us about the spread and mutation of ideas, the role platforms like Facebook and Youtube play in their moderation, and why moderation of these things is incredibly difficult.
Grimmelmann writes:
Facebook and YouTube have promised to take down Tide Pod Challenge videos. Easier said than done. For one thing, on the Internet, the line between advocacy and parody is undefined. Every meme, gif, and video is a bit of both. For another, these platforms are structurally at war with themselves. The same characteristics that make outrageous and offensive content unacceptable are what make it go viral in the first place.
The arc of the Tide Pod Challenge from The Onion to Not The Onion is a microcosm of our modern mediascape. It illustrates how ideas spread and mutate, how they take over platforms and jump between them, and how they resist attempts to stamp them out. It shows why responsible content moderation is necessary, and why responsible content moderation is impossibly hard. And it opens a window on the disturbing demand-driven dynamics of the Internet today, where any desire no matter how perverse or inarticulate can be catered to by the invisible hand of an algorithmic media ecosystem that has no conscious idea what it is doing. Tide Pods are just the tip of the iceberg.
In the Runway Startup Postdoc Program, we select PhD grads that wish to start a company by harnessing their deep tech expertise. These brilliant people need to go through a paradigm shift- from an academic mindset to an entrepreneurial outlook. It’s a shift that requires education and practice, but it’s absolutely necessary for their success.
Entrepreneurial mindset from day 1
This is why we begin our program with a unique learning experience: a 5 day intensive workshop on how to discover the most valuable market opportunities for their innovation. This hands-on workshop presents a visual business tool- the Market Opportunity Navigator– to help postdocs in overviewing their potential markets, developing an open mindset that avoids locking in, and eventually setting a smart strategic focus.
The framework consists of 3 steps that are necessary for that matter: (1) how to identify different applications and target customers stemming from the core abilities of the startup; (2) how to evaluate different market opportunities to reveal the most attractive option; and (3) how to create a strategic plan that focuses on the most promising path but keeps you open minded and agile. Each of these steps is accompanied by a dedicated worksheet that lays out a structured process in a simple manner.
During the workshop, postdocs apply the Market Opportunity Navigator on their own business idea, and go through one full cycle of the process. Fernando Gomez-Baquero, director of Runway and Spinouts, says that this is an excellent opportunity for the postdocs to take a step back from their initial idea and open up to different directions that might be more promising: “participants often come with a specific product and market in mind, but these are unproven. This workshop helps them to define their unique abilities, understand what else may be in store for them, and learn how to validate these options. It clearly lays out all the questions that entrepreneurs must deal with before setting their strategy. It’s the students’ role to find the answers, but we are now confident that they have the right tools to do so”.
Combining planning and experimentation
The wide perspective that this workshop provides is essential before moving to the next step- validating a specific market opportunity through intensive customer interviews and minimum viable products. This is where the NSF I-Corps program comes in, and adds a great boost to the entrepreneurial shift of our postdocs.
Our entrepreneurs come more mature to this program, as they have already screened different strategic options and set their strategic boundaries to engage in more meaningful lean cycles of experimentation. Furthermore, if a business model turns out to be rejected, they can pivot more easily and more distantly.
Ardalan Khosrowpour, Runway postdoc, CEO of OnSiteIQ, and former I-Corps awardee stresses the complementing nature of these two approaches: “The Market Opportunity Navigator helped OnSiteIQ exit a local optimum market opportunity…It helped us take a step back from our laser-focused customer discovery and revisit our decision regarding the customer segments and the product-market fit before moving forward. I believe this is an excellent, crucial, and complementary method to Lean Startup by Steve Blank that should be implemented by all startups and especially for university spinoffs where the market opportunity is less clear than the core enabling technology.”
Education is an ongoing process
Even after our postdocs go through these excellent training programs, we keep holding their hand as they perform the early steps of their entrepreneurial journey. We urge them to use their toolkit and apply these business tools overtime, to reflect on their learning. The systematic approach enables them not only to make smarter strategic choices, but also to discuss and debate with their team, mentors, and stakeholders. After all, structured means are vital in the chaotic process of bringing innovation to the market.
