Category Archives: Computer Science
Lynn Conway, Computing Pioneer and Transgender Advocate, Dies at 86 – The New York Times
Lynn Conway, a pioneering computer scientist who was fired by IBM in the 1960s after telling managers that she was transgender, despite her significant technological innovations and who received a rare formal apology from the company 52 years later died on June 9 in Jackson, Mich. She was 86.
Her husband, Charles Rogers, said she died in a hospital from complications of two recent heart attacks.
In 1968, after leaving IBM, Ms. Conway was among the earliest Americans to undergo transition surgery. But she kept it a secret, living in what she called stealth mode for 31 years out of fear of career reprisals and concern for her physical safety. She rebuilt her career from scratch, eventually landing at the fabled Xerox PARC laboratory, where she again made important contributions in her field. After she publicly disclosed her transition in 1999, she became a prominent transgender activist.
IBM offered its apology to her in 2020, in a ceremony that 1,200 employees watched virtually.
Ms. Conway was probably our very first employee to come out, Diane Gherson, then an IBM vice president, told the gathering. And for that, we deeply regret what you went through and know I speak for all of us.
Ms. Conways innovations in her field were not always recognized, both because of her hidden past at IBM and because designing the guts of a computer is unsung work. But her contributions paved the way for personal computers and cellphones and bolstered national defense.
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Lynn Conway, Computing Pioneer and Transgender Advocate, Dies at 86 - The New York Times
‘I always had the energy to push toward perfection’: Jing Wang shares his secret to academic success – Faculty of Arts & Science
For Jing Wang, chasing perfection is a hobby and one hes very good at. Today, Wang graduates as a member of University College with a specialist in computer science (with focuses in artificial intelligence and theory computation) and a major in mathematics.
Over the course of his degree program, Wang obtained a cumulative grade point average of 4.0, as well as a mark of 100 per cent in 18 of his courses. He also won a staggering 15 major scholarships, and one of three Governor General's Silver Medals bestowed on the most academically outstanding graduating students. Now, hes looking forward to a brilliant new career as a software engineer.
Many students struggle with mathematics, a subject in which youve succeeded brilliantly. To what do you attribute your success?
The most important thing is that I really enjoyed my courses! I think that a love of math played a very important role in my success because it takes a lot of effort. Many of my courses were quite intellectually challenging and sometimes the workload was very high, but I just liked them so much. I always had the energy to push forward to perfection.
Math can be challenging. You need to be able to understand and write proofs. This requires logic and a clear understanding of each definition so that you can prove your argument. Professors spend a long time just teaching students how to write proofs, and when they pay close attention they do very well. Thats pretty much the core ability you need to achieve a high mark in any math course. Once you know how to work with logic, you can pretty much learn anything if you put time into it.
Math has so many applications, computer science being one of them. Was that a subject that always interested you?
I was fascinated by computers when I was young, even when I didnt know how they worked. But as soon as I started to learn programming, I realized I had the potential to build the same kind of thing myself. So that was fascinating, and it was the first program I considered pursuing at the University of Toronto. Everything is digitalized now; everything we do depends on computer systems in one way or another. So I knew that by studying computer science I would get key skills I needed to find a job or start my own company.
In computer science its harder to get a perfect score than it is in math; coding is less obvious than writing proofs and you need to think about how to explain your ideas clearly. You can certainly do well, but its harder to be perfect.
Youre very interested in the theoretical side of computers. What are some new developments in that field that interest you?
Right now were seeing the rise of large language models, the most prominent example being ChatGPT. Thats had a huge benefit in our lives and I think well soon see more development in that area. There are still many fascinating open questions in theoretical computer science, most famously the P vs NP problem the idea that every problem whose solution can be quickly verified can be quickly solved. Someday, I hope well see a solution to that one.
I understand that your studies included a one-year internship. Can you tell me about that?
I did a software engineering internship after my second year as part of a program called the Professional Experience Year Co-op (PEY). I worked at Veeva Systems, which provides software for the life sciences industry. They said theyd like to welcome me back, so Im very happy about that. It was my first experience in a professional setting: I was able to see how the knowledge I learned in class could be applied to real world problems. I also developed some key skills like teamwork, since writing software always involves teamwork. Overall it was a very meaningful experience for me when I returned to the classwork after one year I felt so much more prepared.
What does the future hold for you?
Right now my plan is to return to Veeva Systems as a full-time software engineer. I really like the company and its values. Thats the short term. In the longer term I think maybe someday Ill return to university. Ill continue to develop my career in the software industry, and eventually work in a leadership position in that field.
Any final words before graduation?
Im really thankful to the university because this long journey has been so meaningful. My professors were so nice and so knowledgeable, and I can really say they were role models for me. Often when I submitted final exams, I didnt want to say goodbye to a lot of the courses because I liked them and remembered so many things about them. I was very happy learning here; I think Ive improved so much in math and computer science, but also in the general area of learning and critical thinking.
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Computer science students must be taught to consider social effects – Times Higher Education
In many ways, there has never been abetter time tolead acollege ofcomputer science. AtNortheastern Universitys Khoury College ofComputer Sciences, where Ihave been dean since 2022, our student body has tripled inthe past decade and enrolments are still soaring, while the gender gap isshrinking. We see great enthusiasm for careers inthis dynamic, challenging field.
But computer science is at acrossroads. Acursory review ofdaily news headlines reveals ongoing angst about the role ofAI infair decision-making, automation and job loss. And many ofthe best practices inour field, such as sharing open-source software and creating large-scale platforms for sharing information and news, have also enabled unintended, unfortunate outcomes.
For example, dubious actors have been enabled to piece together code and algorithms for face recognition. Coupled with the ability to scrape large amounts of data from social media platforms, these actors have sold extensive face-recognition systems to law enforcement agencies. While these systems can help identify and rescue abducted children, we now have databases filled with social media images of non-consenting childrens faces.
Such unforeseen outcomes raise questions that cut to the heart of our mission as computer science educators. Is an abundance of computer science graduates good for higher education and, more importantly, the world? Are our students pursuing high-income jobs regardless of the impact of their work? How do we adjust our curriculum to incorporate the effects of computer science in society? How do we encourage our graduates to build ethical and trustworthy computing systems?
I believe the field of computer science needs a fundamental course correction. We can no longer be singularly tied to our mathematical and engineering foundations, focused only on what can be built. We must also ask what should be built, and who needs to be part of that design and implementation process. These questions demand that computer science education and research broaden their community, not diminishit.
At Northeastern, the vast majority of our students study core programmes in computer science, data science and cybersecurity in tandem with diverse fields such as business, biology, philosophy and law, through our combined majors. And over athird of our faculty have joint appointments with other departments, including philosophy, journalism, law, psychology, health sciences, and mechanical and electrical engineering.
An interdisciplinary education will help to ensure that our graduates get beyond the move fast and break things concept that has often driven the tech industry over the past two decades and step up to the challenge of designing AIsystems that rise above our human biases, creating life-enhancing advancements that benefit as many people as possible.
We also need to consider who is entering computer science programmes in the first place. While wehave taken strides be more diverse, weare still seeing a deficit in under-represented populations, including women, people of colour and those who face cultural barriers to high school computer science opportunities. At Northeastern, we created a bridge masters computer science programme, called Align, for students with no formal tech background looking to pivot to a high-tech career. Some of these students come straight from undergraduate programmes, where many students are shut out of computer science programmes because of overwhelming demand. Others look to complement their current careers in healthcare, finance and law. More than half of the students who take advantage of this second chance opportunity are women.
Many programmes across the US are also grappling with how to integrate ethics. AtNortheastern, our approach recognises that stand-alone courses donot help students to understand technical trade-offs and methods for developing ethically informed systems, so we strive to integrate ethics across the curriculum, starting at matriculation with our Oath for Computing.
Modelled on the Hippocratic oath, this statement which all of our students recite and adopt recognises that with computing knowledge comes a great responsibility to serve society. We weave the tenets of this oath into our curriculum and position it as a North Star for all students.
As we enter the new era of transformative advancements inAI, wecannot afford to ignore this great responsibility. The stakes are simply toohigh.
Beth Mynatt is dean of Northeastern Universitys Khoury College of Computer Sciences.
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Computer science students must be taught to consider social effects - Times Higher Education
Researchers leverage shadows to model 3D scenes, including objects blocked from view – MIT News
Imagine driving through a tunnel in an autonomous vehicle, but unbeknownst to you, a crash has stopped traffic up ahead. Normally, youd need to rely on the car in front of you to know you should start braking. But what if your vehicle could see around the car ahead and apply the brakes even sooner?
Researchers from MIT and Meta have developed a computer vision technique that could someday enable an autonomous vehicle to do just that.
They have introduced a method that creates physically accurate, 3D models of an entire scene, including areas blocked from view, using images from a single camera position. Their technique uses shadows to determine what lies in obstructed portions of the scene.
They call their approach PlatoNeRF, based on Platos allegory of the cave, a passage from the Greek philosophers Republicin which prisoners chained in a cave discern the reality of the outside world based on shadows cast on the cave wall.
By combining lidar (light detection and ranging) technology with machine learning, PlatoNeRF can generate more accurate reconstructions of 3D geometry than some existing AI techniques. Additionally, PlatoNeRF is better at smoothly reconstructing scenes where shadows are hard to see, such as those with high ambient light or dark backgrounds.
In addition to improving the safety of autonomous vehicles, PlatoNeRF could make AR/VR headsets more efficient by enabling a user to model the geometry of a room without the need to walk around taking measurements. It could also help warehouse robots find items in cluttered environments faster.
Our key idea was taking these two things that have been done in different disciplines before and pulling them together multibounce lidar and machine learning. It turns out that when you bring these two together, that is when you find a lot of new opportunities to explore and get the best of both worlds, says Tzofi Klinghoffer, an MIT graduate student in media arts and sciences, research assistant in the Camera Culture Group of the MIT Media Lab, and lead author of a paper on PlatoNeRF.
Klinghoffer wrote the paper with his advisor, Ramesh Raskar, associate professor of media arts and sciences and leader of the Camera Culture Group at MIT; senior author Rakesh Ranjan, a director of AI research at Meta Reality Labs; as well as Siddharth Somasundaram, a research assistant in the Camera Culture Group, and Xiaoyu Xiang, Yuchen Fan, and Christian Richardt at Meta. The research will be presented at the Conference on Computer Vision and Pattern Recognition.
Shedding light on the problem
Reconstructing a full 3D scene from one camera viewpoint is a complex problem.
Some machine-learning approaches employ generative AI models that try to guess what lies in the occluded regions, but these models can hallucinate objects that arent really there. Other approaches attempt to infer the shapes of hidden objects using shadows in a color image, but these methods can struggle when shadows are hard to see.
For PlatoNeRF, the MIT researchers built off these approaches using a new sensing modality called single-photon lidar. Lidars map a 3D scene by emitting pulses of light and measuring the time it takes that light to bounce back to the sensor. Because single-photon lidars can detect individual photons, they provide higher-resolution data.
The researchers use a single-photon lidar to illuminate a target point in the scene. Some light bounces off that point and returns directly to the sensor. However, most of the light scatters and bounces off other objects before returning to the sensor. PlatoNeRF relies on these second bounces of light.
By calculating how long it takes light to bounce twice and then return to the lidar sensor, PlatoNeRF captures additional information about the scene, including depth. The second bounce of light also contains information about shadows.
The system traces the secondary rays of light those that bounce off the target point to other points in the scene to determine which points lie in shadow (due to an absence of light). Based on the location of these shadows, PlatoNeRF can infer the geometry of hidden objects.
The lidar sequentially illuminates 16 points, capturing multiple images that are used to reconstruct the entire 3D scene.
Every time we illuminate a point in the scene, we are creating new shadows. Because we have all these different illumination sources, we have a lot of light rays shooting around, so we are carving out the region that is occluded and lies beyond the visible eye, Klinghoffer says.
A winning combination
Key to PlatoNeRF is the combination of multibounce lidar with a special type of machine-learning model known as a neural radiance field (NeRF). A NeRF encodes the geometry of a scene into the weights of a neural network, which gives the model a strong ability to interpolate, or estimate, novel views of a scene.
This ability to interpolate also leads to highly accurate scene reconstructions when combined with multibounce lidar, Klinghoffer says.
The biggest challenge was figuring out how to combine these two things. We really had to think about the physics of how light is transporting with multibounce lidar and how to model that with machine learning, he says.
They compared PlatoNeRF to two common alternative methods, one that only uses lidar and the other that only uses a NeRF with a color image.
They found that their method was able to outperform both techniques, especially when the lidar sensor had lower resolution. This would make their approach more practical to deploy in the real world, where lower resolution sensors are common in commercial devices.
About 15 years ago, our group invented the first camera to see around corners, that works by exploiting multiple bounces of light, or echoes of light. Those techniques used special lasers and sensors, and used three bounces of light. Since then, lidar technology has become more mainstream, that led to our research on cameras that can see through fog. This new work uses only two bounces of light, which means the signal to noise ratio is very high, and 3D reconstruction quality is impressive, Raskar says.
In the future, the researchers want to try tracking more than two bounces of light to see how that could improve scene reconstructions. In addition, they are interested in applying more deep learning techniques and combining PlatoNeRF with color image measurements to capture texture information.
While camera images of shadows have long been studied as a means to 3D reconstruction, this work revisits the problem in the context of lidar, demonstrating significant improvements in the accuracy of reconstructed hidden geometry. The work shows how clever algorithms can enable extraordinary capabilities when combined with ordinary sensors including the lidar systems that many of us now carry in our pocket, says David Lindell, an assistant professor in the Department of Computer Science at the University of Toronto, who was not involved with this work.
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Researchers leverage shadows to model 3D scenes, including objects blocked from view - MIT News
J. Cole Smith Reappointed to 5-Year Term as Dean of College of Engineering and Computer Science Syracuse … – Syracuse University News
J. Cole Smith
Vice Chancellor, Provost and Chief Academic Officer Gretchen Ritter today announced that J. Cole Smith has been reappointed to a five-year term as dean of the College of Engineering and Computer Science (ECS). Todays announcement follows a comprehensive review process that includes feedback from key stakeholders, including ECS faculty, staff and advisory board members.
In Coles nearly five years as dean, the College of Engineering and Computer Science has grown stronger on multiple counts and made great strides towards reaching a new level of excellence, Provost Ritter says. This is an exciting time for the college, and I can think of no better leader to shepherd the students, faculty, staff and alumni into this new era.
Smith assumed leadership of ECS in October 2019. His tenure has been marked by several high points for the college. A massive renovation, which included multiple new lab spaces and the Allyn Innovation Center, served to modernize ECS buildings and facilities. The pending new Campos Student Center, supported by a recent $2 million gift that Smith helped secure, will further enhance the colleges physical space.
Smith oversaw the development of the new Syracuse University Center for Advanced Semiconductor Manufacturing, an interdisciplinary center that brings together expertise in artificial intelligence, cybersecurity, manufacturing processes, optimization and robotics to advance the science of semiconductor manufacturing. He also helped launch a new masters degree program in operations research and system analytics, as well as the signature co-op program.
Under Smiths leadership, ECS research expenditures grew by 30% during the 2022-2023 academic year over 2019 levels. Enrollment, faculty size and staff size are also on track to grow by 50% in the next four years as part of a plan Smith developed. He also helped guide the college toward bronze-level status in the American Society for Engineering Educations Diversity Recognition Program.
Engineering and Computer Science is driving regional, national and international growth in areas such as advanced manufacturing, sustainable infrastructure, healthcare engineering, advanced computing technologies and materials science, Smith says. I have never been a part of a more exciting moment at the nexus of college, University, city and national growth. What we are doing here matters and will resonate for decades to come, and it is a true privilege to have the opportunity to realize the transformational opportunity that awaits Syracuse University and the College of Engineering and Computer Science.
Smith came to Syracuse from Clemson University, where he held positions as associate provost for academic initiatives and chair of the Department of Industrial Engineering. His research focuses on integer programming and combinatorial optimization, network flows and facility location, computational optimization methods and large-scale optimization due to uncertainty or robustness considerations. In 2023, he was named an Institute for Operations Research and the Management Sciences (INFORMS) fellow.
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Kallie (Ziltz) Pearl Named Percy Hughes Award Recipient – Lehigh University
This years recipient of the Percy Hughes Award received multiple nominations from faculty and students across the Lehigh community. Kallie (Ziltz) Pearl '16 '17 '18G '24 Ph.D. is a four-time Lehigh alumna, most recently graduating from the College of Educations Teaching, Learning and Technology (TLT) program with her doctoral degree.
Pearl joined the P.C. Rossin College of Engineering and Applied Science faculty in 2020, where she has developed innovative ways to engage studentsespecially women and other underrepresented populationsin computer science.
Teaching is something that I was born to do, she says. But I have been so blessed to cultivate an interdisciplinary niche for myself between computer science and education.
LILAC (Looping Interactive Learning and Authentic Contexts) is the acronym Pearl uses to describe the innovative approach she developed with colleagues to improve student engagement and learning. In her nomination of Pearl, TLT professor and program director Brook Sawyer explains, Kallies mission of improving Lehighs computer science courses has been unwavering since she has been an undergraduate student herself, struggling to feel like she fit in computer science as a woman.
Former student Alexia Drey noted Pearls generosity of spirit and support for her students in her award nomination.
Dr. Pearl wants each and every one of her students to know that they can and will succeed in her course if they put in the effort, despite being from a traditionally underrepresented group, Drey says. She inspires her students every day, and her passion and love for computer science shines through every time you interact with her.
A tireless advocate for women in computing, Pearl led a group of students attending the Grace Hopper Celebration this past fall. Nominator and program director Sharon Kalafut says Pearl came to her years ago with the idea to start a Women in Computing Club within the COE. Today, Pearl serves as the faculty advisor for the club. During the summer and weekends, she has worked with middle school students as part of the Women in Science & Engineering (WISE) days and Charting Horizons and Opportunities in Careers in Engineering and Science (CHOICES) program at Lehigh as well as the DaVinci Center in Allentown.
In his nomination TLT faculty advisor Tom Hammond notes, The most visible impact of Kallies work is her publications, which span both academic journals, such as the International Journal of Computer Auditing, popular outlets such as the Huffington Post and presentations including keynote and panelist roles for the WISE initiative.
I see myself in the work Hughes accomplished, and know that my path would not be as clear without folks like him paving the way, says Pearl. I don't see my work in the classroom and as an educational researcher as big or bold, but I know that it is important to push Lehigh to emerge as a strategic leader in high-quality education.
Over the course of his 35-year tenure at Lehigh, Percy Hughes used the responsibility of scholarship to pursue social change and transform the Lehigh culture. By committing himself to interdisciplinary work and humanistic principles, he furthered Lehighs tradition of scientific and classical education. From womens rights to environmentalism, Hughes devoted his life to historically progressive ideas.
The Percy Hughes Award for Scholarship, Humanity and Social Change is awarded annually by the College of Education to honor a Lehigh community member who works towards implementing transformative ideas in the local, national and world communities. Since the award's inception in 2010, nine individuals have been recognized for their work addressing the world's most pressing challenges. Award recipients are leaders who not only foster Lehigh's historic educational mission, values and core beliefs but also push Lehigh in new directions and heights of excellence.
To learn more about Hughes and the Percy Hughes Award, visit https://ed.lehigh.edu/insidecoe/awards/percy-hughes-award.
Story by Beth Blew.
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Kallie (Ziltz) Pearl Named Percy Hughes Award Recipient - Lehigh University
Bill would require Michigan high schools to offer computer science course – 9 & 10 News
LANSING Computer science courses could soon become available to more Michigan students under a new proposal in the state legislature.
All Michigan high school students would have the opportunity to take a computer science course under new legislation proposed in the state house.
Bill sponsors say that over 30 other states already require the offering of a computer science course for high school students, as well as 55% of Michigan high schools.
The proposal would require all public high schools to offer at least one computer science course but would not implement the course as a graduation requirement. The policy wouldnt go into effect until 2027.
The legislation would also allow schools to offer the course virtually if they lack the resources for in-person teaching.
Rep. Carol Glanville, a former teacher and sponsor of the bill, says that computer science courses provide both direct knowledge of technology and the thinking abilities that are becoming more critical by the day.
Computer science is a foundational skill necessary for todays students to succeed in a 21st century society, said Glanville, D-Walker.
Supporters of the legislation also say the requirement would help students from all backgrounds explore the topic more easily. Over 70% of current computer science students are boys, and Black students are underrepresented compared to White and Asian students.
By putting computer science in every high school that will help communicate that this opportunity is open to all students, said Julia Wynn, representing code.org.
Lisa Rivera, a teacher from Mackinaw City, testified in support of the bill, saying her rural district of less than 150 students has offered a computer science course for nearly 20 years and requires it for students in 10th grade.
The computer science classroom environment is truly amazing, she said. No matter the topic being covered, there is a focus on problem solving and collaboration. This focus helps students become leaders in the classroom, students who arent always traditional leaders and other academic areas.
Any teacher would be able to teach a computer science course after completing a professional development course.
According to the Bureau of Labor Statistics, the media annual wage for the computer and IT industry is over $100,000, double the national average for all fields. The Bureau also projects over 350,000 openings in the field per year through 2032, a growth rate faster than most other industries.
The bill has bipartisan support from members of the House Education Committee and could be passed into law later this year.
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Bill would require Michigan high schools to offer computer science course - 9 & 10 News
Noise-canceling headphones can use AI to ‘lock on’ to somebody when they speak and drown out all other noises – Livescience.com
Noise-canceling headphones are widespread nowadays, but scientists have found a way to take these devices to the next level by creating headphones that can focus on one external sound source and block out all other noises.
The technology, called "Target Speech Hearing," uses artificial intelligence (AI)to let the wearer face a speaker nearby and after a delay of a couple of seconds lock onto their voice. This lets the user hear only that specific audio source, retaining the signal even if the speaker moves around or turns away.
The technology comprises a small computer that can be embedded into a pair of commercial, off-the-shelf headphones, using signals from the headphones' built-in microphone to select and identify a speaker's voice. The scientists outlined the details in a paper published on May 11 in the journal Proceedings of the CHI Conference on Human Factors in Computing Systems.
Related: 'It would be within its natural right to harm us to protect itself': How humans could be mistreating AI right now without even knowing it
Scientists hope the technology could be used as aids for people with impaired hearing, and they are working to embed the system into commercial earbuds and hearing aids next.
"We tend to think of AI now as web-based chatbots that answer questions," said study lead author, Shyam Gollakota, professor of Computer Science & Engineering at the University of Washington. "In this project, we develop AI to modify the auditory perception of anyone wearing headphones, given their preferences. With our devices you can now hear a single speaker clearly even if you are in a noisy environment with lots of other people talking," Gollakota said in a statement.
Target Speech Hearing (TSH) follows on from research the same scientists conducted into "semantic hearing" last year. In that project, they created an AI-powered smartphone app that could be paired with headphones, which let the wearer choose to hear from a list of preset "classes" while canceling out all other noises. For example, a wearer could choose to hear sirens, babies, speech or birds and the headphones would single out only those noises and block out all others.
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To use TSH, the wearer faces straight in front of the speaker whose voice they wish to hear, before tapping a small button on the headphones to activate the system when positioned correctly.
When the speaker's voice arrives at the microphone, the machine learning software then "enrolls" the audio source. It allows for a small margin of error in case the listener isn't directly perpendicular to the speaker before it identifies the target voice and registers vocal patterns. This lets it lock onto the speaker regardless of the volume or the direction they're facing.
As the speaker continues talking, it improves the system's ability to focus on the sound because the algorithm better identifies the unique patterns of the target sound over time.
For now, TSH can only enroll a single audio source, or a single speaker, at any one time, and it's less successful if there's another noise of a similar volume coming from the same direction.
In an ideal world, the scientists would present the system with a "clean" audio sample to identify and enroll, with no other environmental noise that could interfere with the process, they said in the paper. But this would not be well-aligned with building a practical device, as obtaining a clear sound is challenging in real-world scenarios.
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Master’s student capstone spotlight: AI-Enabled Information Extraction for Investment Management – Harvard School of Engineering and Applied Sciences
Data science and computational science and engineering masters students at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) take AC297R: Computational Science and Engineering Capstone Project. Taught by Weiwei Pan, Assistant Director for Graduate Studies in Data Science, the course groups students together for semester-long research projects in which they work with client organizations to tackle real-world challenges.
AI-Enabled Information Extraction for Investment Management
Noah Dohrmann (S.M. 24), Sudhan Chitgopkar (S.M. 24), Jimmy Mendez (S.M. 24), Stephanie Monson (S.M. 24, M.E. 25)
Client: Harvard Management Company
What real-world challenge does this project address?
This project focuses on extracting information from Limited Partnership Agreements legal documents which outline terms for a monetary partnership between two entities. These documents are long, verbose, and difficult to parse. As a result, entire legal teams are sometimes necessary to summarize these documents. Here, we streamline the process by developing a machine learning model able to ingest and extract salient information from LPAs, reducing the workload and complexity that financial firms like the Harvard Management Company face.
How does this research attempt to solve that real-world challenge?
This research helps take large semi-structured data (like long documents that have different sections or subsections) and extract a set of terms from the data. Presently, machine learning models aren't well-suited to understanding and retaining large amounts of context (as you might need when reading 100+ page documents). To solve this problem, our research has developed both machine learning and classical software engineering applications to help pass only the most relevant context to large language models (LLMs). We also develop some of the existing literature on prompt engineering to help LLMs generate accurate answers to tough, industry-specific questions.
How did you apply the skills you learned at SEAS to your project?
The skills weve learned at SEAS helped us design and develop a cohesive and production-level application end-to-end. SEAS has taught us how to design good, robust, and versatile software and how to turn those designs into reality at scale to be deployed at companies of all sizes which is hopefully the future for this project!
What part of the project proved the most challenging?
LLMs are very prone to hallucination, or providing a false response if it does not find the query or if the query answer does not exist in the document at all. These false positives are quite undesirable when the information extracted from the document will be used to make key business decisions, such as investment. Through prompt engineering techniques, we were able to greatly reduce the false positive rates.
What part of the project did you enjoy the most?
We really enjoyed working closely alongside the C-suite, data science team, and lawyers at the Harvard Management Company, and gaining insights from different stakeholders in the project. Often, we think software projects like these are limited to developers and their direct managers, but having such a diverse set of people working alongside us gave us fresh new perspectives and helped us consider new ideas.
What did you learn, or skills did you gain, through this project?
We were able to broaden our understanding of different machine learning paradigms while getting rigorous hands-on experience and developing production-level software with some great people!
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What incoming students can harness from a successful UW-Madison computer sciences alum – Daily Cardinal
John Stecher sits in an office in New York City, reflecting on a career trajectory that most young professionals can only dream of.
Today, he is the head of Technology and Innovations at Blackstone, the world's largest alternative investment firm. But 27 years ago, he was only a computer science freshman at the University of Wisconsin-Madison.
Stecher, a UW-Madison alum, commands a crucial role as the chief technology officer at Blackstone. His journey from the collegiate labs of Madison to the executive offices on Lexington Avenue embodies professional growth, determination and the power of collaboration.
Many incoming students may look to technical proficiency as the only cornerstone of corporate success. But Stecher's journey from UW-Madison to Blackstone illustrates that success also depends on embracing hard work, strategic thinking and an innovative spirit. Adopt these principles as your tools to transform challenges into opportunities and aspirations into achievements.
Stecher began his rise to Blackstone at IBM, where he was awarded the title of Master Inventor.
"The title Master Inventor means that you are constantly innovating and driving forward IBM's intellectual property portfolio," Stecher told The Daily Cardinal.
Over his nine-year tenure at IBM, Stecher contributed to 45 patents, each addressing various complex challenges that had not been solved before. His innovations ranged from improving how computers manage their memory and resources to designing better ways to store data across different areas in a network.
This period of his career illustrates Stecher's commitment to continual learning and an unwavering drive to pioneer solutions that had never been achieved before.
But he didnt do it alone. Stecher, working alongside a dedicated IBM team, helped create, refine and implement solutions "that can actually be helpful in the world."
Reflecting on his title as a Master Inventor, Stecher said it influences everything from receiving accolades "woo, you're a master inventor, that's super cool!" to developing a deeper understanding of collaboration's role in innovation.
You cant make stuff by yourself. You are just a single person with a finite set of ideas, and no matter how smart you are, working together and collaborating with others is so much more effective," Stecher said.
Following his tenure at IBM, he joined Goldman Sachs as a managing director, where he helped launch the firm's retail banking division.
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But the primary focus for Stecher in his later years was running the engineering and product teams for Marcus, a consumer banking platform designed to simplify personal finance with user-friendly online services for savings, loans and investment management. Under Stecher's leadership, the team managed to "move from the first line of code to booking loans within six months, then going live by the tenth month."
This turnaround not only showcased his ability to lead under pressure but also showed the necessity of flexible leadership in the fast-paced tech environment.
Stecher then transitioned to Barclays, serving as the chief technology officer and innovation officer for three years then moved to Blackstone to assume the role of chief technology officer.
Blackstone is the world's largest alternative asset manager with $1.04 trillion in assets under management as of Dec. 31, according to Investors Business Daily.
In his role, Stecher focuses on harnessing the power of technology to transform and enhance Blackstone's operations. Stecher has been instrumental in migrating Blackstone to Amazon Web Services (AWS), completed at the end of 2021.
Stecher credits this move as a foundational element for the future of Blackstone, allowing for continued operational advancements.
"I looked at what would increase efficiency and enable a highly available infrastructure that could span across the U.S. in different data centers, Stecher said. That was a huge part of my decision to move toward AWS."
But Stecher said he doesn't always jump for the newest technologies, instead looking at the cost of making the move versus the benefit."
From recent innovations at Blackstone, to a career-long commitment to principles of determination, innovation and collaboration, Stechers path to success embodies the Wisconsin Idea of lifelong learning.
Whether youre an incoming student, or preparing to graduate next spring, consider how Stechers principles of relentless pursuit and strategic innovation can be applied to your studies and upcoming careers.
What solutions can you devise for the pressing issues in your field? How might you, like Stecher, drive forward the next wave of innovation?
His path from the classrooms of UW-Madison to the executive suite at Blackstone demonstrates that success is often not just about what you learn, but about how you apply that knowledge to tackle the challenges you encounter and adapt creatively at every step.
Bryson Turner is a sophomore studying computer science and economics. Do you agree that an emphasis on collaboration and a focus on innovation is the key to career success? Send all comments to opinion@dailycardinal.com.
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