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Wrapping Up SGI 2021

After six weeks of intensive research and tutorials on applied geometry, we finally are ready to wrap up SGI 2021 and send our Fellows back to their home institutions. Directing this program has been one of the most rewarding experiences of my career, and it has been a pleasure seeing our students advance as scientists, mathematicians, and supportive community members.

SGI’s success is entirely thanks to a huge team of volunteers whose time and energy made the program possible.

Below, I acknowledge the many colleagues who have participated in the planning, leadership, and day-to-day activities of SGI 2021. The sheer length of this list is an inspiring reflection of the supportive community we enjoy in geometry research.

To start, SGI 2021 was only possible with the support of our generous sponsors, whose donations allowed us to offer a stipend to each SGI Fellow commensurate with a summer internship:

SGI was organized over the previous year with guidance from colleagues at a variety of institutions worldwide. A Steering Committee provided opinions and advice throughout the planning process:

Within MIT, several faculty and staff members contributed substantial effort to make the program a success. My team in the Geometric Data Processing (GDP) Group provided advice and volunteer support, from feedback on how to structure the program to hand-packing 72 boxes to ship to our Fellows and volunteers; GDP admin Mieke Moran organized payments and many other key aspects that made the program run smoothly. Our EECS Department Chair Prof. Asu Ozdaglar, AI+D Chair Prof. Antonio Torralba, and CSAIL Director Prof. Daniela Rus advocated for the program and provided support and encouragement as SGI obtained final approval within the MIT administration. CSAIL Assistant Director Carmen Finn provided critical last-minute help to make sure our Fellows were paid on time. Prof. Frédo Durand provided much-needed advice—and allowed me to vent—at several junctures.

SGI 2021 received far more applications than anticipated, and our final cadre of 34 Fellows and 29 additional tutorial week participants was painfully difficult to select. Our admissions committee carefully read all the applications:

The first week of SGI centered around five days of tutorials to get our Fellows up to speed on geometry processing research. Each tutorial day was organized by a different volunteer, who took charge of the content for the entire day and generated valuable course materials we can reuse in the future:

  • Day 1: Dr. Oded Stein (MIT), basic techniques in geometry processing
  • Day 2: Hseuh-Ti (Derek) Liu (University of Toronto) and Jiayi Eris Zhang (University of Toronto and Stanford), shape deformation
  • Day 3: Silvia Sellán (University of Toronto), shape representations
  • Day 4: Michal Edelstein (Technion) and Abhishek Sharma (École Polytechnique), shape correspondence
  • Day 5: Prof. Amir Vaxman (Utrecht University), directional fields

The remaining five weeks of SGI included a host of 1-3 week research projects, each involving experienced mentors working closely with SGI Fellow. Our full list of projects and project mentors is as follows:

  • Dr. Itzik Ben-Shabat: Self-supervised normal estimation using shape implicit neural representation (August 16-August 27)
  • Prof. Mikhail Bessmeltsev and Prof. Ed Chien: Singularity-Free Frame Field Design for Line Drawing Vectorization (July 26-August 6)
  • Dr. Tolga Birdal and Prof. Nina Miolane: Uncertainty Aware 3D Multi-Way Matching via Soft Functional Maps (July 26-August 6)
  • Prof. David Bommes and Dr. Pierre-Alexandre Beaufort: Quadrilateral and hexahedral mesh optimization with locally injective maps (July 26-August 6)
  • Prof. Marcel Campen: Improved 2D Higher-Order Meshing (July 26-July 30)
  • Prof. Keenan Crane: Surface Parameterization via Intrinsic Triangulations (August 9-August 27)
  • Dr. Matheus Gadelha: Learning Classifiers of Parametric Implicit Functions (August 16-August 27)
  • Prof. Lin Gao and Jie Yang: Unsupervised partial symmetry detection for 3D models with geometric deep learning (August 16-August 27)
  • Christian Hafner and Prof. Bernd Bickel: Joints for Elastic Strips (August 9-August 13)
  • Yijiang Huang and Prof. Caitlin Mueller: Design optimization via shape morphing (August 16-August 27)
  • Dr. Xiangru Huang: Moving Object Detection from consecutive LiDAR Point Clouds (August 23-August 27)
  • Prof. Michael Kazhdan: Multigrid on meshes (July 26-July 30)
  • Prof. Paul Kry and Alexander Mercier-Aubin: Incompressible flow on meshes (July 26-August 6)
  • Prof. Kathryn Leonard: 2D shape complexity (July 26-July 30)
  • Prof. David Levin: Optimal Interlocking Parts via Implicit Shape Optimizations (July 26-August 6)
  • Angran Li, Kuanren Qian, and Prof. Yongjie Jessica Zhang: Geometric Modeling for Isogeometric Analysis with Engineering Applications (August 2-August 6)
  • David Palmer: Bayesian Rotation Synchronization (August 2-August 13); Planar-faced and other specialized hexahedral meshes (August 16-August 27)
  • Prof. Jorg Peters (The beauty of) Semi-structured splines (August 9-August 13)
  • Alison Pouplin and Dimitris Kalatzis: Learning projection of hierarchical data with a variational auto-encoder onto the Klein disk (July 26-August 6)
  • Prof. Leonardo Sacht: Robust computation of the Hausdorff distance between triangle meshes (August 9-August 20)
  • Prof. Yusuf Sahillioglu: Cut optimization for parameterization (August 2-August 13)
  • Josua Sassen and Prof. Martin Rumpf: Mesh simplification driven by shell elasticity (August 9-August 20)
  • Dr. Nicholas Sharp, Prof. Etienne Vouga, Josh Vekhter: Nonmanifold Periodic Minimal Surfaces (August 9-August 27)
  • Dr. Tal Shnitzer-Dery: Self-similarity loss for shape descriptor learning in correspondence problems (August 9-August 13)
  • Dr. Ankita Shukla and Prof. Pavan Turaga: Role of orthogonality in deep representation learning for eco-conservation applications (August 9-August 13)
  • Prof. Noah Snavely: Reconstructing the Moon and Earth in 3D from the World’s Photos (August 9-August 13)
  • Prof. Justin Solomon: Anisotropic Schrödinger Bridges (August 16-August 27)
  • Prof. Marco Tarini: Better Volume-encoded parametrizations (August 2-August 13)
  • Prof. Amir Vaxman: High-order directional field design (July 26-August 6)
  • Prof. Etienne Vouga: Differentiable Remeshing (July 26-August 6)
  • Dr. Stephanie Wang: Discrete Laplacian, area functional, and minimal surfaces (August 16-August 20)
  • Paul Zhang: Classifying hexahedral mesh singular vertices (July 26-August 6); Subdivision Surface Mesh Fitting (August 16-August 27)

An intrepid team of TAs helped our participants learn new topics, refined the tutorial activities, and supported the research projects:

Each week of SGI, we had multiple guest speakers drop by to share their research and experiences, and to give advice to the SGI Fellows:

  • Prof. Katia Bertoldi, Harvard: Multistable inflatable origami from deployable structures to robots
  • Prof. Michael Bronstein, Twitter/Imperial College London: Geometric Deep Learning: the Erlangen Programme of ML
  • Prof. Albert Chern, UCSD: Gauge Theory for Vector Field Design
  • Prof. Bruce Fischl, Harvard/MGH: Geometry and the Human Brain
  • Dr. Fernando de Goes, Pixar: Geometry Processing at Pixar
  • Prof. Rana Hanocka, University of Chicago: Deep Learning on Meshes
  • Prof. Alexandra Ion, Carnegie-Mellon University: Interactive Structures – Materials that can move, walk, compute
  • Prof. Chenfanfu Jiang, UCLA: Developments in smooth optimization contact
  • Prof. Theodore Kim, Yale University: Anti-Racist Graphics Research
  • Prof. Yaron Lipman, Weizmann Institute: Implicit Neural Representations
  • Prof. Mina Konaković Luković, MIT: Transforming Design and Fabrication with Computational Discovery
  • Prof. Lakshminarayanan Mahadevan, Harvard: Folding and cutting paper: art and science
  • Prof. Caitlin Mueller, MIT: Geometry of High-Performance Architecture
  • Prof. Matthias Niessner, TU Munich: Learning to Reconstruct 3D Scenes
  • Íñigo Quílez: Intro to SDFs and Examples
  • Dr. Elissa Ross, Metafold: Periodic geometry: from art to math and back again
  • Dr. Ryan Schmidt, Epic Games and Gradientspace: Geometry Processing in Practice
  • Prof. Tamar Shinar, UC Riverside: Partitioned solid-fluid coupling
  • Prof. Emily Whiting, Boston University: Mechanics-Based Design for Computational Fabrication

Last but not least, incoming MIT PhD student Leticia Mattos Da Silva organized a talk and panel discussion on the graduate school application process, including a Q&A with Silvia Sellán, Jiayi Eris Zhang, and Oded Stein.

The cast of thousands above is a testament to the dedication of the geometry research community to developing a diverse, energetic community of young researchers.

SGI 2021 comes to a close as quietly as it began, as our Fellows and mentors close one final Zoom call and return to their lives scattered over the globe. In the months and years to come, we look forward to keeping in touch as our Fellows become colleagues, collaborators, and leaders of future generations of researchers.

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Like drinking from a fire hose

That was the tongue-in-cheek remark our TA Peter Rock made at the end of SGI’s last tutorial week session. For me, a fresh CS graduate who always managed to steer clear of the dark abyss where “real math” hides, that remark hit close to home. I think it is fair to say that even for the most math whizzy of us fellows, whether it felt like drinking from a fire hose or a squeeze bottle, the tutorial week left us undeniably very well hydrated.

The week started with Oded Stein’s lecture, an extremely friendly introduction to this new world of geometry processing. For me, it felt like a mixed bag of known concepts, brand new stuff, and some in-between. Maybe because of this, Oded’s lecture was just the introduction I needed to feel like I could do this thing. Surely enough, a few minutes after Oded finished his lecture, pictures of mangled triangle meshes and Gouraud-shaded goats started to flood our Slack. Not only could we do this, we were doing it!

Finally, Prof. Justin Solomon made some remarks at the end of the day that resonated with me so much; I hope I never let myself forget. I do not remember his exact words, but the message was: “math is hard for everyone. There’s no shame in it. Your job is not to understand things right away. Your job is to ask for help until you do.”

What followed the next day was a lecture by Derek Liu, showing how a few lines of math wizardry in MATLAB could perform shape deformations. Things were starting to look like the SIGGRAPH videos I’ve been drooling over for years! As is to be expected, with great wizardry comes great amounts of students asking for help. I was among them. Yet, Derek was so incredibly patient in walking all of us through each mathematical question and their respective MATLAB lines, I left the session actually knowing how to do those things. For someone who loved the videos but never understood a line of the papers, it was a day to remember.

The day continued, then, with Eris Zhang’s lecture, which took Derek’s concepts even further. It was mind-blowing to think a few months ago, a video of Eris’ work was one of those I was drooling over, and now she was there, teaching us the ropes, using excerpts from the video as an example! To me, that is the perfect picture of what an invaluable experience SGI is.

The third day was a very different experience (for me). Silvia Sellán’s lecture brought me a new point of view for things like splines and NURBS, concepts I had previously taught as a TA for semesters on end (albeit years ago). Her approach was very lighthearted and humorous, yet very grounded, making sure everything was accessible and carefully explained. The exercises were equally well thought out. Even so, I eventually needed to ask for help on a more “mathy” task, but Silvia did not give me the answer. Instead, she smoothly guided me through figuring it out for myself, which was amazing! Her closing remarks were: “now make sure you help others who struggle as well.” To me, this way of thinking summarizes the incredible spirit we’ve been having throughout the program.

The day closed with a talk by Shadertoy’s Íñigo Quilez, which first introduced us to rendering using SDFs, then completely opened Pandora’s box. Íñigo’s message was: “you are future researchers, well, here are some things for you to think about.” As honored as I feel by his trust in us, I must say I was too mesmerized by the rendering possibilities to think about how to solve the issues. As someone who used traditional rendering approaches for a long time, the world of SDFs felt like a trip to wonderland for a Mad Hatter’s tea party. A trip I wish to repeat soon! Again the feeling I had on the previous days is repeated: I had been visiting Shadertoy since before college, looking at the walls of code and wondering how they yielded such mesmerizing results. Well, now Íñigo has shown us the way, and the ball is on our court. Amazing.

I could go on for pages talking about the following days, including the incredible first week of research, but I believe this is better suited for a subsequent post. Overall, I can say that I feel extremely fortunate to be a part of this thing, be hand-fed this select knowledge from such experts in the field, and now have such an overview of what paths I can take in my career. SGI is proving to be much more of a game-changer in my life than I could have ever previously imagined. To everyone who made this possible, my sincerest thank you!!

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SGI: The First Day

July 19th 2021, the long anticipated day that SGI 2021 begins. I woke up nervous and excited. I reviewed the first 4 exercises, ate breakfast and then logged into Zoom from my bedroom in Winchester, VA. I joined the other fellows, professors, and invited guests who all logged in from their respective time zones all over the world. My nervousness faded when Oded Stein, before he began his lecture, said “If you’re here, you already fulfill the prerequisites”. It made me feel at ease and realize that we were all picked to be here for a reason and while some people have different strengths than me, I was chosen and I should be here too.

Oded Stein began his course on basic techniques in geometry processing by first explaining what geometry processing is. This was very helpful as I could now understand what it is from a few different perspectives as well as have a good answer for when people ask me what I am doing this summer. The course was a great introduction as I had never been introduced to any topics in geometry processing and the exercises helped greatly. My favorite exercise was on Shading and Perspective. I was able to take my new friend Spot the cow and give him multiple makeovers. I changed him from ombre, to blue, to red (my friend who is a ginger specifically asked for this one). I added different lighting and even gave him a shadow. I learned how to change the perspective so his proportions would look more realistic, and take away the axis so there was less distraction.

Another thing I really enjoyed was the talk from Ryan Schmidt, from Epic Games. The part I found particularly interesting in his talk was how geometry processing is used all over, especially in the medical field; to make prosthetics, help doctors 3D print arteries and organs to visualize before surgery, and even dentists use it to scan and model teeth.

The First Day was awesome and I can’t wait to continue to learn and research more in this area in the weeks to come. 🙂

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Before the Beginning

While the official start date, 19th of July, is still a couple of days from now, the SGI experience began the very day I received the acceptance letter back in March. In this post I briefly share my thoughts on the journey so far – SGI’s social event, attending the Symposium on Geometry Processing 2021, and my implementation of a paper presented in the conference.

Slack and Virtual Coffees

The SGI slack channel was created at the end of March and has been buzzing with activity ever since. Initially, as everyone introduced themselves, I was proud to see that I am a part of a team that is truly diverse in every aspect – geographically, racially, religiously and even by educational backgrounds!

Shortly after, we started biweekly ‘virtual coffees’ in which two people were randomly paired up to meet. These sessions have been instrumental in refining my future goals. As someone who entered research just as the world closed down and started working from home, I haven’t had the opportunity to visit labs and chat with graduate students during the lunch break or by that water cooler. Speaking with professors, teaching assistants and SGI Fellows has debunked many of my misconceptions regarding graduate school.  Additionally, I also learned a lot about possible career paths in geometry processing and adjacent fields like computer graphics, and about the culture in this community.

Symposium on Geometry Processing

SGP was a comprehensive four-day event including tutorials, paper presentations and talks on the latest research in the field. While all the sessions were amazing, I was especially awed by the keynote ‘Computing Morphing Matter’ by Professor Lining Yao from Carnegie Mellon University. She talked about various techniques that combine geometry, physics, and material science to create objects that can change shape in a pre-determined manner. This ability to morph can be leveraged in various ways and across many industries. To list a few of its usages, it can be used to create a compact product that can morph into the final shape later thus saving packaging material and shipping costs, to develop self-locking mechanisms, and to produce aesthetically appealing shapes. Due to such varied use cases, morphing matter has applications in furniture designing to food production to engineering problems.

Implementing ‘Normal-Driven Spherical Shape Analogies’

In one section of the tutorial ‘An Introduction to Geometry Processing Programming in MATLAB with gptoolbox’ at SGP, the ease with which complex problems can be solved using MATLAB and gptoolbox was demonstrated by implementing research papers. I had never before seen a language/library tutorial that included paper implementations and was delighted at the prospect of turning the tedious process of learning a new tool into an exciting process of implementing a research paper. Eager to test out this new way, I implemented one of the research papers presented at the SGP – ‘Normal-Driven Spherical Shape Analogies’ by Hsueh-Ti Derek Liu and Alec Jacobson.

The paper details how an input shape can be stylized to look like a target shape by using normal driven shape analogies. The process boils down to three steps:

  1. Compute the mapping between a sphere and the target shape.
  2. Using the sphere-target shape mapping as an analogy, find the target normals for the input object.
  3. Generate the stylized output by deforming the input object to approximate the target normals.

When I arrived at code that gave outputs that looked right, I faced an unanticipated problem: Without any error metric, how can you know that it’s working well? After working on this project I definitely have a renewed appreciation for work in stylization.

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2021 SGP Day 1

On the first day of the Symposium on Geometry Processing (SGP), I was excited to learn two things: how welcoming the geometry processing community is and different techniques for mesh stylization.

First, it was relieving to me when joining the ice-breaker events on the first day of SGP to learn how welcoming the community is to attendees from all levels. At first, I was scared to introduce myself as an undergraduate student who is new to this discipline and am going to work in SGI as a summer fellow. However, the graduate students, postdocs, and professors were really welcoming, and I was excited to see some of the mentors in the breakout rooms. Through conversations with other Ph.D. students, professors, and engineers in non-academic disciplines, I realized how people from different backgrounds can all contribute to this field. This eased my nervousness from the past two days and motivated me to explore more about geometry processing through SGP!

Second, I would like to highlight two talks in mesh stylization given by Maximilian Kohlbrenner and Hsueh-Ti Derek Liu, respectively, titled “Gauss Stylization: Interactive Artistic Mesh Modeling based on Preferred Surface Normals” and “Normal-Driven Spherical Shape Analogies”. To begin with, a style is a “distinctive manner which permits the grouping of works into related categories” (Fernie 1995, referenced in Liu’s talk). In geometry processing, stylization tools take a piece of geometry and reshape it to have a distinctive appearance. Some elements of style are straightforward, such as shapes, proportions, and lines. One previous stylization method is cubic stylization, whose objective function sums an as rigid as possible (ARAP) energy term and a “cubeness” term with a scalar weight \(\lambda\).

In Kohlbrenner’s talk, he discussed Gauss stylization, which subtracts cubeness from the ARAP energy instead of adding them together. Then, they reformulate their energy by decoupling the normals such that there are 3 sets of variables, leading to an ARAP-like optimization method. It was difficult for me to follow the details, but this is the big scale picture I learned from the talk. It is interesting to me not only because all of these are new but also because being able to see the new shapes they create from Gauss images. It would not occur to me how editing surface normals can change the look or use of a piece of geometry so much.

Liu introduced another normal-driven algorithm to stylize different shapes. The main idea of his 3-step algorithm works as follows. First, he matches the sphere to a style template. Second, he matches the sphere to an input shape. Last, he does deformation (optimization) through a normal-based method. His work uses two different constructions related to shape matching and editing: the Gauss map and curvature flow. As introduced above, Gauss maps go from every point on a surface to its normal on the unit sphere, which can be edited to express a transformation of a surface. After describing the basic steps of his method, Liu discussed the difficulty of the optimization process and his approach. The difficulty lies in the fact that the equations are nonlinear. However, with a change of variables, the equations show how some of his variables can be computed using a single SVD while others can be computed by solving a linear problem. Just like Kohlbrenner’s method, Liu’s algorithm alternates between these two steps to optimize. This research is interesting to me as this algorithm not only achieved the initial goal but also can be used in practice. In the end, he also discussed a lot of extensions and applications that are possible to explore or learn. Some include applying other energy terms (instead of the ARAP one), polycube, and geometric texture.

I really enjoyed these two lectures, which introduced Gauss maps and other related shape synthesis ideas. The contents motivate me to explore more about mesh stylization and I am excited to learn more about them in the future.

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Reporting from the SGP Graduate School

SGI Fellows were registered for and invited to attend the Symposium on Geometry Processing (SGP), the premier venue for disseminating new research ideas and cutting-edge results in geometry processing.

I am writing this from the comfort of the EST time zone and from a boring but quiet dorm room. The Symposium on Geometry Processing (SGP) has successfully reminded me of the existence of a world outside my current location – a remarkable feat, especially given the forced geographic sedentarism of the past year and a half. Plenty of SGP attendees were active, participating, asking questions, and being engaged, despite it being late at night or very early in their time zones. Many other people will watch the SGP recordings on Youtube in the upcoming days. The concluding remark of “have a great day, or afternoon, or evening, depending on where you are right now” gave insight into precisely how geographically widespread the geometry processing community is.

Before delving further, some context is warranted: SGP is a yearly conference where people disseminate new results and ideas placed at the enticing intersection of theory and applications of mathematics, computer science, engineering, and other subjects. This year’s event is divided into the Graduate School (July 10-11) and the Conference (July 12-14). As I am writing this, it is July 11, so I have only attended the Graduate School events so far. 

Out of the talks I have attended, I want to focus on the Introduction to Geometry Processing Programing in MATLAB with gptoolbox. It is a fantastic tutorial prepared and presented by Hsueh-Ti Derek Liu, Silvia Sellán, and Oded Stein, and advised by Alec Jacobson. The tutorial is comprehensive and explains how things fit together in a bigger context. Furthermore, it provides the possibility for hands-on Matlab experience, which comes with solutions in case you get stuck.

For context, gptoolbox is a set of Matlab functions for geometry processing, aimed to make things easier and to prevent researchers from reinventing the wheel. I will tell you three new things I took away from the tutorial. This is, of course, not to say that there were only three things one could take away! In fact, I encourage you to watch the video and try to find more.

First, it was great to see how “from-the-ground-up” the teaching approach was. I prefer to prevent, rather than fix, technical crises, and the introductory bits of Matlab knowledge (such as: if you want to suppress the output of a statement, terminate the statement with a semicolon) were very welcome. I spent more evenings than I would like to admit trying to compile non-working code, only to realize – by trial-and-error – that my mistake was fixable in 3 seconds. As such, explicitly stating things, with no assumption of prior knowledge, was great.

My favorite part from Oded’s section was learning how to give objects shadows, as well as playing with the way light is reflected from the surface of the object. The tutorial covered techniques based on the Phong reflection model, so I look forward to learning additional approaches and more nuanced techniques.

Second, I was especially intrigued by the part on spectral conformal mapping in Derek’s section. Not only do we get to see the theoretical description of a geometric process, the knowledge of how important the subroutine is, and the paper it is first described in, but we also get a visual representation on how the algorithm works. We get a “before” and “after” picture of a shape that is familiar to us, alongside theoretical descriptions of mathematical objects. It turns out, you CAN have the best of both (mathematical) worlds!

Third, I was especially fascinated by the ability to triangulate a 2D shape in just two lines of code with the help of the get_pencil_curve function. The idea is that you can “call” the function and draw any shape you would like, using your mouse click as the line input. First, Silvia illustrated the need for such a tool before introducing it. But also, after triangulating the figure, she outlined – for comparison – the work one might need to do to get the same result had we not had gptoolbox. The alternative included at least two other programs and the word “export” multiple times, which not only sounds like a lot of work, but also like a logistical nightmare.

As a newcomer to geometry processing, it was good to see the dedication to knowledge exchange and the great efforts made to be inclusive towards the largest possible number of people. I spent part of this summer watching geometry processing courses to bring myself up to speed with the discipline, and my brain was ecstatic when it recognized concepts I had studied earlier, or when it was able to make connections on its own. The existence of the Graduate School made me only more excited for what is in store for the rest of the conference and for the rest of the summer. So, I am keeping my brain open for all the knowledge acquisition that will undoubtedly occur during SGP and, afterwards, during Summer Geometry Institute (SGI).

Lastly – the Graduate School at SGP gave me an idea of the level of growth I will experience in the coming weeks, first at the SGP talks, and – next – at SGI. Not only will I learn a lot, but it will also be fun and incredibly rewarding! I think it will be especially interesting to put this post side by side with one I will write closer to the end of the SGI program, and to compare the difference marked by a few weeks of intensive learning. 

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Welcome to SGI 2021

Welcome to the official blog of the Summer Geometry Institute 2021, to be held July 19 to August 28, 2021. 🎉🎉🎉 I am writing this initial post to introduce our program and to share a few of our plans for this summer.

First, a quick introduction. I’m Justin Solomon, an associate professor of Electrical Engineering and Computer Science (EECS) at MIT and organizer of SGI 2021. I lead the MIT Geometric Data Processing group, which studies problems at the intersection of geometry, large-scale optimization, and applications in areas like graphics and machine learning.

SGI is the result of discussions among a worldwide network of geometry processing researchers, which started during the 2020 Symposium on Geometry Processing (SGP)—which, like many conferences in 2020, was held online for the first time. While we were sad not to see each other in person at a conference center in Utrecht, the online format format actually allowed SGP to reach a broader and more geographically diverse audience than ever before. This helped us realize that we should be creating similar opportunities for students and early-stage researchers to enter geometry processing research, even if they do not opportunities to try this discipline at their home institutions. This led us to design SGI, a summer research program designed to introduce a broad pool of students to geometry processing research through immersive interaction with top researchers in the discipline.

SGI aims to accomplish the following objectives:

  • spark collaboration among students and researchers in geometry processing,
  • launch inter-university research projects in geometry processing involving team members across broad levels of seniority (undergraduate, graduate, faculty, industrial researcher),
  • introduce students to geometry processing research and development, and
  • diversify the “pipeline” of students entering geometry processing research, in terms of gender, race, socioeconomic background, and home institution.

In addition to its research goals, SGI aims to address a number of challenges and inequities in the geometry processing discipline. Not all universities host faculty whose work touches on this emerging discipline, reducing the cohort of students exposed to this discipline during their undergraduate careers. Moreover, as with many engineering and mathematical fields, geometry processing suffers from serious gender, racial, and socioeconomic imbalance.

So, we set to work to launch SGI by summer 2021. We obtained funding from a number of generous sponsors across industry and academia, listed here. Last January, we posted an application, and by the February 15 deadline we received 627 applications! A careful review process led us to narrow down to a cohort of 35 (paid) SGI Fellows, a brilliant, diverse, and enthusiastic group of early-stage researchers; we also invited a second cohort of students to participate in our initial week of geometry processing tutorials. We were blown away by the enthusiasm and breadth of backgrounds/stories we encountered among our applicants, and our group of Fellows includes participants across many time zones and educational institutions.

Now that SGI is approaching in just a few weeks, we’re digging into the details of organizing this large, decentralized program. We’ve set up a shared Slack environment, confirmed 15 guest speakers, and tested online videochat tools. A team of SGI Fellows led by our student Lucas designed a custom-printed coffee mug to be distributed to the SGI Fellows, mentors, and volunteers. Just last week, my graduate students, postdocs, and I packed 72 packages to be mailed around the world with these mugs, as well as other swag provided by our program sponsors for the Fellows.

SGI kicks off in roughly two weeks, and it will happen in two phases:

  • In the first week, our Fellows (plus additional invited participants) will participate in tutorials led by a team of geometry processing experts, designed to introduce them to the big ideas and scientific techniques encountered in geometry processing research. Each day is led by a different researcher: Oded Stein (MIT), Silvia Sellán (U of Toronto), Hseuh-Ti (Derek) Liu (U of Toronto), Michal Edelstein (Technion), and Amir Vaxman (Utrecht University).
  • In the remaining five weeks, the students participate in short-term research projects. Each project lasts 1-2 weeks and is led by a geometry processing expert. We have over 30 project mentors, who have proposed projects across a variety of applications, from machine learning on triangle meshes to discrete differential geometry to Bayesian inference. Each project is worked on intensively by 4-8 students, who interact day-to-day through digital environments, shared repositories, and so on. Our program will be interspersed with guest speakers from industry and research, as well as panel discussions on graduate school admissions, research techniques, and other topics.

On this blog, the SGI students and team members will share their progress. Our goal is to share technical insights gained by our student as well as progress of the program itself. We invite interested parties to subscribe, so they can receive day-to-day updates as we train the next generation of geometry processing experts!