From a young age, Ms. Trine K. Quady has been intrigued by the world of chemistry. Her fascination began at just eight years old, when she blew out a candle and was mesmerized by the wispy tendrils of smoke swirling through the air. Curious about the behavior of particles, she asked her big sister if it would be possible to predict their movements if one could manipulate the air in the room. Later learning the complexity of this challenge, it foreshadowed her desire to understand the physical world through the lenses of math and chemistry and life long passion for scientific exploration.

Trine credits much of her intellectual growth to the exceptional teachers and mentors she encountered throughout her educational journey. Their encouragement pushed her to challenge herself both as a student and a researcher. Now, as a graduate student at UC Berkeley and a 2025-26 MolSSI Software Fellow, she has had the opportunity to work alongside her mentor, Dr. Taylor Barnes, who has played a pivotal role in her development as a software engineer. Under his guidance, Trine has learned to dissect large software goals into manageable tasks. Their discussions often start with high-level concepts like parallelization and then dive deep into the intricate details of hardware-level operations. This mentorship has broadened her exposure to various software tools, significantly enhancing her skills and knowledge.

The MolSSI Software Fellowship has proven to be a transformative experience for Trine, enriching her understanding of software sciences. The collaborative environment allows her to engage in meaningful conversations with her fellow software fellows, often starting from familiar ground and evolving into comprehensive discussions about software practices and hardware specifics. This supportive community has made tackling research challenges feel more achievable, providing invaluable guidance along the way.

Trine’s current research focuses on the implementation and acceleration of a local second-order Møller-Plesset Perturbation theory (MP2) code. Unlike traditional implementations, her local-MP2 code is tailored to calculate energy differences between two molecules, specifically targeting energy variations during conformational changes. By optimizing the correlation treatment in similar regions of the geometries, she aims to achieve rapid, difference-matched local MP2 energy calculations. While the theoretical speed-up is promising, the practical implementation poses significant software challenges, underscoring the vital role of the MolSSI fellowship in her journey.

Looking ahead, Trine aspires to become a professor of theoretical chemistry at a research-intensive university. She is passionate about both research and mentoring, believing that academia is the perfect setting for this blend. One of her greatest hopes is to teach a graduate-level quantum mechanics course, a subject that profoundly shaped her own academic path.

When she’s not immersed in the world of chemistry, Trine enjoys indulging her culinary skills, particularly in making “a mean croissant.” She is also an avid runner, having completed her first marathon last October and she plans to tackle the Taco Bell 50k this coming October. Professionally, she’ll complete her PhD and pursue a post-doctoral position.

Follow Trine’s journey and explore her work as she continues to make strides in the field of theoretical chemistry!

Check out her GitHub if you are interested in more of her work

Weiliang Luo’s interest in molecular science started early, sparked by a periodic table tucked into the back of a dictionary. What began as curiosity—wondering how matter is arranged and transformed—quickly deepened through hands-on exposure to simple experiments and vivid chemical reactions that felt almost magical.

Today, that curiosity drives his research at MIT, where he works at the intersection of quantum chemistry, machine learning, and scientific software. His primary focus is Enerzyme, a project centered on developing next-generation neural network potential (NNP) methods for enzymatic catalysis. The goal is to make AI-driven molecular simulations more accessible, robust, and scalable for complex biochemical systems. To do this, he combines modular, physics-inspired model design with large-scale quantum chemistry, transfer learning from biochemical data, and automated active learning workflows with uncertainty quantification.

Building Enerzyme has meant tackling both scientific and engineering challenges. Early versions of the framework were powerful but difficult to maintain, relying on fragile scripts and inefficient GPU usage. Through his MolSSI Software Fellowship, Weiliang worked with mentors—Drs. Benjamin Pritchard, Taylor Barnes, and Jessica Nash—to redesign the system from the ground up. By implementing best practices for multi-GPU PyTorch jobs on Slurm clusters and restructuring key workflows, he significantly improved performance and stability. He also reworked the NEB pipeline to better handle convergence issues, turning it into a more automated and reliable process.

These improvements went beyond speed. Standardizing data structures and configuration handling reduced user error and improved reproducibility, helping transform Enerzyme from a personal research tool into shared infrastructure used across his group.

The longer-term vision for Enerzyme is to become an open, extensible platform—accessible to experimental biochemists, flexible for developers, and aligned with rapid advances in atomistic machine learning. By accelerating simulations of enzyme catalysis, particularly in challenging systems like metalloenzymes, Weiliang hopes to enable new insights into complex biochemical processes. Ultimately, this work could support mechanistic studies, enzyme engineering for sustainable chemistry, and rational drug discovery.

The MolSSI fellowship has also given him the freedom to explore ambitious ideas while connecting with a broader community of computational scientists. These interactions have strengthened his interest in building software that is not only technically sound, but widely useful.

Looking ahead, he is open to paths in academia, industry, or startups, with a consistent goal: advancing molecular science through better computational tools. He is also motivated to mentor others as AI continues to reshape the field.

Outside the lab, Weiliang channels his creativity into the arts. He directs large-scale cultural performances and experiments with incorporating generative AI into storytelling and design. He also enjoys singing and arranging a cappella music, drawn to the same collaborative energy that defines his scientific work.

If you are interested in more of his work, please visit his GitHub and LinkedIn pages

• GitHub
• LinkedIn
• X

The Accelerating Curricular Transformation in the Computational Molecular Sciences (ACT-CMS) program is pleased to announce that the 2026 round of Faculty Fellowship applications is now open.

ACT-CMS is an education and faculty development program from MolSSI. The goal of ACT-CMS is to transform science curricula by accelerating the integration of programming and computation into existing molecular science courses through faculty training and the development of open and reusable curricular modules.

The Faculty Fellows Program is the cornerstone of ACT-CMS. A Faculty Fellowship lasts one years and is awarded to a molecular science educator developing curricula integrating programming and computation into existing science courses. Throughout the program, Faculty Fellows will receive curriculum development and assessment training and will upskill their programming and computational skills. They will produce a curriculum module that uses programming and computation to teach STEM concepts in an existing course that they teach. These modules will be open and reusable, allowing other educators to adopt them in their classrooms.

Applications for the next cohort of Faculty Fellows open in January 2026 and close on February 28, 2026. A Faculty Fellowship has the following benefits:

• $5000 support (stipend + travel funding) stipend each year of the fellowship.
• Mentorship from an ACT-CMS Programming and Computation Mentor and an ACT-CMS Curriculum Mentor.
• Annual meeting at MolSSI headquarters for training and networking.

Application Link: Click Here.

If you are interested in applying and have questions, please register for information session Here. The information session will be held on January 30, 2026, at 1:00 PM ET (10:00 AM PT)

For more information about the ACT-CMS Fellowship Program, please visit the ACT-CMS website.

The Molecular Sciences Software Institute (MolSSI) is proud to announce the release of a new Udemy course: C++ Project Management: CMake, CPack, and Beyond, created by MolSSI Software Scientist Taylor Barnes.

Becoming an expert C++ software engineer requires much more than writing code. Successful developers also need to navigate the complex world of compilers, build systems, package managers, containerization tools, and debuggers that power serious scientific software. This course provides a natural next step for students and researchers who know the basics of C++ and are ready to tackle real-world project management.

🎓 Upon completion, you’ll receive a shareable credential to highlight your training on LinkedIn or your CV.

Special Offer: Just $12.99!

Use coupon code C63D76238F8CA8A16BCF at checkout to get the course for only $12.99
👉 Enroll here: C++ Project Management: CMake, CPack, and Beyond

Offer valid until Oct 4, 2025.

What You’ll Learn

This hands-on course dives into the practical aspects of building, distributing, and maintaining C++ software:

• CMake: Configure builds, compile executables and libraries, and manage dependencies.
• CPack: Create distribution-ready packages for your projects.
• Debian packaging: Understand package structures and run your own test APT server.
• Debugging tools: Use sanitizers and language servers to improve project reliability.
• Container-native development: Explore Docker-based workflows that can streamline and modernize your development environment.

The course also addresses advanced CMake concepts such as variable substitution, scope handling, and creating packages that are easy for others to consume.

Course Format

All lessons are recorded inside a Docker development environment, with support for both Neovim and VSCode. This setup ensures participants can follow along step by step while experiencing the benefits of container-native development.

Who Should Enroll?

• Students with a basic foundation in C++ who want to take the next step.
• Developers interested in contributing to real-world scientific projects.
• Coders looking to create and distribute libraries for others to use.

Prerequisites: Basic familiarity with C++ (conditions, loops, simple classes) and some experience with Git are recommended.

Are you an early-career graduate student or researcher new to quantum chemistry and looking to expand your skillset? Have you ever attended a MolSSI training and wished you had a credential to show off on your professional profiles?

We have good news for you!

The Molecular Sciences Software Institute (MolSSI) has launched its first self-paced Udemy course: Introduction to Quantum Chemistry Simulation, taught by Dr. Taylor Barnes. This course introduces the core concepts of quantum chemistry simulation through practical, hands-on work with Psi4, a widely used open-source package for quantum chemistry. You can run calculations directly in Google Colab or set up a local installation, whichever fits your workflow.

🎓 Upon completion, you’ll receive a shareable credential to highlight your training on LinkedIn or your CV.

Special Offer: Just $12.99!

Use coupon code D8A475313E0A94E03FFB at checkout to get the course for only $12.99
👉 Enroll here: Introduction to Quantum Chemistry Simulation

Offer valid until May 17, 2025.

Who Should Take This Course:

• Undergraduate and first-year graduate students
• Researchers looking to break into quantum chemistry
• Anyone with a basic chemistry background (advanced high school level)
• No programming experience required!

Course Overview:

Learn how to use the laws of quantum mechanics to simulate the world at the molecular level.  We’ll be focusing on gas-phase quantum chemistry using Gaussian based wavefunction theory methods.  You’ll use Psi4, a popular open-source software package regularly used by professional researchers, to run simulations of small chemical systems.  Don’t worry if you’re not a math genius; this course avoids down-in-the-weeds mathematical analysis in favor of conceptual overviews and practical advice.  Anyone with basic chemistry familiarity (equivalent to an advanced high school course) will be able to start running interesting calculations on real-world systems by taking this course.

Course Highlights:

• Installation and usage of Psi4.
• The key choices that go into running a quantum simulation, such as method and basis set.
• The differences between popular wavefunction methods, such as Hartree-Fock theory and Coupled Cluster theory.
• How basis sets work.
• Basis set selection.
• Calculating energies.
• Defining molecular geometries using both Cartesian coordinates and Z-matrices.
• Running geometry optimizations.
• Dealing with Basis Set Superposition Error.
• A basic introduction to multiconfigurational methods.
• Calculating thermodynamic quantities, such as heat of formation.
• Evaluating excited states.

Early Steps in Computational Science

Dr. Carlos Bueno’s journey into computational biophysics started by helping his father to automate scheduling tasks in Excel. This early exposure to programming sparked a lasting interest, evolving into writing simple programs in Visual Basic, such as a titration calculator, where he found that “even simple chemical models hide multiple complexities”. His academic path then took him to Dr. Mirko Zimic’s bioinformatics lab in Peru, where he navigated at the interface between biology, chemistry, physics, and programming. Whether setting up computing clusters or diving into biophysical modeling for tuberculosis research and poultry vaccine development, Carlos’s work was deeply informed by the proximity and insights gained from Dr. Patricia Sheen’s experimental lab, whose lab benches were next to their computers. This closeness between the labs allowed him to bridge computational and experimental perspectives.

Building Open-Source Tools and Leadership

At Rice University, Carlos joined Professor Peter Wolynes’ group at the Center for Theoretical Biological Physics, focusing on mesoscale biophysical models of complex protein interactions. His research evolved through close collaborations with faculty across disciplines, including Dr. Margaret Cheung, Dr. M. Neal Waxham, Dr. José Onuchic, which enriched his perspective on both the biological relevance and computational demands of his work. Within this collaborative environment he faced the challenge of managing and developing software that organically developed in a fast-paced academic environment, such as multiple versions of the code coexisting without version control or insufficient documentation. This led him to the MolSSI best practices, a turning point in his approach to scientific software.

“The MolSSI best practices completely reshaped how I approached scientific software,” Carlos reflects. He began implementing version control, unit testing, continuous integration, and thorough documentation, contributing to the development of OpenAWSEM in collaboration with Dr. Nick Schafer and Dr. Wei Lu for protein modeling and Open3SPN2 for DNA simulations in OpenMM.

The MolSSI Software Fellowship, alongside the mentorship of Dr. Jessica Nash, proved instrumental in Carlos’s growth as a software leader. He states, “Working with Jessica has helped me tackle problems leading open-source collaborative software projects with large teams, collaborating effectively with the bigger scientific computing ecosystem, and adopting more effective coding styles and design patterns to ensure our software tools can be easily adapted to tackle a vast range of problems.” This guidance, combined with insights from other mentors like Levi, who emphasized long-term software design, solidified his confidence in leading projects, particularly in prioritizing requirements and refining communication.

Carlos highlights specific areas where Jessica’s mentorship was invaluable: “Her feedback has helped me think more deliberately about design patterns and how to structure codebases, so they are easier to extend and maintain. She has also introduced me to valuable resources and best practices that I now apply regularly in my projects for testing and benchmarking. We have also had discussions about licensing, community contributions, and interoperability with other tools like MDTraj, and MDAnalysis. She has help us to develop new methods and interfaces for the Frustratometer project, making it more flexible and accessible.”

A Vision for Science and Mentorship

Carlos’s vision extends beyond immediate projects. He aims to remain at the intersection of theory and experiment, bridging biology, chemistry, and physics through computational modeling. His immediate goal is to expand the AWSEM ecosystem into a robust, well-documented platform for future collaborators.

Beyond his research, Carlos is passionate about mentorship and science education, contributing to programs like Science Clubs Peru, iGEM, the Serendipity Program, and the Frontiers in Science Program. He is particularly proud of his open-source contributions, OpenAWSEM and Open3SPN2, which are now being used and extended by others.

Above all, Carlos finds joy in spending time with his son, seeing the world through his eyes and reminding himself of the constant learning and growth that defines human experience.

If you are interested in more of his work, please check his GitHub , LinkedIn, or personal website.