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Problem-Solving for Tomorrow: MITS Alumni at the Forefront of Technological Innovation

As technological change accelerates, organizations increasingly rely on those who can solve complex problems in the face of the unknown. In their coursework, students in the Master in Information Technology Strategy (MITS) program at ºÃÉ«ÏÈÉúTV (CMU) learn about not only the latest technologies but also how these technologies influence people and institutions. Highlighting this holistic approach to coursework and the opportunity to develop technical judgment through a capstone project, three MITS alumni share how their experiences at ºÃÉ«ÏÈÉúTV are helping them navigate today’s dynamic technological landscape. 

Administered by the Carnegie Mellon Institute for Strategy & Technology (CMIST), and in partnership with the and the , the MITS program provides a high-level strategic framework at the intersection of cybersecurity, data analytics, and systematic implementation, all as students pursue an area of specialization. While MITS students typically arrive at ºÃÉ«ÏÈÉúTV with well-defined interests, their classes help them broaden and refine their interests by showing how different pieces fit together and bridging the gap between theory and practice. 

For example, Cristin Connerney, who graduated in 2022 and currently works on machine learning infrastructure at Audible, entered the MITS program focused on machine learning and data science. Her goal was to understand the theory behind machine learning and to learn how to build the systems that translate ideas into functioning technologies. Coursework in distributed systems, robotics, and application development allowed her to see where machine learning fits within a larger technical ecosystem and prompted her to focus on problem-solving methodology, rather than any single tool or technique. “Once you understand how to approach a hard problem, breaking it down, testing assumptions, and iterating, that same process applies across different domains,” Connerney said. 

Pablo Marín Vicuña, who graduated in 2024 and works as an AI research and development manager at Banco Falabella in Santiago, Chile, had a similar experience. Entering the MITS program with a background in data science and machine learning, Marín Vicuña focused on software engineering, privacy, and technology strategy throughout his time at Carnegie Mellon. He found that his coursework gave him a more complete understanding of how machine learning models fit into broader software systems, which clarified the space he wanted to operate in. Faced with the “happy problem” of more interesting courses than time, he prioritized completing the foundational courses in the first semester in order to develop a clearer understanding of systems and their constraints. He then shifted to an intentional exploration phase in the second semester of coursework in order to focus on Generative AI, DevOps, and Machine Learning in Production. “After the program, I became more fluent not only in bridging technical and non-technical teams, but also in connecting different technical disciplines,” Marín Vicuña said, noting that the progression of coursework had a direct professional impact. “This broader technical range has allowed me to help align teams, anticipate integration challenges, and contribute more effectively to complex, real-world systems,” he said. 

Courses in the MITS program offer multiple opportunities for students to develop effective approaches to open-ended problems. From implementing core machine learning algorithms from scratch to using a neural network to build an image classification model, Connerney dedicated her time at ºÃÉ«ÏÈÉúTV to putting theory into practice. “Software is a field where what you’re building often feels entirely new,” she said, adding that “over time, the unfamiliar becomes manageable, and the hard problems become solvable.” Connerney also highlighted how coursework can lead to lasting insights and exciting opportunities within CMU. For example, a course on robotics and ethics taught by , Kavcic-Moura Professor of Robotics, shaped Connerney’s understanding about how new technologies are introduced, adopted, and experienced, ultimately inspiring her to pursue a position in the Community Robotics Education and Technology Empowerment (CREATE) Lab. “That experience reinforced the idea that technical work can be both rigorous and deeply human-centered,” she said. 

Yifan Luo, who graduated from MITS in 2024 and now works as a data analyst at Kinertia in Pittsburgh, appreciated her coursework’s emphasis on building end-to-end projects. Rather than following a highly-structured path to a final answer, she noted that the learning process was iterative, requiring her to figure out which questions to ask and to determine the direction to take. During her job search, Luo drew on those experiences to communicate concretely about how she approaches open-ended problems. “In my current role, that way of thinking carries over into how I experiment, make tradeoffs, and work with data as part of a larger system,” she said. 

The opportunity to tackle open-ended problems culminates in a capstone project, in which groups of students partner with a company, nonprofit, or educational organization for a period of twelve to fourteen weeks to test workable solutions to a strategic problem. Connerney, whose capstone experience as part of a small, cross-functional team included building an app for ProCogia, views the project as a valuable “chance to develop technical judgment,” in which students practice deciding what matters, how to allocate their time, and how to balance tradeoffs in the absence of a single, “right” answer. “Those skills compound over time, and the capstone is a rare chance to exercise them in a setting that is both supported and realistic,” she said, adding that the project required her team to navigate ambiguity and align technical choices with business goals. While leading a roundtable event for current MITS students last fall, Connerney also highlighted how diversity within the capstone team can give students the opportunity to meaningfully increase their skillsets, noting that some of the skills she uses today were first forged while collaborating with software specialists.

“The capstone is where the program truly comes together,” shared Marín Vicuña, whose group worked with a research team led by Kathleen Carley, a professor in the School of Computer Science’s Institute for Software Research and the director of the Center for Informed Democracy and Social Cybersecurity (IDeaS), to analyze Telegram conversations related to the Russia-Ukraine war. The experience helped him consolidate what he had learned over the course of the program and apply that knowledge in a realistic setting. “It provides the space to go deep on a real problem, integrate technical and conceptual skills, and learn how to produce work that is meaningful to domain experts—not just technically correct,” he observed. 

According to Luo, the capstone experience “reflected the nature of real client work, where ambiguity and evolving goals are common.” Under the guidance of Vincent Sha, associate dean of information technology and operations for the Dietrich College of Humanities and Social Sciences, her team worked on a project exploring how large language models (LLMs) can transform the educational experience, including through simulation-based learning. “The capstone felt like a realistic simulation of a job—working with a team on a real problem, but with more space to experiment, make mistakes, and learn from them,” Luo said. The experience underscored how the capstone project allows students to refine skills that will serve them well throughout their careers, including navigating uncertainty as a team, communicating clearly, and delivering a meaningful result. 

Whether at a start-up or a large company, MITS alumni find that the skills they build at ºÃÉ«ÏÈÉúTV serve them well in the professional world. As he was finishing the program, Marín Vicuña knew that he wanted a role that utilized both his technical and non-technical strengths and allowed him to stay close to the problems being solved. In his new AI research and development role at Banco Falabella, Marín Vicuña enjoys hands-on work, exposure to non-standard problems, and the ability to contribute to how teams think about and use artificial intelligence. Simultaneously, he continues to lead as chief technology officer and co-founder of a personalized skincare startup in Chile—a venture he launched while at Carnegie Mellon. These two paths, he finds, are perfectly complementary. “One allows me to shape how a large organization evaluates and implements AI, while the other keeps me deeply hands-on, building and iterating within a small, fast-moving environment,” he said.

Prior to her current role at Audible, Connerney worked as a founding engineer at Instalily which at the time was an early-stage startup. When one of Instalily’s largest clients was acquired by Home Depot in an $18 billion deal, Connerney had the chance to meet Home Depot CEO Ted Decker, a fellow Carnegie Mellon alumnus. She recounted how, after praising the work she had done, he paused and asked, “Did you go to CMU?”—a powerful reminder of the reach and reputation of Carnegie Mellon.

Whatever their career trajectory, MITS graduates are prepared to respond to challenges while thinking holistically about the impact of technological innovation on various industries and society. In order to successfully apply technology to interesting and meaningful problems, Luo emphasizes the value of the iterative process of experimentation and the importance of learning to ask the right questions. Marin Vicuña anchors his approach in his commitment to continuous learning and practical engagement, driven by a primary motivation to build, improve, and connect ideas across domains. Expressing excitement about future opportunities to influence technical direction and mentor others, Connerney remains focused on the bigger picture. “I’m most motivated by solving interesting problems and building things that have a positive impact,” she said, adding that this is “a perspective that was shaped and reinforced during my time at ºÃÉ«ÏÈÉúTV.”

(Image 1, on left: Cristin Connerney at the Data Connect Conference 2024, where she gave a talk titled "AI in Production," pictured with Iris Cheng, an early Instalily.ai engineer; on right: While at Instalily, Connerney started the "Women in AI" Network with other early female engineers and is pictured hosting the "Women in AI Coffee & Breakfast SF Tech Week 2024"; Image 2: Yifan Luo works on her MITS capstone project exploring how large language models (LLMs) transform education; Image 3, on left:  Pablo Marín Vicuña currently works as an AI research and development manager at Banco Falabella; on right: Marín Vicuña presenting his CMU capstone)