Big ideas don鈥檛 wait 鈥� and neither do the researchers behind them.

The 2026 Reach for the Stars honorees 鈥� six 麻豆原创 assistant professors 鈥� are already making a substantial impact on their respective fields through meaningful research and creative work that extends far beyond campus, with national and international influence.

Across disciplines, their work and research reflect a shared mission to advance ideas into impact 鈥� uncovering what shapes ethical decision-making in the workplace; exploring the origins of our solar system; developing computational solutions to meet future energy demands; designing more intuitive and reliable software experiences; strengthening education for students with disabilities; and engineering faster, more energy-efficient artificial intelligence (AI) systems.

Together, this brilliant group represents the kind of bold, forward-thinking innovation 麻豆原创 continues to champion.

Each year, the Reach for the Stars awards recognize early-career faculty opening new doors for what鈥檚 possible across their fields. The prestigious award is second only to Pegasus Professor as 麻豆原创鈥檚 highest faculty honor.

In recognition of their achievements, each honoree will receive a $10,000 annual research grant for three years in addition to the distinction of being an award recipient.

The 麻豆原创 community is cordially invited to come and congratulate the recipients from 3-5 p.m. Wednesday, April 1, in the Pegasus Ballroom at the Student Union as part of the 2026 Founders鈥� Day Faculty Honors Celebration.

This year鈥檚 Reach for the Stars honorees are:

John Bush

Assistant professor of management in the College of Business

What鈥檚 something few people know about you?

Working at 麻豆原创 is a homecoming for me. Growing up in Florida, I had the opportunity to experience all the great things this state and its universities have to offer. And while my younger self might not have predicted I’d end up in Black & Gold, 麻豆原创 and Orlando have been incredible homes.

What does your research focus on?

I study when, why, and how employees cross ethical lines, and what role leaders, management policies, and organizational systems play in those decisions. A big part of what makes my work unique is that I focus on an important puzzle: how things we typically think of as “good” can promote unethical behavior. We tend to assume that well-intentioned management practices will always lead to good outcomes. However, my research shows that’s not always the case, and the unintended consequences can be significant.

What drives you to take on this challenge?

Before I entered academia, I worked in corporate finance and accounting. That experience meaningfully shaped how I think about ethics in organizations.

There’s a common assumption that unethical behavior is a 鈥渂ad apple鈥� problem, or rather, that it comes down to an individual’s character or integrity. But as my work has shown, it’s often a 鈥渂ad barrel鈥� problem. The environments organizations create, the systems they put in place and the ways managers approach leadership profoundly influence how people behave.

What makes 麻豆原创 the right place for you to do this kind of work?

I’m a firm believer that the people make the place 鈥� and the faculty, staff and students of 麻豆原创 are truly what make it such a great place to be. The College of Business has a management department full of colleagues who are both excellent scholars and genuinely collaborative people.

What鈥檚 next for you or your research?

I’m excited about several new directions, each of which builds upon my existing work. I’m particularly interested in examining more nuanced, less studied drivers of ethical decision-making. For example, what happens when someone becomes an accidental witness to unethical behavior? How does that experience shape what they do next and the moral burden that鈥檚 placed on them?

Ana Carolina de Souza-Feliciano

Assistant professor at the

What鈥檚 something few people know about you?

While many people know I鈥檓 not afraid to face challenges, few know that I鈥檓 afraid of roller coasters.

What does your research focus on?

I study the small bodies of our solar system (objects such as asteroids, Trojans and trans-Neptunian objects) from an observational perspective to try to understand how our planetary system formed and evolved. The small bodies that remain from the early solar system still preserve clues about the materials and conditions that existed when planets formed. By observing their surfaces, compositions and physical properties, we can piece together the history of how the solar system came to be.

What drives you to take on this challenge?

The solar system still holds many unanswered questions, and every observation has the potential to reveal something completely new about its history. I鈥檓 especially motivated by the idea that these small and distant objects preserve a record of the earliest stages of planetary formation, and since we still don鈥檛 know much about them, we need to better characterize these groups to have a chance of getting closer to important scientific answers.

What makes 麻豆原创 the right place for you to do this kind of work?

麻豆原创 provides a dynamic research environment with strong collaborations and access to facilities that help me achieve my scientific goals.

What鈥檚 next for you or your research?

I aim to expand my research group and continue developing new projects exploring the composition and physical properties of small bodies in the outer solar system.

Shyam Kattel

Assistant professor of physics in the College of Sciences

What鈥檚 something few people know about you?

I enjoy long, quiet walks or runs. It鈥檚 when I do my best thinking and come up with new ideas for teaching and research.

What does your research focus on?

My research group is interested in understanding chemical processes through computer simulations. These chemical processes are central to many energy and fuel generation and energy conversion processes. We are exploring the design of catalytic materials that selectively convert abundant small molecules, such as CO2, N2, NO3, O2 and H2O, to a wide variety of synthetic chemicals and fuels in a carbon-neutral way to fulfill the growing energy demand of the future.

What drives you to take on this challenge?

I鈥檓 a huge advocate of sustainability. I鈥檓 fascinated by the rapid development and advancement of modern computers, machine learning (ML) and AI, which have enabled us to understand complex science on a time scale that鈥檚 impossible with traditional trial and error methods. This unique opportunity to utilize supercomputers with ML and AI to tackle energy and sustainability challenges keeps me awake at night.

What makes 麻豆原创 the right place for you to do this kind of work?

By training, I鈥檓 a physicist, but my research focuses on looking into chemical reactions. 麻豆原创鈥檚 physics department is among a handful of institutions in the U.S. with a very strong catalysis program. This allows me to collaborate within the department and teach a physics course, which I enjoy. Additionally, the university鈥檚 large size and research facilities present opportunities to recruit the best students and to collaborate both within and beyond the department.

What鈥檚 next for you or your research?

My lab is developing capabilities to integrate ML and AI into our methods for understanding structure-materials property relationships across a large set of materials, driving the development of the next generation of clean and sustainable energy and fuel generation technologies. Our goal is to develop an integrated materials design framework that anyone can use for their research and for teaching research-based undergraduate and graduate courses.

Kevin Moran

Assistant professor of computer science in the College of Engineering and Computer Science, director of the Software Automation, Generation and Engineering Research Lab and affiliate of the Cyber Security and Privacy faculty cluster initiative

What鈥檚 something few people know about you?

I was a Division 1 rower as an undergraduate at the College of the Holy Cross. Our team competed in the national championship regatta my senior year and was ranked among the top 20 teams in the country.

What does your research focus on?

If you鈥檝e ever been frustrated by glitches in apps or websites, my students, collaborators and I aim to give engineers the tools they need to build more reliable software. My group has pioneered work in user interface engineering, focusing on user-facing systems and making software easier to use.

What drives you to take on this challenge?

Since I was young, I鈥檝e enjoyed building things, taking them apart and understanding how they work. I view software as the ultimate engineering medium, where abstract ideas can quickly become reality. What excites me most is tackling the complexity of modern software systems by developing tools that engineers can easily adopt. Seeing those tools save engineers hours or days of time is truly fun.

What makes 麻豆原创 the right place for you to do this kind of work?

麻豆原创 has been an excellent place to grow as an early-career researcher. I鈥檝e received invaluable mentorship from department and college leadership, as well as senior faculty. The university鈥檚 connection to the local tech industry is also exciting, and I look forward to forming connections with local companies to put our tools into practice.

What鈥檚 next for you or your research?

Software engineering is rapidly shifting toward agentic workflows, where AI-powered agents perform engineering tasks autonomously. While this increases speed, it also introduces complex errors that are harder to spot. My lab aims to understand these software engineering agents, improve their reliability and create tools that help developers use them effectively.

Soyoung Park

Assistant professor of teacher education in the College of Community Innovation and Education (CCIE)

What鈥檚 something few people know about you?

When I travel for conferences, I love to explore local bookstores and cafes.

What does your research focus on?

My research focuses on transforming educator preparation to better support students with disabilities. Supported by more than $3.75 million in U.S. Department of Education funding, my work prepares special education teachers, speech-language pathologists and school psychologists to serve students with autism spectrum disorders and high-intensity needs. I also develop evidence-based mathematics interventions for students with learning disabilities.

What drives you to take on this challenge?

Mathematics remains an area where both research and practice need stronger alignment. Teachers need accessible, evidence-based guidance on how to teach effectively, but it isn鈥檛 always easy to find or interpret. Students need consistent access to high-quality instruction that meets their individual needs. I鈥檓 interested in helping bridge that gap so that research can better support educators and the students they serve.

What makes 麻豆原创 the right place for you to do this kind of work?

麻豆原创鈥檚 strong infrastructure for research and collaboration further amplifies my work. Support from the Office of Research has been instrumental in advancing my research development, grant capacity and interdisciplinary collaboration. As a CCIE research fellow and affiliated faculty member at the Toni Jennings Exceptional Education Institute, I have valuable opportunities to engage in interdisciplinary collaboration across colleges.

What鈥檚 next for you or your research?

Our next project focuses on synthesizing large data sets to help educators identify mathematics interventions that align with their students鈥� needs. We鈥檙e also exploring how AI can support this process through pedagogical AI chatbots and interactive web-based platforms that guide educators in interpreting and applying research evidence in practice. Ultimately, this work aims to strengthen both instruction and student outcomes at scale.

Hao Zheng

Assistant professor of electrical and computer engineering in the College of Engineering and Computer Science

What鈥檚 something few people know about you?

I enjoy traveling, especially visiting national parks and exploring new cities. Each trip helps me recharge, and I often come back with fresh perspectives and new ideas.

What does your research focus on?

My research focuses on making today鈥檚 AI systems faster, more energy-efficient and more reliable by bridging the gap between algorithms and hardware. AI has reshaped daily life, but behind the scenes, modern AI models require enormous amounts of computation and energy. My work explores new ways to co-design hardware and software so AI can run efficiently, especially for irregular or sparse data structures, such as graphs.

What drives you to take on this challenge?

I鈥檓 driven by both the importance and the difficulty of the problem. We鈥檙e at the turning point of rethinking future computing systems. Defining a new computing paradigm, despite its challenges, can have a far-reaching impact across society. Our research can fundamentally reshape how future computers are designed and how AI is deployed at scale.

What makes 麻豆原创 the right place for you to do this kind of work?

麻豆原创 is an ideal place to pursue bold research ideas, supported by strong momentum in engineering, computing and interdisciplinary collaboration. The university also offers an exceptional and supportive community of mentors and collaborators, including students, who set a high bar for excellence. I鈥檝e been fortunate to work with many outstanding colleagues, and those experiences have shaped how I think about building a high-impact research program and growing as a scholar.

What鈥檚 next for you or your research?

Next, we鈥檙e expanding our work toward real-world deployments, including applications in healthcare and robotics. We鈥檙e also continuing to strengthen our research in building processors for AI and scientific computing so that our ideas can translate into improvements in performance and energy efficiency.

But that may change in the future through the efforts of a 麻豆原创 researcher. Dazhong Wu, an associate professor of mechanical and aerospace engineering, has received a Young Faculty Award from the Defense Advanced Research Projects Agency (DARPA) for his project titled 鈥�Artificial Intelligence-Enabled Affordable and Scalable Additive Manufacturing Part Qualification.鈥� The award will include nearly $500,000 of funding for the two-year project with an optional $500,000 for a third year of work, depending on how the research progresses.

The goal of the project is to develop an efficient and cost-effective machine learning model that can predict the defects and mechanical performance of 3D printed materials. Current metal additive manufacturing processes use expensive materials, such as titanium alloys, to build complex, high-performance parts layer-by-layer from digital models. Those parts undergo lengthy trial-and-error testing cycles that result in the destruction of parts and an overall loss of money.

With Wu鈥檚 novel method that mixes AI with additive manufacturing, the industry can move away from destructive testing and reduce inspection costs.

鈥淯sing AI we can predict the mechanical performance of 3D printed parts with small amounts of destructive and non-destructive testing data. With this, we can ensure every part is consistent, reliable and less costly.鈥�

Once Wu鈥檚 AI model is built, he hopes it can be implemented in various industries to transform how they manufacture critical components.

鈥淚鈥檓 hopeful this AI-enabled additive manufacturing qualification framework will be used across many industries, including aerospace and, many more,鈥� Wu says. 鈥淏ringing costs down is crucial to the additive manufacturing industry. To do that, we need to make sure every part consistently meets performance requirements.鈥�

About the Researcher

Wu joined 麻豆原创in 2017 after serving as a senior research associate at Penn State University鈥檚 Department of Industrial and Manufacturing Engineering. In 2021, the Society of Manufacturing Engineers ranked him among the 20 most influential academics in additive manufacturing. In the College of Engineering and Computer Science, he manages the Additive Manufacturing and Intelligent Systems Lab, where he and his team develop smart manufacturing techniques.

The project depicted is sponsored by the Defense Advanced Research Projects Agency. The content of this article does not necessarily reflect the position or policy of the government and no official endorsement should be inferred.

Supported by a gift from Meta, the two-year project uses electromyographic (EMG)-based human-machine interface technology as a platform for investigating motor learning through gamified training systems. While EMG systems are often studied in the context of prosthetic limb control, the broader goal of the project is to understand how adaptive interfaces can become more intuitive and embodied over time.

鈥淭his Meta support will enable my lab to work on real-world problems that can have an immediate impact on neurotechnologies.鈥� 鈥� Mohsen Rakhshan, assistant professor

麻豆原创 was selected through Meta鈥檚 competitive funding initiative, in part because of its interdisciplinary approach pairing engineering with philosophy and ethics.

Mohsen Rakhshan, an assistant professor in 麻豆原创鈥檚 Department of Electrical and Computer Engineering and the Disability, Aging and Technology (DAT) faculty cluster initiative, and Jonathan Beever, a professor of philosophy and director of the 麻豆原创 Center for Ethics, will lead the project.

鈥淭his Meta support will enable my lab to work on real-world problems that can have an immediate impact on neurotechnologies,鈥� Rakhshan says. 鈥淭he impact ranges from individuals using augmented and virtual reality for entertainment to individuals with amputation or paralysis seeking to improve their quality of life. It also gives my engineering students the opportunity to integrate ethics research into their technical work.鈥�

Advancing Motor Learning Through EMG

EMG-based interfaces translate electrical signals generated by muscle activity into digital commands, allowing users to control devices through subtle physical gestures. In immersive environments, these systems can enable more natural interaction with virtual objects. In rehabilitation settings, they can assist in training neural prostheses.

The 麻豆原创 team is using this technology to examine how people learn new motor skills in digital environments, particularly through gamified interaction tasks designed to strengthen human-computer coordination. By training both the participant and the signal-processing algorithm (often called a 鈥渄ecoder鈥�) simultaneously, through a process known as co-adaptation, researchers aim to create systems that improve alongside the user.

鈥淎 significant challenge for most of these systems is that they require constant retraining or calibration of the decoder,鈥� Rakhshan says. 鈥淩etraining after each use can discourage individuals from using these devices long term. The human nervous system is plastic 鈥� it can adapt and improve performance over time. But if the decoder is constantly reset or kept static, it may prevent the nervous system from leveraging that plasticity. We aim to develop a co-adaptive loop between the human and the device.鈥�

Rather than focusing solely on stable decoding, the project investigates how adaptive systems can enhance motor learning, improve user confidence and promote a stronger sense of embodiment in human-machine interaction.

If successful, the research could inform next-generation EMG systems used in immersive computing, rehabilitation technologies and assistive devices.

Embedding Ethics Into Engineering

A defining feature of the project is the integration of ethics alongside engineering from the outset.

鈥淚nterdisciplinary collaboration between ethics and technical experts is the best path forward for responsible innovation.鈥� 鈥� Jonathan Beever, professor

Longitudinal EMG studies can reveal subtle motor signatures that uniquely identify individuals, raising questions about privacy and data protection. Adaptive systems may also influence a user鈥檚 sense of agency, whether individuals feel genuinely in control of the interface. For example, if an EMG system begins adjusting its interpretation of muscle signals automatically, users may feel the device is responding to them intuitively or, in some cases, acting unpredictably. Researchers want to better understand how these dynamics affect trust, confidence, and long-term use.

To address these questions, Beever will be embedded within the 麻豆原创 Laboratory for Interaction of Machine and Brain (LIMB), contributing directly to experimental design and evaluation. The team will conduct structured assessments of agency and embodiment while examining potential privacy leakage from EMG signal data.

鈥淚nterdisciplinary collaboration between ethics and technical experts is the best path forward for responsible innovation,鈥� Beever says. 鈥淭echnological advancement must be guided toward good ends. Our work emphasizes not only ethical research practices but also deeper questions about autonomy and agency in human-machine interfaces.鈥�

A Three-Phase Study

The longitudinal study will involve 30 participants completing 10 sessions over two months, allowing researchers to measure both short-term and long-term motor learning outcomes.

The project will occur in three phases:

Phase 1: Standardizing muscle signal data so artificial intelligence systems can more accurately interpret user intent.

Phase 2: Training both participants and machine learning models simultaneously 鈥� a co-adaptive process designed to improve human-computer interaction through gamified tasks.

Phase 3: Conducting structured evaluation of agency, embodiment and privacy risks while developing a publishable ethics framework for adaptive EMG-based systems.

鈥淭here has been a significant increase in industry interest in using biological signals such as EMG, from muscles, and EEG, from the brain, to interact with virtual and augmented reality, consumer electronics, prostheses for individuals with amputation and robotic systems for individuals with paralysis,鈥� Rakhshan says.

This research is supported by a gift from Meta. The project is conducted by faculty, staff and students in 麻豆原创鈥檚 Department of Electrical and Computer Engineering, the Disability, Aging and Technology research cluster and the 麻豆原创 Center for Ethics.

麻豆原创鈥檚 texts and technology program has received a 2026 grant from the National Endowment for the Humanities (NEH) to launch 鈥淏uilding a Digital Humanities Generative AI Learning Community,鈥� a 24-month initiative designed to help faculty and graduate students thoughtfully integrate AI into humanities teaching.

This year, 麻豆原创 is leading one of only 84 projects funded by the NEH and is the only institution in Florida to be selected for the award.

Associate Professor and Professor will lead the initiative, which focuses on interdisciplinary collaboration, curriculum redesign and hands-on experimentation with emerging AI tools.

Coding for Creativity

Salter, director of graduate programs in the College of Arts and Humanities, says the project builds on a long tradition in digital humanities of teaching creative problem-solving through technology.

鈥淚n a lot of humanities programs, when we teach people how to build digital projects, we鈥檙e teaching them some level of code,鈥� Salter says. 鈥淏ut often we鈥檙e working with low-code tools 鈥� interfaces designed for a specific purpose, like building a certain kind of game. Once students learn how to navigate those tools, what really matters is their ideas, the design, the story they want to tell.鈥�

She explains that generative AI tools function in a similar way. Rather than replacing creativity, they can expand it.

鈥淲hen we look at agentic AI, it鈥檚 essentially a low-code computational interface,鈥� Salter says. 鈥淭he better you can define and plan a concept, the more the system can assist with the underlying technical work 鈥� especially in the creative applications.鈥�

Reimagining Humanities Work

Stanfill says the grant will fund course redesign efforts over the next two years. Faculty and graduate student participants will adapt existing undergraduate digital humanities courses to meaningfully incorporate AI in ways that align with humanistic expertise. Stanfill鈥檚 scholarship has recently received national recognition. In 2025, they were awarded the National Communication Association’s Diamond Anniversary Book Award for their book 鈥淔andom Is Ugly: Networked Harassment in Participatory Culture鈥�.

鈥淚t鈥檚 about integrating AI in a way that makes sense for each course and for what humanities already bring to the table,鈥� Stanfill says. 鈥淭he goal is to enhance 鈥� not replace 鈥� the core strengths of humanities scholarship.鈥�

The funding will also support stipends that allow participants in the program to experiment with advanced AI tools that are expensive to access.

鈥淭hey are more cost-intensive,鈥� Salter says. 鈥淧art of what this grant allows us to do is give students real access 鈥� not just a limited sandbox version 鈥� so they can fully understand what these tools can do.鈥�

The implications extend to areas such as archival transcription and preservation. Advances in handwriting recognition and large-scale document analysis could help students work with under-digitized collections in new ways.

鈥淚f you can bring a class into an archive that鈥檚 been underappreciated and use these tools, you can build searchable databases and identify patterns in ways that used to require years of manual labor,鈥� Salter says.

The grant strengthens 麻豆原创鈥檚 position as a leader in digital humanities education, the researchers say. By fostering collaboration across disciplines and encouraging thoughtful AI integration, the texts and technology program aims to model how humanities scholarship can evolve alongside technological innovation.

The 鈥淏uilding a Digital Humanities Generative AI Learning Community鈥� 聽project has been made possible in part by a major grant from the National Endowment for the Humanities: Democracy demands wisdom. Any views, findings, conclusions, or recommendations expressed in this publication do not necessarily represent those of the National Endowment for the Humanities.

For computer engineering major Kamalakkannan Ravi 鈥�20MSCpE 鈥�25PhD, the goal was never to just earn a doctorate 鈥� it was to build artificial intelligence (AI) systems people could trust in the moments that matter most.

That bold vision found its momentum at 麻豆原创. As a student, Ravi was drawn to a university that encouraged big questions and interdisciplinary thinking, along with strong engineering fundamentals 鈥� the kind 麻豆原创 is rapidly becoming known for as a rising force in engineering and technology. The university鈥檚 dynamic research environment gave him the freedom to explore where machine learning, biomedical applications and human-centered AI converge, while mentorship in the Department of Electrical and Computer Engineering helped sharpen his purpose.

Now, he鈥檚 carrying that 麻豆原创-driven determination to Harvard Medical School and Boston Children鈥檚 Hospital, where he鈥檒l begin a research fellowship with the Division of Genetics and Genomics to advance trustworthy AI for clinical decision-making in healthcare.

At Harvard, Ravi will work on a project that aims to help physicians identify rare diseases earlier and respond more quickly. His research focuses on developing and evaluating clinical decision support tools that analyze electronic health record data and natural language processing to detect patterns that may signal a rare condition. These tools are designed to support clinicians in identifying patients who may benefit from further genetic evaluation, testing or a specialist referral. Ravi鈥檚 role centers on creating trustworthy, transparent AI methods that align with clinical systems, helping ensure these technologies are used responsibly in real-world healthcare.

Overcoming Obstacles Without a Blueprint

Ravi鈥檚 path to this opportunity was shaped by his persistence and commitment to making an impact long before he arrived at 麻豆原创.

Originally from Chennai, India, he鈥檚 a first-generation college student who entered higher education without a family blueprint to guide him. That experience influenced how he navigated graduate school and advanced research environments, reinforcing the importance of mentorship, community and resilience.

After earning a bachelor鈥檚 degree in biomedical engineering from Anna University, Ravi worked as a research assistant at the Indian Institute of Technology Madras. There, he gained early exposure to data-driven modeling and applied systems research at the intersection of engineering and medicine 鈥� experiences that shaped his interest in applying computational methods to biomedical and societal challenges. He鈥檇 take this interest on his pursuit of graduate education abroad.

Finding Interdisciplinary Opportunity at 麻豆原创

Ravi chose 麻豆原创 specifically for its strength in engineering combined with opportunities for interdisciplinary, human-centered research.

Within the Department of Electrical and Computer Engineering, he found an environment that encouraged him to explore machine learning, biomedical applications and ethical AI.

Under the mentorship of Pegasus Professor Jiann-Shiun Yuan, who oversees the NSF-sponsored Multi-functional Integrated System Technology Center聽and specializes in developing the next generation of smart systems, Ravi refined his research, which bridges technical innovation with societal impact.

At 麻豆原创, Ravi鈥檚 research focused on trustworthy and comprehensible AI in critical settings, including healthcare and public safety. His dissertation, 鈥淎rtificial Intelligence for Social Wellness: Threats and Ideology Detection in Online Texts,鈥� examined how scalable and ethically grounded AI systems can be designed for real-world applications. His work emphasized interpretability, reliability and evaluation with human decision-makers in mind.

His doctoral work led to the development of several datasets and frameworks, including:

• RICo, a large-scale dataset analyzing ideological discourse in online communities
• ALERT, a threat detection framework that combines active learning with AI to support transparency and reduce labeling burden
• TRuST-M, a human-subject study exploring how explanation quality affects user trust in AI-assisted moderation systems.

Portions of this work were supported by the U.S. Department of Homeland Security 鈥� a testament to its national relevance and real-world value.

Growing Through Leadership, Mentorship and Community

Beyond his studies, Ravi immersed himself in the 麻豆原创 graduate community, taking on leadership roles that reflected his commitment to service and mentorship.

He served as senator for the in student government, director of professional development for the Graduate Student Association and president of the . He also led Alpha Alpha Alpha, the national honor society for first-generation college students, advocating for the success of first-generation graduate students.

Mentorship remained central to his experience through his involvement in the NSF-funded L.E.A.R.N. (Learning Environment and Academic Research Network) program, a STEM-focused living-learning community for first-year and transfer college students, and his service as a senior design project judge.

Ravi鈥檚 academic excellence, leadership and mentorship at 麻豆原创 were recognized through multiple awards, including the ORCGS Doctoral Fellowship, the Graduate Presentation Fellowship, the Graduate Research Mentor Award, the 麻豆原创 Alumni Fellows Leadership Scholarship and the Reuel Buchanan Aspire to Inspire Scholarship. These honors provided valuable support and enabled him to focus on research throughout his doctoral studies.

Advancing Impact Beyond 麻豆原创

As Ravi prepares to begin his fellowship at Harvard Medical School, he credits 麻豆原创 with shaping both his research approach and his sense of responsibility as a scholar. He hopes his journey encourages other students, especially first-generation scholars, to pursue ambitious, interdisciplinary work while remaining grounded in mentorship, ethics and service to the broader community.

Brian Creel, associate director for career planning at 麻豆原创 Career Services, leads the career planning team in providing career counseling and assessment, career education and employment readiness skills.

鈥淏e ready to talk about your professional self through storytelling, and overprepare through deep research on the employer.鈥� 鈥� Brian Creel, Associate Director at 麻豆原创 Career Services

鈥淒on鈥檛 forget that employers want to get to know the real you. Be authentic,鈥� Creel says. 鈥淏e ready to talk about your professional self through storytelling, and overprepare through deep research on the employer. Find your spots to showcase your knowledge.鈥�

Creel shares his advice on every stage of the job interview process as the 麻豆原创 community prepares for its spring semester Internship and Career Expo. The event, which will be held on March 10 at Addition Financial Arena, features more than 250 companies across a variety of industries from diverse fields including technology, finance, healthcare, engineering and more.

How can you make a strong impression on your job interview?

• Know your professional story/prepare your elevator pitch
• Offer a confident greeting, handshake and smile
• Think about two to three key selling points about your professional self. For 麻豆原创 students, start with your major/expected graduation and talk about related skills/experience including student clubs and class projects
• Research employers and showcase your knowledge in conversation
• Give examples to back up your answers. Storytelling is a big part of the interview experience.

You mentioned an elevator pitch. What is your method for crafting one?

Your elevator pitch introduces you to recruiters in 30-60 seconds. Follow the present-past-future format:

• Present: What are you currently studying? What鈥檚 your major or program?
• Past: Highlight a recent relevant experience (e.g., internship, research project, volunteer work).
• Future: State your career goals and explain why you鈥檙e excited to connect with this employer.

What are some ways you can make your resume stand out in a pile?

• A resume should be concise, organized marketing document highlighting your education, experiences and achievements; its purpose is to secure an interview and evolve with your professional growth.
• Keep formatting clean and consistent: 1-inch margins, 1 page (up to 2 max), standard 10- to 12-point fonts, professional appearance and easy-to-scan layout.
• Focus content on relevance: tailor to the position, connect transferable skills, emphasize contributions and quantify results whenever possible.
• Use strong writing mechanics: start bullets with action verbs, maintain consistent verb tense (present for current roles, past for previous) and keep statements concise.
• Include core sections as appropriate: Heading, objective (optional but tailored), education (reverse chronological order), summary of qualifications (skills-focused) and experience (employment, internships, research, projects).
• Add optional sections when relevant: Activities, leadership, honors/awards, publications or research.

What software or AI tools do you recommend in helping build your resume?

• is a fantastic tool available to all students by logging in with their NID credentials
• VMock is a 24/7 virtual career assistant that utilizes technologies like artificial intelligence, machine learning and sophisticated analytics engine to deliver instant, personalized, and smart career guidance to students and professionals.
• Do not rely only on AI to write content for your resume. Double check wonky spelling/grammar and word choices to make sure it is your voice.
• Be aware that employers are now reviewing resumes and running them through plagiarism detection software to check for AI.
• Utilize AI (VMock can do this) to make sure your resume matches the language in the job description closely enough so that it will pass through applicant tracking systems successfully.

What are questions you recommend job candidates ask the interviewer?

Typically, it鈥檚 best to focus on two to three questions to have prepared to ask at the end of the interview.

• Ask about the company culture. What is it like to work there?
• Ask about the position or opportunity in a way that helps you learn more than what you have already learned on your own research. In your opinion, what qualities/traits do you look for in an ideal candidate to be successful in the role?
• Ask about what to expect in the interview process. What are next steps?

Are there any best practices you recommend for following up after an interview?

Within 24 hours, send personalized thank-you emails to the recruiters you spoke with that include:

• A brief recap of your conversation
• An expression of gratitude
• A question or statement to keep the dialogue going

Nothing motivates Ilkin Isler 鈥�22MS 鈥�25PhD quite like this phrase: 鈥淚t can鈥檛 be done.鈥�

When Isler says candidly, 鈥淲orking on my Ph.D. is the most difficult thing I’ve ever faced,” there鈥檚 a montage of difficult things in her life to consider 鈥� physical and mental, past and present.

For example, in August 2025, the recent computer science doctoral graduate began work as a senior artificial intelligence (AI) engineer at Universal Creative. Her role involved analyzing complex white papers and developing state-of-the-art AI systems from scratch 鈥� all for the purpose of improving the safety of park guests.

鈥淚 find solutions for high-risk applications,鈥� Isler says, 鈥渨hich is a good description for what I love to do.鈥�

“… when I hear something can鈥檛 be done, it motivates me to make it happen.” 鈥� Ilkin Isler 鈥�22MS 鈥�25PhD

The fact that her work requires fortitude also fits Isler well. In high school in Turkey, she once walked into a gym 鈥渏ust for something to do.鈥� A trainer immediately suggested she head to the cardio area, where she鈥檇 blend in easily. Isler, however, saw the powerlifting space and thought, 鈥�罢丑补迟鈥檚 what I want to do.鈥�

鈥淚 had to teach myself how to do [powerlifting],鈥� she says. 鈥淧eople probably thought I鈥檇 give up, but when I hear something can鈥檛 be done, it motivates me to make it happen.鈥�

Self-taught and competing despite her small frame, Isler went on to become a European powerlifting champion.

All of this is important for understanding the person who, while studying at 麻豆原创, helped develop an AI model to assess cancerous tumors.

Using Computer Imaging to Enhance Patient Care

Guided by a team of advisors, Isler came up with a way to feed medical imaging into an algorithm that measures shapes and textures with more speed, precision and consistency than is currently possible. Given such accurate information, an oncologist could make quicker, more confident decisions 鈥� improving overall patient care.

“… [Ilkin’s] work helps push the field forward in an important and timely way.” 鈥� David Mohaisen, 麻豆原创 computer science professor

鈥淭he problem she chose to work on is inherently difficult for several reasons,鈥� says David Mohaisen, 麻豆原创 computer science professor and one of her advisors. 鈥淢edical imaging is a high-stakes domain where errors have serious clinical consequences.鈥�

鈥淚t鈥檚 also a mature and crowded research area, with competitive works focusing on incremental benchmark gains rather than addressing deeper issues, such as reliability, uncertainty and clinical integration,鈥� Mohaisen continues. 鈥淚nstead of chasing marginal improvements, Ilkin focused on meaningful outcomes. Her work helps push the field forward in an important and timely way.鈥�

Yet the breakthrough alone, and the work that went into it, does not fully capture what Isler faced at the dizzying start of her doctorate journey.

Taking a Chance to Change Her Life and Others

Isler arrived from Turkey with two suitcases and a hotel reservation near 麻豆原创.

鈥淢y mom filled one of the suitcases with Turkish food,鈥� Isler says. She can laugh now, but at the time, she had no clear path beyond the airport. 鈥淚 had to figure everything out.鈥�

A few years earlier, she traveled across the globe to 麻豆原创 as an undergraduate, having earned a competitive internship in the Synthetic Reality Lab, where she worked with Pegasus Professor Charles Hughes and then computer engineering doctoral student Kamran Ali 鈥�21PhD on facial expression recognition.

鈥淪he committed herself to the research,鈥� Hughes says, 鈥渁nd even contributed to writing and editing the resulting report after she returned to Turkey.鈥�

Days away from starting doctorate-level research, with all her belongings in a single piece of luggage, Isler would do what she does best: find a way. She moved from the hotel to an unfurnished apartment.

But with her, Isler brought two specific interests to her postgraduate research at 麻豆原创. Her mother, a dentist in Turkey, inspired an interest in medical advancement. Her father, a computer science professor, recognized in his daughter the curiosity and determination required for the field.

鈥淚f I know an idea can be impactful, I鈥檒l do whatever is necessary to make it a reality,鈥� she says. 鈥淭he higher the stakes, the more driven I become.鈥�

Those stakes led her to focus on medical imaging solutions for cancer care worldwide. Without a medical background, she collaborated with doctors. It helped that she never looked at her research as an academic exercise. She wanted only to deliver something trustworthy that clinicians everywhere could use to eliminate gray areas in image analysis.

鈥淚鈥檝e been fortunate to work with many doctoral students over the years, and Ilkin stands out on multiple levels,鈥� says Mohaisen, pointing out her motivation, energy and curiosity, before adding: 鈥淚鈥檇 say she is among the most driven.鈥�

Fueled by Challenge and Service

By now, the source of Isler鈥檚 uncommon drive is clear. Every time someone showed skepticism about her powerlifting, she responded by breaking a national record. Although she could have attended a private college in Turkey, where she would have been surrounded by familiar language and culture, she instead chose to move across the world to study AI.

There鈥檚 one more motivation that consistently guides her: others.

Isler considers her greatest accomplishment in powerlifting to be the doors she helped open for others in Turkey to try any form of fitness they choose. And she says she would gladly move to another continent again, with just a suitcase and her AI skills, if it meant helping improve the lives of others.

鈥淲hen I look back, I can see that I鈥檝e often traded comfort for growth,鈥� she says, 鈥渁nd I will not hesitate to do it again.鈥�

鈥�There鈥檚 a lot of places that say, 鈥楬ey, look at all the things we鈥檝e done.鈥� And then there鈥檚 麻豆原创 that says, 鈥楲ook at all the things we鈥檙e doing,鈥� 鈥� Sleppy says. 鈥淚 wanted to be part of building the future.鈥�

鈥淚 wanted to be part of building the future.鈥� 鈥� Joe Sleppy

In his first year, he landed undergraduate research opportunities thanks to 麻豆原创鈥檚 , which offers students opportunities for career exploration and experiential learning in STEM the first two years of their college career.

In 麻豆原创 Professor of Nanotechnology Jayan Thomas鈥� lab, the two partnered on the idea that would eventually become Capacitech Energy, where Sleppy has served as CEO since its inception in 2016 during his sophomore year.

Future-Proofing the Power Grid

Capacitech is a rapid response energy storage leader building high-power and space-conscious energy storage systems for an increasingly complex grid. Essentially, Sleppy and his team turn supercapacitor components into modular, plug-and-play systems that harden power infrastructure against power demand spikes, outages and equipment damage.

Sleppy explains traditional power infrastructure, such as generators and batteries, are like a marathon runner whereas supercapacitors are more like a sprinter. Modern facilities 鈥� like data centers that power AI 鈥� demand power 24/7 but also demand even more power than normal for just a few seconds. Ideally, both a sprinter and marathon runner are required. So, Capacitech鈥檚 products make it practical to form relay teams between the traditional infrastructure (marathon runners) and supercapacitors (sprinters).

鈥淚f we can use supercapacitors to complement batteries, generators, fuel cells and the broader grid to serve this demand profile that鈥檚 coming from manufacturing facilities and data centers, then we鈥檙e making the world a better place 鈥� economically, but also in terms of power sustainability and security. And I think that that鈥檚 very important,鈥� Sleppy says.

They made their first commercial sale in 2022 to Red Bull and have been running full force ever since.

Built by 麻豆原创

The company was bolstered by many resources at 麻豆原创 on its way to raising the $2.5 million it has so far through investors and federal research and development programs. To this day, 麻豆原创鈥檚 continues to house Capacitech鈥檚 operations with adaptable leasing structures, physical space, mentoring programs and community that have adapted to their needs as they鈥檝e grown. This year, they鈥檒l expand into new warehouse in research park, adjacent to 麻豆原创鈥檚 campus.

鈥淭he world is watching. Let鈥檚 use innovation and entrepreneurship to make it better.鈥� 鈥� Joe Sleppy

鈥溌槎乖� encouraged me to think outside of the box,鈥� he says. 鈥溌槎乖� is an innovative university because they鈥檒l ask, 鈥榃hy not?鈥� I think I share the same philosophy with running Capacitech. Let鈥檚 try it. The world is watching. Let鈥檚 use innovation and entrepreneurship to make it better.鈥�

In 2026 Sleppy expects Capacitech to announce new partnerships and pilot programs in industry. And they鈥檙e already engaged in mentoring the next generation of Knights with internship opportunities for students.

鈥淓ntrepreneurship is how the world gets better 鈥� whether it鈥檚 a nonprofit or a tech startup like ours,鈥� Sleppy says. 鈥淏y reducing strain on the grid and extending the life of critical infrastructure like batteries and microgrids, we鈥檙e making energy systems more resilient and accessible. That means fewer vulnerable communities at risk and more room for innovation to grow. It鈥檚 hard not to get excited when your work genuinely makes the world better.鈥�

Joe Sleppy was recognized on Forbes’ 30 Under 30 Energy & Green Tech list in 2026.

鈥淲e often hear that 鈥榳e鈥檙e at a turning point in human history,鈥欌�� Tian says, 鈥渁nd with AI research in a university setting like this, it鈥檚 true.鈥�

This is just one example of AI innovations at 麻豆原创. Learn about more at the .

Tian has adapted quickly 鈥� and gladly 鈥� to life at 麻豆原创 since arriving last May to teach computer science. He is now living what he once imagined as the idyllic scenario: talented artificial intelligence (AI) specialists coming from around the world to collaborate with medical experts and launch new projects, pressing each other through formidable challenges and achieving the unachievable.

鈥淭he ultimate goal for my team is to extend people鈥檚 lives, significantly,鈥� Tian says.

Assembling a Dream Team

Tian鈥檚 ambition has eluded human pursuits for millennia. Even medical AI has barely begun to approach its potential impact 鈥� especially when compared with other AI applications like chatbots and fintech.

鈥淭here are two major limitations with medical AI,鈥� Tian says. 鈥淥ne is the privacy of data 鈥� AI requires a lot of data. The other issue holding back progress is collaboration. Computer scientists working on AI typically don鈥檛 know medicine. We need input from doctors and biologists. In that sense, universities are uniquely positioned.”

“Universities bring together computer scientists, physicians and hospitals 鈥� allowing us to identify clinically meaningful problems, access real-world data responsibly and develop solutions that are grounded in medical practice.鈥�

With all of this available to his AIM team, they鈥檝e been building a system that can learn from each patient鈥檚 history, exams, MRIs, CTs and life information. Given the copious amount of data, the AI model would then predict the person鈥檚 future medical trajectory.

For example, a doctor could know the probability of dementia five years before onset. An oncologist could use MRI scans to determine the gene mutation associated with a tumor within seconds rather than performing surgery and then waiting weeks for the results of a genome test.

Diseases would be preventable. Treatment plans would be more effective and less costly. People would be healthier, happier and live longer.

How close are we?

鈥淐lose,鈥� Tian says. 鈥淚t鈥檚 sometimes hard for me to believe, too.鈥�

At the Forefront of AI

As recently as 2020, Tian didn鈥檛 give much thought to topics like longevity or the location of Orlando.

While working to complete his Ph.D., Tian had immersed himself in familiar computer-science objectives at the University of Adelaide in Australia. Day and night, the lab became a replacement for the home he鈥檇 left on the Chinese peninsula of Liaodong. In just three years, he published more than 15 papers.

Yet something was missing: a greater purpose.

鈥淚鈥檝e always wanted to discover a solution to a mystery that has never been solved,鈥� he says.

He didn鈥檛 know what that mystery might be until an advisor asked him, 鈥淒o you want to work on fun AI video projects, or do you want to really impact lives?鈥�

The conversation grabbed Tian鈥檚 attention. He鈥檇 been reading about groundbreaking AI research in computer vision and medical imaging. Many of the papers came from an institution in the U.S., a place called 麻豆原创.

After finishing his Ph.D., Tian came to the U.S. for postdoctoral work at Harvard University and the University of Pennsylvania, digging his attention deeper into not only medical AI, but also into 麻豆原创.

鈥淚 found out about 麻豆原创鈥檚 young medical school with physicians and scientists working together. And then I heard about the hospitals in the Orlando area, including AdventHealth and Orlando Health, and this freedom to explore AI applications. I wanted to be in an environment like that, where research can advance quickly.鈥�

Tian fast-tracked his postdoctoral role so he could accept a position at 麻豆原创, participate in the collaboration, and continue his pursuit of the unsolved mystery: extend life. Shortly after he arrived, the Institute of Artificial Intelligence (IAI) opened its doors 鈥� and Tian went on to establish his lab, taking a significant step toward his long-term research goals.

Big Goals Leads to Big Impact

You can sense a profound energy inside AIM.

It鈥檚 a convergence of talent and enthusiasm. In addition to Tian, the institute has recruited two dozen faculty, more than 100 doctoral students and 10 postdocs to imagine and encourage progress. The expertise transcends domains, including computer science, robotics, finance, smart cities and medicine.

鈥淲e all have big goals,鈥� Tian says.

Less than a year after heading up the AIM Lab, he says, 鈥淲e aren鈥檛 far off from deploying AI models in hospitals to help doctors.鈥�

Tian works at the same speed as technology (fast), until a certain topic comes up. Family. He looks up and begins to describe his hometown, his mother, and the sight of his dad walking in the door one night with the family鈥檚 first computer.

鈥淗e and I were fascinated. We went from trying to install the first software to building our own computers and robots. I could never get enough of it.鈥�

Those memories motivate him to work even faster toward his ultimate goal.

鈥淚 want to help everyone have a quality life to 100 鈥� or longer. My family. Me. All of us,鈥� he says. 鈥淚 love the possibility. I love being here, at this turning point, with the opportunity to make a huge impact.鈥�

The needed breakthrough may be just around the corner with the development of an online dashboard DrugTRAC, which uses an AI-powered algorithm to synthesize information provided from statewide lab records 鈥� allowing for nearly real-time insights on the local drug supply.

鈥淓ven though I鈥檓 an administrator, this research is something I think I鈥檒l always be involved in because it is so important,鈥� she says. 鈥淭his is how we save lives 鈥� by reaching out and doing things proactively instead of retrospectively.鈥�

This initiative was created through Project Overdose, a community-based nonprofit focused on combating overdoses resulting from the opioid and drug epidemic that Cortelyou worked with for six years. Formerly called Project Opioid, Project Overdose partners with local business, faith, philanthropy and public health leaders to address substance use in Florida.

How DrugTRAC Works

Cortelyou collaborated with tech developer Social Innovation Technologies to help design DrugTRAC, which stands for tracking, reporting, advocacy and coordination. The data, which is anonymized and privacy-protected, relies on routine lab tests like urine and toxicology screens to offer researchers new insights into which substances are circulating in Florida communities.

鈥淥ne of the biggest challenges in this field is that we鈥檝e always been behind,鈥� Cortelyou says. 鈥淭he only real data about what is happening in the drug supply in your community has been from mortality data, which takes almost 12 to 18 months to get after someone dies from an overdose. That means you鈥檙e dealing with yesterday鈥檚 problem. If you’re trying to make decisions based on trends that were happening a year ago, you’re always behind.鈥�

The dashboard compiles nightly drug-screen results and tracks more than 90 different substances before mapping emerging trends down to the ZIP code level. That information can then be used to alert community leaders and first responders to potential spikes and co-occurring substances, like the presence of fentanyl in cocaine.

DrugTRAC鈥檚 Current and Future Impact

The tool recently detected the presence of carfentanil, an extremely dangerous synthetic opioid that is nearly 1,000 times more potent than morphine and 100 times more than regular fentanyl. It could require four or five administrations of Narcan to revive someone from a fatal overdose, making it crucial that first responders and community leaders are alerted to any presence in the community.

However, artificial intelligence will take the tool鈥檚 impact to the next level. Cortelyou and the Social Innovation Technologies team anticipate being able to launch a more proactive approach with the help of AI in the next six months. By integrating an innovative, AI-powered algorithm into the system based on a range of data 鈥� including economic indicators, major events, arrest records and time of year 鈥� to predict future trends. That information can be used to provide early warnings to hospitals, emergency medical services, law enforcement and community organizations.

鈥淚’m working with the programmer to help them identify the data sources that will feed into the algorithm, like the factors that cause spikes in drug usage,鈥� Cortelyou says. 鈥淭he dream is that once this system becomes predictive, we鈥檒l be better prepared and able to say, 鈥楬ey, in the next couple of weeks, we’re expecting to see X, Y and Z happen in your community. Get ready.鈥欌��

Cortelyou says they are also currently investigating ways to make the alerts and information more accessible, like social media content targeted toward younger, more at-risk age groups.

Ultimately, Cortelyou hopes this technology can help communities get ahead of drug overdoses and help communities respond faster than ever before.