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By Holly Wise and Inder Kumar, International Coaching Federation (ICF)-Certified Coaches and facilitators of optional one-on-one coaching sessions for India RISE Fellows Ask someone to picture a leader, and a familiar figure often appears: charismatic, assertive, directive and visibly authoritative. It is the person at the front of the room, making decisions, setting the direction and ensuring tasks are completed. There is little question about who is in charge. For early-career women building scientific careers, this image can become especially sharp. They are often mentoring students or juniors while navigating institutional expectations in environments where seniority and expertise are closely watched. But there is a measurement problem with this image of leadership. When young scientists measure themselves only against this commanding figure, they can easily conclude that they are lacking something. Through our coaching practice, we have observed that many capable people do not need more advice on how to adopt this style of leadership. Instead, we create the conditions for them to examine their own assumptions, recognise their strengths and make more intentional choices. That approach felt particularly relevant to our work with emerging women leaders. Their challenge is often finding ways to exercise their strengths that feel authentic to who they are. The conversations we have had with India RISE Fellows suggest they are not lacking leadership qualities. They are measuring themselves against a standard that does not necessarily align with their values. They do not always see themselves reflected in the image of leadership they have inherited. Recognising the leadership already present Across the coaching-skills workshop and one-on-one coaching conversations, we were struck by the words Fellows used to describe their own strengths: supportive, calm, reflective, people-centred, relationship-focused and approachable. They described themselves as people who listen, bring out other people’s strengths, develop confidence rather than dependence, and maintain relationships while still holding people accountable. Their reflections made clear that Fellows are already practising this style of leadership. In their academic and laboratory settings, they assess priorities, design professional learning opportunities and mentor juniors and students. For some, there was a clear tension: how do I reconcile the standard image of a leader with my own values? This dilemma is not about whether one leadership style is better than another. The question is whether Fellows can begin to recognise the leadership already present in their own way of working and become more deliberate about how they use it. Assertive with care Several Fellows reflected on what it would mean to be “assertive with care”. That phrase describes something more demanding than simply appearing confident. It asks a leader to hold together qualities that are too often presented as opposites. A leader can be: Approachable and authoritative Caring and firm Reflective and decisive Supportive and accountable Relationship-focused and clear about boundaries The ability to hold these qualities together is not a contradiction. It may be the work itself. Being approachable does not require permissiveness. Being caring does not mean avoiding difficult conversations. Listening does not mean delaying every decision. Maintaining relationships does not mean sacrificing accountability. The Fellows’ reflections suggest that these qualities can strengthen one another. Putting them into practice requires judgement: when to listen and when to act, when to support and when to challenge, when to remain flexible and when to hold a boundary. That judgement depends on understanding both the person and the context. Space to define leadership for ourselves Coaching gave Fellows a structured way to examine these choices. In the workshop, they distinguished coaching from mentoring and advising, then practised being present, asking open-ended questions, reflecting and exploring strengths. Through demonstrations, role-play, peer conversations and group coaching, they experienced how a conversation changes when the first response is a question rather than an instruction or solution. While mentorship offers perspective and advice from someone who has travelled further along a similar journey, coaching offers something different. It slows the conversation down, creating a non-judgemental space in which a person can articulate what matters, test inherited assumptions about authority and decide what action to take. Perhaps most importantly, Fellows have the space to define leadership for themselves. Through this process, a more nuanced understanding of authority begins to take shape. The question “How do I become a better leader?” becomes more specific: How can I be more intentional about being the kind of leader I already am? Creating spaces where Fellows can recognise, refine and trust the leadership they are already beginning to practise may be one of the quiet strengths of the India RISE cohort. Holly Wise Holly Wise is an ICF-certified coach and leadership partner based in Bengaluru, India. She helps high-performing professionals navigate career transitions and leadership challenges with structured coaching and practical strategies. Holly brings together rigorous coach training, extensive cross-cultural experience, and years of leading teams and mentoring professionals across sectors. She partners with accomplished professionals to cut through operational noise and lead with the clarity and confidence needed to create meaningful institutional impact. Inder Kumar Inder Kumar is an ICF-certified leadership and career development coach. He brings over two decades of experience building businesses, leading teams and mentoring professionals across technology, consulting and operations in Africa, Europe and India. Today, he helps professionals, founders and entrepreneurs navigate transitions and uncertainty with greater clarity, confidence and self-direction. Through India RISE, he helps Fellows apply coaching skills to peer mentoring conversations and take greater ownership of their growth.

By Rinki Prasad Bhagat, a second-year PhD research scholar in the Department of Pharmaceutical Technology at Jadavpur University, Kolkata and India RISE Fellow 2026 There is a question I return to often, usually late at night when an experiment has not gone the way I hoped: Can I make a meaningful contribution to cancer research? No classroom ever prepared me to sit with a question like that. I do not have an answer yet. But I have come to believe the lab is where I learned to keep working even without one. Finding my way into research My path here was not direct. As a child, I loved biology enough to want to become a doctor. I was fascinated, as many children are, by the idea of understanding the body and helping people heal. That particular dream did not work out. But I did not want to leave medicine behind altogether, so I chose pharmacy instead, hoping it would keep me close to something I cared about, even if I was not yet sure how. For a long time, pharmacy was something I studied from textbooks, something I understood in theory, on paper, in the language of lectures. That changed during my bachelor’s degree, in the middle of the disruptions of the COVID-19 years, when I got the chance to work in a laboratory for my final-year project on formulation development. My guide at the time, Prof. Pintu Kumar De, believed in me at a stage when I was still finding my footing, and that belief mattered more than I think he ever realised. No classroom had told me that a medicine is not simply prescribed that it is designed, tested, and refined, often through long stretches of trial and error before it works the way it is meant to. The lab taught me that. It turned pharmacy from a subject into a practice, and it planted the first real seed of wanting to pursue research further. In my master’s, I moved to an earlier stage of that process, into computational drug discovery, using in silico, or computer-based, tools to predict how a molecule might behave before testing it in the laboratory. My supervisor, Dr. Shovanlal Gayen, introduced me to computational research patiently, from the ground up, and gave me a language for thinking about molecules through models. It was intellectually exciting work, and in many ways, it still felt close to the classroom: screens, models, predictions. But it left a gap I could feel. I had learned to predict molecular behaviour. I had not yet learned to synthesise a compound at the bench, to fail and try again, or to see it come together after repeated attempts. I wanted the part of the process that no lecture could simulate, and that desire eventually led me toward a PhD. Learning to begin again I am now in the second year of my PhD in the Department of Pharmaceutical Technology at Jadavpur University, under the supervision of Prof. Tapan Kumar Maity, where I work on designing chemical scaffolds and evaluating compounds built around them for potential anticancer activity. What is a chemical scaffold? A scaffold is the core structure of a molecule, which researchers can modify to explore how those changes affect its properties and activity. Joining a new lab meant becoming a beginner all over again, learning new techniques, a new rhythm of work, and a different relationship with uncertainty. Much of what I know now, I owe to my lab senior, Dr. Avik Maji, who taught me from scratch, patiently and repeatedly, without ever making me feel behind. He believed I could do this, even on the days I did not believe it myself. That belief has carried me through more difficult stretches than I can count. And there have been difficult stretches. The last two years have not moved in a straight line. There have been long spells with limited resources, when I have had to find my own way around a problem instead of waiting for someone to solve it for me, and a period of ill health that slowed me down in ways I had not planned for. “I have had to learn, slowly, that recovering and starting again is part of research too.” Why cancer research is personal Somewhere underneath all of this sits a more personal reason for choosing cancer as my focus. My maternal grandmother passed away because of cancer, and my aunt has lived through it. I was too young, when my grandmother was ill, to understand what was happening beyond knowing that something had taken her away slowly, without anyone around me having a clear answer for why. I do not think that memory alone explains the scientific questions I ask at the bench today. Those are shaped by evidence, by data, by what the research actually allows me to test. But I would be lying if I said it had nothing to do with why I keep returning to the bench on the days when nothing works. Finding my voice through India RISE Alongside the science, I have been working on something quieter: learning to speak up. For much of my academic life, I found it difficult to voice an idea clearly or advocate for my own work in a room full of people. My time with India RISE has shaped this more than almost anything else. Its mentors have taught me, in small and repeated ways, to celebrate wins I used to dismiss as too minor to count, to ask for help instead of struggling through silently, and to stop underestimating what I am capable of. I am still learning to be patient with my own pace of growth, and I suspect that particular lesson will take longer than any single experiment. I think often about how ordinary these struggles are, and how rarely we talk about them while they are happening. Early-career researchers, and women in research in particular, can feel expected to appear confident and certain

By Vamanie Perumal, Lead AI Researcher, AI4NetZero Group, IIT Madras and India RISE Fellow 2026 When I led a peer-led session for the India RISE cohort on using artificial intelligence in research, I began with two disclosures. First, I did not come from a computer science background. My bachelor’s and master’s degrees were in the sciences, and I pivoted to AI only during my PhD at IIT Madras. I therefore wanted to share a practitioner’s perspective on how a scientist or biologist can use AI in research. Second, I used AI to help prepare the session. The notebook and parts of the presentation came from NotebookLM. I retained different slide styles because some outputs did not meet my requirements or contained inaccuracies. The result demonstrated a central point: AI-generated work still requires human review and editing. AI tools can initially feel overwhelming, and their capabilities keep evolving. Researchers do not need to use every platform, although it helps to understand what different tools can and cannot do. I do not use more than two or three tools for a single task. The useful question is: what exactly are you trying to achieve? AI is only a tool, and the real master is the researcher and her domain expertise. It can generate information at a speed that is difficult for any individual to process, but speed does not make the information accurate. AI is a fluency machine, not a truth engine. When someone begins using a large language model, its confident answers can appear convincing. With greater expertise, the user becomes better able to identify where the model is fabricating information or generating what I call “confident mess.” Human expertise and context are what make the use of AI effective. Before using AI for a research task, I ask whether it can reasonably be completed manually. AI is most useful when a task becomes cumbersome or exceeds human scale. For example, I work with around one trillion data points on an everyday basis, which cannot be analysed manually. If I were working with only a thousand data points, however, a manual method might still be possible. Researchers should first judge whether AI is genuinely necessary. I think of human-AI collaboration at four levels. A researcher may begin by asking a tool to explain a concept. She can then add the context in which she wants to apply it, ask the tool to criticise the proposed method and, finally, use it for an adversarial review by providing detailed information about the dataset, hypothesis, limitations and possible results. During the session, I used principal component analysis, or PCA, for Raman spectroscopy as an example. Simply asking, “What is PCA?” is very different from asking whether PCA is appropriate for a particular dataset. A useful prompt would explain the researcher’s mathematical knowledge, the limitations of the data and the scientific questions she is trying to answer. It would ask the tool to act as a scientific reviewer, challenge the method and identify supporting literature. The researcher must then examine the response through her own subject knowledge. AI can also support literature reviews. A good review usually begins with a seed paper, followed by backward snowballing to examine the work it cites and forward snowballing to identify later research that develops it. Tools such as Connected Papers, Elicit, Consensus, ResearchRabbit and NotebookLM can assist with different parts of this process. I demonstrated them using a paper on predicting uranium in Punjab’s groundwater through machine learning. Because few studies had addressed this question, the exercise revealed the platforms’ limitations. One identified relevant prior work, another found a newer paper, and another returned no useful results. I therefore recommend comparing no more than two or three tools, checking a sample of their results and returning to the original papers. Once papers have been collected, I use a three-pass approach, for summarising the papers. The first pass screens abstracts and conclusions. The second examines figures, tables, methods and findings. The third develops critical arguments and considers how the research might be extended. I created structured prompts for each stage and used NotebookLM to rank and synthesise the papers. This keeps the human method of reading at the centre instead of asking a tool to produce an entire review from uploaded articles. The same principle applies to scientific writing. My preferred structure is the OCAR approach: opening, challenge, action and resolution. I also use academic-writing resources such as They Say/I Say to provide examples of how arguments, citations and diverging results can be presented. A clear structure and good examples produce more useful output than a general instruction to write a paper. AI-assisted coding also requires safeguards. Models may generate long scripts, silently skip errors or repeatedly create files and functions that become difficult to manage. Researchers should write a detailed specification, divide the analysis into stages, define assumptions and thresholds, introduce checkpoints and maintain logs. When a failure occurs, it is better to identify the stage that failed than to ask AI to debug the entire repository. Most importantly, researchers must be able to explain the code they use. Expected results alone do not prove that the code is correct. There are serious limitations to consider. AI can fabricate information, reproduce gender bias, create confidentiality risks and raise questions about ownership. Unpublished data and materials should not be uploaded casually to large language models. Excessive reliance on AI can also homogenise writing, dilute a researcher’s individual identity and contribute to de-skilling. I once received a peer-review comment asking me to carry out an analysis that was not technically feasible. Because it did not make scientific sense, I used an AI-detection tool, which flagged the comment as AI-generated. That did not establish its source conclusively, but the experience reinforced the need to evaluate every recommendation through domain expertise. My view is that we should retain the human element in our work so that it continues to represent our identity and thinking. If AI is used consciously, with verification

By Indrani Devi Sarma, India RISE Fellow 2026 and Senior Resident at All India Institute of Medical Sciences, Guwahati “There is no gift equal to food and water, no sacred day equal to Dwadashi, no mantra greater than the Gayatri, and no deity greater than the mother.” Chanakya Neeti This line has stayed with me because my understanding of life was shaped by my mother. As the honorary principal of a women’s college, she dedicated her time to educating young women and helping them build more independent lives. She taught me to think about others before myself. I always wanted to become a researcher, but for a long time, I did not know how to turn my desire to find answers into work that could directly improve people’s lives. My time at AIIMS Guwahati changed that. I moved from saying, “I wish I could do something about this,” to saying, “I will try my best to do something about it.” I realised that even if an attempt fails, it will teach you something and point you towards another path. As a popular Hindi line says, “Risk hai toh ishq hai,” which can be translated as, “Where there is risk, there is love.” If I never risk failure, I will never know the joy of succeeding. My technical advisor and mentor, Dr. Dibyajyoti Saikia, strengthened this belief. He placed his trust in me, and together we started Vritiksha Tech Pvt. Ltd. to work on problems where technology could make a meaningful difference. Sometimes, significant changes begin with small events. After a viral infection caused laryngeal palsy and affected my mentor’s ability to speak, we began discussing something most of us take for granted: the ability to communicate. Gestures used by people with speech impairments may not be understood by someone who has not been trained to interpret them, while existing communication tools may rely on cameras or internet access. We asked a simple question: how can someone communicate in a dark room, without a camera or a network connection? That question led to Vritivani, an initiative designed to help people with speech impairments communicate through simple finger movements, without relying on cameras or the internet. When we spoke to members of the community, they confirmed that such a device was genuinely needed. Their response showed me that an idea arising from an ordinary conversation could change how someone experiences the world. Our first prototype has now reached the initial target we set for it, encouraging me to keep looking for other problems where a focused intervention could help. One such problem was access to ferritin testing in resource-constrained settings. Ferritin levels help clinicians assess iron deficiency and guide decisions about whether a patient may need intravenous iron therapy, but the test can be costly or slow to obtain. Using machine-learning algorithms, I developed a tool that uses information from a complete blood count, a cheaper and routinely available test, to estimate ferritin levels. It is an early step, but with further validation, it could help identify patients who may need additional assessment and appropriate treatment. Another idea emerged when I stepped in to teach a class. I noticed that many students were more comfortable with digital devices than textbooks, and longer concepts often struggled to hold their attention. Digital platforms were already part of how they encountered information, so I began asking how they might become a more purposeful part of the classroom. This led to iDIAL, a method that allows instructors to organise information into gamified learning modules. Students play as they learn, with knowledge becoming the key to progressing through the game. These experiences have taught me that entrepreneurship does not necessarily begin with a business plan, a company or even a fully formed idea. It begins with a problem that you cannot ignore. For me, it is the willingness to replace “I wish someone would do something about this” with “Perhaps I can try.” An idea may simply need to meet the right problem, time and context before it can make a difference. This understanding has also made me think differently about women and entrepreneurship. Many women learn to solve problems, manage finances, use limited resources, generate income, take risks, make decisions and build networks from an early age. Yet these abilities, particularly when practised within the home or community, are not always recognised as forms of leadership or entrepreneurship. Recognition matters. If we want more women to imagine themselves in positions of leadership, we must make the women who already occupy these positions visible. Titles such as principal, dean or principal investigator are gender-neutral, yet many people may still unconsciously picture a man. Even my own name has sometimes been changed from Indrani to Indraneel by people who do not know me, perhaps because the latter fits their mental image of someone in a particular position. I have wondered whether explicitly feminine forms of institutional titles, such as “decaness” for a woman dean, could help challenge that default image. More broadly, how do we make women’s authority visible through the language and images around us? When a young woman repeatedly sees women as principals, deans, principal investigators, entrepreneurs and institutional leaders, she begins to understand that these paths are open to her too. Recognition does not only honour the woman who has already climbed the ladder. It can inspire another woman to begin climbing. Perhaps this is what my mother taught me without ever calling it entrepreneurship. She educated young women, led an institution and helped others imagine fuller lives. She taught me my first lessons in leadership, not by explaining how to build a company, but by showing me how to notice a problem, take responsibility and try to improve someone else’s life. For me, entrepreneurship begins with empathy. It begins when we see a problem, believe that we can act and find the courage to risk failure. Women have practised this form of entrepreneurship quietly for generations. We do not always need to become

By Srishti Kapil, Communications Lead at India RISE Fellowship and Programs and Communications Specialist at Gupta-Klinsky India Institute at Johns Hopkins University Before I knew what a laboratory smelled like, what scientists did all day, what degrees they needed or what their work paid, science arrived as photographs in newspapers, rockets on television, school assemblies after major launches, and women whose names suddenly seemed to belong to the whole country. I remember Kalpana Chawla this way. On 1 February 2003, the Space Shuttle Columbia broke apart during re-entry, killing all seven astronauts aboard. Chawla was one of them. I was young enough that the mechanics of what had happened were beyond me. What I understood was simpler and, perhaps, more important. An Indian-born woman had gone to space. She had gone somewhere so far away that we had to look upward to describe it. Space, which until then had belonged to rockets and planets and diagrams in textbooks, acquired a human face for me. A woman’s face. I think children learn professions this way. We collect them as images long before we encounter them as choices. Years later, I watched Barkha Dutt anchor We the People and Shekhar Gupta host Walk the Talk. Through those programs, I encountered conversations that rarely reached the classrooms and neighbourhoods of the smaller towns where I grew up. I remember writing unfamiliar words in my diary, looking them up in the thick thesaurus we kept at home, and trying them out the next day to impress my English teacher. I wanted to be a journalist. For a while, I also wanted to be a detective. This ambition was entirely Nancy Drew’s fault. I spent enough years following her through hidden staircases, missing wills and suspicious strangers to become convinced that adulthood might consist of noticing what everyone else had missed. Astronaut. Reporter. Detective. My childhood occupations had costumes. A spacesuit. A microphone. A magnifying glass, at least in my imagination. You could draw them. My actual career is harder to draw. Most days it looks like a desk and a laptop. Tabs. Drafts. Comments in margins. Emails that multiply while I answer them. Some days I work on something that feels consequential, a story, an argument, a program trying to shift some small piece of the world. On other days I change the wording in a document for the seventh time because an institution has decided that one adjective is safer than another. I had no childhood image for this kind of work. What the screen permits The distance between media and STEM feels much smaller to me than we often make it sound. Before someone applies for engineering school, sits an entrance exam or walks into a laboratory, she has already spent years receiving messages about the sort of person who belongs there. UNESCO currently estimates that women make up roughly one-third of researchers worldwide and 35% of STEM graduates globally. Across G20 countries, women hold only 22% of STEM jobs. San Diego State University’s 2025 analysis of top-grossing US films found that women accounted for 38% of speaking characters. The share of films with female protagonists had fallen from 42% in 2024 to 29% in 2025. ROX’s 2024 Girls & STEM Impact Report, based on a US survey of 17,502 girls in grades 5 through 12 conducted during 2022 and 2023, found that 55% were considering a STEM career, up from 45% in its 2017 study. At the same time, the share who believed they were good at maths and science had fallen from 73% to 59%. Interest had grown while belief in their own ability had weakened. That contradiction stays with me. The same ROX study found that confident girls were 20% more likely to consider STEM careers. Girls whose teachers treated them as though they were smart were 56% more likely to express interest in a STEM occupation. The Geena Davis Institute’s study of ‘Scully Effect’ found that, among women familiar with The X-Files character, half said Scully had increased their interest in STEM. Sixty-three per cent said she had increased their confidence that they could excel in a male-dominated profession. A fictional scientist had altered how real women understood their own possibilities. Who gets remembered Of course, getting women into the scientific imagination solves only the first problem. There is another question waiting at the other end of the career.Who gets remembered? In 1993, historian of science Margaret Rossiter gave a name to the systematic under-recognition of women’s scientific contributions: the Matilda Effect, named after nineteenth-century suffragist Matilda Joslyn Gage. Rossiter described a history in which women scientists could be ignored, denied credit, or gradually disappear from the account of work they had helped produce. Research conducted years after Rossiter coined the term suggests how persistent those mechanisms can be. Anne Lincoln and colleagues examined awards and prizes across US scientific societies. For scholarly research awards between 2000 and 2010, men were twice as likely to win after accounting for their representation in the nomination pool. Committees chaired by men awarded prizes to men 95.1% of the time, even though women made up 21% of the nominees considered by those committees. A 2013 experiment by Silvia Knobloch-Westerwick, Carroll Glynn and Michael Huge offered 243 young communication scholars conference abstracts carrying male or female author names. The work associated with male authors was judged higher in scientific quality, particularly when the subject itself was perceived as male-typed. Women for Mars Indian cinema has made this question personal for me. When Mission Mangal (2019) arrived, I was hungry for what it offered: a room full of Indian women doing science. The film is a heavily dramatised account inspired by ISRO’s Mars Orbiter Mission, Mangalyaan, which launched in November 2013 and entered Mars orbit the following year. The women in the film were busy, funny, tired, dressed like people I might actually encounter in an office or on the metro. Tara Shinde, played by Vidya Balan, could move between the Mars mission

By Himashree Deka, Research Scholar, Indian Institute of Technology (IIT), Guwahati and India RISE Fellow 2026 Could technology help identify signs of mental health challenges before they become severe? This question now sits at the centre of my research, but it was not where my engineering journey began. Like many engineering students in India, I initially viewed engineering through the familiar language of coding, circuits, systems, and technological innovation. Mental health seemed to belong elsewhere, usually to hospitals, counsellors, or specialists, and it was rarely discussed openly in academic spaces. Yet around me, I could see how stress, isolation, academic pressure, and emotional distress often remained unnamed until they had already begun to affect a person’s studies, relationships, or daily life. That perspective began to change during my time at IIT. Through discussions with my guide, Dr. Hanumant Singh Sekhawat, I was introduced to the idea that engineering and artificial intelligence could contribute to meaningful societal challenges. During one of our conversations, he gave me a copy of Psych 101 by Paul Kleinman. The book offers an accessible introduction to the fundamental concepts, theories, and experiments that have shaped psychology. By exploring how psychologists study human behaviour, cognition, emotions, and decision-making, it encouraged me to think beyond purely technical problems and appreciate the scientific understanding of human experience. Reading it broadened my perspective on how scientific inquiry can be applied not only to understanding the natural world, but also to addressing complex human and societal challenges. As our discussions continued, I began to look more closely at mental health as a problem of both care and access. In India, many people still delay seeking support because of stigma, lack of awareness, limited availability of trained professionals, cost, or uncertainty about where to begin. For students and young adults in particular, early signs of distress can be mistaken for ordinary pressure or hidden out of fear of being judged. This led me back to the question: could technology help identify signs of mental health challenges before they become severe? Today, my work focuses on developing AI-driven approaches for mental health awareness and early detection. Specifically, I study human behavioral signals, particularly eye movements and speech to identify patterns associated with mental health conditions. One area of my research explores eye-movement analysis for the early detection of schizophrenia. Eye movements are closely linked to cognitive processes and brain activity. The way individuals focus, shift attention, scan visual information, or track objects can reveal subtle behavioral markers. While these patterns may be difficult for humans to detect consistently, machine learning models can uncover meaningful signals that support early screening. Another focus of my research is speech-based depression detection. Human speech conveys far more than words alone. Variations in tone, energy, speaking rate, pauses, and vocal expression often reflect emotional and psychological states. Depression can subtly influence these characteristics, and AI techniques can help identify such changes through the analysis of voice recordings. What fascinates me most is that these indicators emerge from ordinary human behavior. We speak and move our eyes every day without conscious thought, yet these seemingly routine actions can reveal silent struggles that individuals may find difficult to express. The purpose of this research is not to replace doctors, psychologists, or therapists. Mental healthcare fundamentally depends on human empathy, professional expertise, and meaningful interpersonal support. Rather, I see AI as a complementary tool, one that can assist in early screening, raise awareness, and encourage timely intervention. Early detection is particularly important in mental health. Many individuals postpone seeking help because of stigma, limited awareness, or fear of being judged. By the time support is received, the condition may already have affected their academic performance, career, relationships, or overall quality of life. Technologies capable of identifying early warning signs could help bridge this gap and facilitate access to care at a much earlier stage. This potential is especially significant in India, where mental health resources remain limited relative to the size of the population and where support is often concentrated in urban or institutional settings. For someone who is unsure whether their distress is serious enough to seek help, or who does not have easy access to a counsellor or psychiatrist, AI-enabled screening tools could offer a first point of awareness. In the future, such tools may help make preliminary assessment more accessible, scalable, and affordable. Working in this field has also transformed my understanding of technology itself. Research is often measured through algorithms, accuracy metrics, and technical publications. Yet behind every dataset lies a human story. This perspective serves as a constant reminder that technology should not only be intelligent, but also responsible, ethical, and meaningful. My journey has shown me that engineering can create impact far beyond its traditional applications. By combining signal processing, machine learning, and data-driven analysis, I hope to contribute to a future where mental health conditions are detected earlier, understood more deeply, and discussed more openly. Sometimes the signs are visible in the movement of the eyes. Sometimes they are heard in the nuances of a voice. And sometimes, recognizing those signs early can be the first step toward healing. By Himashree Deka Research Scholar, Indian Institute of Technology (IIT), Guwahati and India RISE Fellow 2026

By Palkin Arora, Postdoctoral fellow, IIT Gandhinagar and India RISE Fellow 2026 I did not begin my journey in research with the intention of becoming a neuroscientist. I wanted to be a clinician. That was the plan I held onto: clear, structured, and meaningful. When I could not secure a clinical position, that certainty quietly gave way to uncertainty. What followed was not a bold pivot, but a direction I had not consciously chosen. I turned to biochemistry, telling myself that if I could not work directly with patients, I could at least stay close to the biology of disease. But very quickly, I found myself lost in it: pathways upon pathways, intricate but overwhelming. I remember sitting with pages of metabolic maps, thinking: this is important, but it feels distant, hard to connect to something human. For a while, I carried that quiet doubt, that maybe I had taken a path that did not quite fit. And then, one class changed everything. It was a neurobiology lecture where my professor paused midway and shared an email he had received. It was from a neighbour of a patient living with amyotrophic lateral sclerosis, or ALS. She wrote about how the patient’s involuntary movements were misunderstood by the community and how people mocked what they did not understand. She wrote about visiting doctors, about leaving without answers. Almost as an act of hope, she began reaching out to researchers. I do not remember the rest of that lecture. I remember sitting there, struck by something I had never fully grasped before: when healthcare systems reach their limits, people turn to research. Not as an abstract pursuit, but as a possibility, sometimes the only one left. Research no longer felt distant. It was not just about knowledge; it was about responsibility. That moment shifted something fundamental in me. Research no longer felt distant. It was not just about knowledge; it was about responsibility. With that shift, I moved towards neuroscience. Finding the Brain-Body Connection For my Master’s dissertation, I began studying microglia, the immune cells of the brain. The first time I saw them under the microscope, I remember pausing longer than necessary. They were not static structures; they seemed alive in a way I had not expected, constantly extending and retracting, quietly surveying their environment. I remember thinking: these cells are always watching, always responding. What fascinated me even more was what we began to observe: that inflammation in the body could activate these cells in the brain. The boundary I had once imagined between brain and body started to dissolve. The brain was not isolated; it was in constant conversation with the rest of the body. That idea stayed with me. Studying Injury, Disruption, and Recovery I carried this idea into my PhD, where I studied traumatic brain injury, or TBI. Here, the questions became more complex. What happens when the brain is disrupted? How does that disruption extend beyond neural circuits? What I found was that injury does not remain contained. A blow to the brain can ripple through the body, altering immune responses, metabolism, and overall physiological balance. The brain does not break alone; it takes the body with it. This work showed me what breakdown looks like, not as a single event, but as a gradual loss of coherence across systems. But somewhere in the middle of studying how the brain breaks, I found myself drawn to a different question. What does it mean for the brain to rebuild? This curiosity led me towards understanding resilience, large-scale brain networks, and eventually, meditation. If injury represents disruption, then practices like meditation offer a window into regulation: how the brain can reorganise, stabilise, and adapt in intentional ways. From disruption to regulation, from breakdown to rebuilding, the question remained the same, but the lens had shifted. At its core, my work now explores how the brain interacts with the body, and how these interactions shape our experience of the world. Navigating Research as an Early-Career Woman in STEMM Alongside this intellectual journey, there has been another, less visible layer to my experience in research. There were moments when progress felt uncertain, not because of a lack of effort, but because of delays, dependencies, and unclear timelines. Work that required acknowledgement would wait. Decisions would stretch out. And in those spaces, it was easy to begin questioning not just the system, but myself. These are not always the challenges we are trained to anticipate. They are subtle, often unspoken, yet deeply influential, especially for early-career researchers navigating complex institutional structures. For many women in STEMM, these experiences are not exceptions; they are patterns that shape how we move, persist, and sometimes hesitate within research spaces. Learning to navigate this has been its own form of training. An Evolving Relationship With Research My journey, in that sense, is still unfolding. From wanting to treat patients, to understanding molecules, to studying the brain in states of injury and recovery, I have come to see research not as a fixed path, but as an evolving relationship between questions, systems, and lived experience. And perhaps that is where I find myself now, not at a destination, but in a direction. A curious neuroscience researcher, trying to understand the brain, not only in how it breaks, but in how it rebuilds, adapts, and continues. Because sometimes, the most meaningful paths are not the ones we choose, but the ones that reshape how we choose to see. By Palkin Arora, Postdoctoral Fellow, Indian Institute of Technology (IIT), Gandhinagar and India RISE Fellow 2026

By Beth Romanski, Curriculum Director, India RISE and Senior Program Manager, Gupta-Klinsky India Institute From the earliest stages of envisioning the India RISE Fellowship, I was inspired by the opportunity to help build a large-scale educational initiative with meaningful impact. The vision was clear: to create a transformative, accessible, and empowering learning experience for early-career women STEMM researchers in India. The challenge was to translate that vision into a curriculum that was rigorous, relevant, and responsive to researchers working across disciplines, institutions, and regions. Building a Learning Journey For me, curriculum design has always been more than the organization of content. It is the careful construction of a learning journey. A strong curriculum asks what learners should be able to do by the end of an experience, what support will help them get there, and how a program can honor diverse backgrounds while maintaining high academic and professional standards. My approach began with listening. Over several months, our team reviewed insights from Indian institutions, industry partners, global STEMM programs, Johns Hopkins faculty, and women scientists at different stages of their careers. Most importantly, we listened closely to partners and prospective learners in India to ensure that what we were designing would make sense within their cultural, institutional, and professional contexts. These conversations reinforced a simple truth: meaningful professional growth requires more than technical expertise. Researchers also need mentorship, confidence, leadership development, institutional navigation skills, and a supportive professional community. This is especially true for early-career women researchers in Indian academic and research settings. Many are expected to excel in research while also carrying administrative, mentoring, or caregiving responsibilities. Others work in environments where access to senior mentors, international networks, or leadership training may be uneven. A curriculum designed for impact must recognize these realities and offer a learning experience that is both rigorous and practical. It must also create value beyond the fellowship year, giving fellows continued access to resources, networks, and skills they can return to as their careers evolve. Three Pillars: Research, Leadership, and Mentorship With this in mind, we designed the India RISE curriculum around three interconnected learning pillars: research, leadership, and mentorship. The research pathway supports fellows in strengthening advanced research and project management skills, including research ethics, proposal development, grant writing, scientific communication, stakeholder engagement, and translational research. The leadership pillar helps fellows build self-awareness, confidence, adaptive leadership practices, and strategic career plans. The mentorship pillar places guidance and peer learning at the center of the fellowship, connecting fellows with research advisors, program mentors, peer mentors, and coaching support. Each pathway is intentionally layered. Fellows are not simply receiving information. They are applying ideas to their own research trajectories, reflecting on their professional goals, and building a personalized roadmap for growth. One core tool is the Individual Development Plan, or IDP, which is tailored to each fellow and helps connect research ambitions with leadership development and mentorship needs. The experiential Capstone Project also gives fellows a way to apply each stage of the researcher journey in real time, creating immediate value for their own career trajectories, their institutions, and India’s broader research ecosystem. Designing for Outcomes and Access The curriculum is grounded in evidence-based adult learning theory, including competency-based education and backward design. Each module begins with clear learning outcomes and works backward to identify the activities, assessments, and resources needed to support mastery. In this model, outcomes matter more than time spent on any one activity. Accessibility was also a central priority. Having spent decades developing professional education, online learning, and micro-credential programs, I believe high-quality learning should meet learners where they are. For India RISE, this meant designing a flexible, hybrid experience that combines self-paced learning on JHU’s online learning platform, highly interactive live virtual workshops, reflective exercises, peer discussions, mentorship sessions, coaching, and in-person convenings. These formats are designed to fit together, accommodate different learning preferences, and maximize live sessions for skills application and peer engagement. This flexibility matters. India RISE fellows are researchers working in demanding institutional environments while balancing teaching, fieldwork, administrative duties, and personal commitments. A well-designed curriculum must respect that complexity while still creating momentum, shared progress, and honoring personal wellbeing. Our program competencies include resilient and adaptive leadership, and the curriculum supports fellows in building these skills for sustainable academic research careers. As motivation and incentive, fellows also have the opportunity to earn a Johns Hopkins verified micro-credential, helping them demonstrate their skills on CVs and digital profiles for career recognition and advancement. Mentorship as a Skillset My own experience with mentorship has shaped how I think about integrating it into the fellowship curriculum. Early in my career, a senior woman leader selected me as her mentee for a women’s leadership initiative. I had not yet built confidence in my professional path, but she saw potential in me before I fully saw it in myself. Since then, mentors, peers, supervisors, and male allies have helped me recognize my strengths and take the next step. Those experiences taught me that mentorship is not only about advice. It is about developing a mentorship skillset: knowing how to seek guidance, build trusted relationships, support peers, and eventually pay that support forward. India RISE embeds this through a triad mentorship model that includes dedicated India RISE Program Mentors, self-selected Technical Research Advisors, and both group and one-on-one mentoring formats. Together with peer engagement, coaching modules, and workshops, this model helps fellows grow not only as mentees, but also as future mentors within their own institutions. Leading From Wherever You Are Our approach to leadership development is also strengths-based. Through self-reflection, hands-on practice, and personalized coaching, fellows are encouraged to understand their values, voice, and vision. Tools such as strengths-based assessments help them identify how they lead, collaborate, and grow. The aim is to build self-awareness, efficacy, and agency, so fellows can lead from wherever they are. Developing the India RISE curriculum has been challenging, creative, and deeply meaningful. It has renewed my passion for thinking differently about integrated learning experiences

At the Hopkins India Conference 2026, the Gupta-Klinsky India Institute at Johns Hopkins University convened a roundtable titled “Reimagining Women’s Leadership in STEMM Research: Institutional Reforms That Work.” The discussion brought together senior voices from academia, policy, philanthropy, and global development to examine a persistent contradiction in India’s research ecosystem: while women’s participation in STEMM education has steadily increased, leadership within research institutions continues to remain disproportionately male. As part of the convening, the India RISE Fellowship invited fellows to submit practitioner-grounded institutional reform proposals based on their lived experiences within Indian research ecosystems. Selected fellows then presented their ideas directly to our panellists. What emerged was a powerful reminder that many of the barriers shaping women’s careers in STEMM are neither invisible nor inevitable. They are institutional. And importantly, they are reformable. Moving Beyond Mentorship Toward Sponsorship Across the presentations, one theme surfaced repeatedly: mentorship alone is insufficient without systems that actively create visibility and leadership opportunities for women researchers. Drawing from her experience within academic research environments, Dr. Sushama Agarwalla (IIT Hyderabad) argued that leadership progression often depends less on talent than on access to institutional networks, sponsorship, and nomination pathways that frequently remain informal and opaque. Her proposal focused on introducing structured sponsorship systems within institutions, where senior faculty and administrators would take explicit responsibility for recommending early- and mid-career women researchers for grants, committees, and leadership roles. She also proposed institutional dashboards to track women’s participation in leadership positions and decision-making structures over time. Similarly, Debyashreeta Barik, Ph.D., working in biotechnology and nanomedicine, highlighted the absence of formal mentorship and sponsorship pathways for women researchers navigating early career transitions. While informal mentoring relationships may exist, she noted that access often depends heavily on personal networks and institutional proximity. Her proposed reforms included structured mentorship programmes, leadership development support, and sponsorship mechanisms that would actively connect women researchers to collaborative projects, institutional committees, and funding opportunities. She also emphasised the need for re-entry pathways for researchers returning after caregiving-related career interruptions, including bridge funding, flexible promotion timelines, and temporary research support. Together, these proposals reflected a broader shift in the conversation around women in STEMM, from “fixing confidence gaps” to redesigning institutional systems that determine visibility, recognition, and advancement. The Invisible Labour Behind Academic Leadership In a particularly striking intervention, Anubhuti Joshi (AIIMS Rishikesh) examined what she described as the “hidden tax” placed on unmarried women researchers through a phenomenon known as singlism. Within many academic environments, she argued, unmarried women are often informally expected to absorb additional teaching, coordination, mentorship, and administrative responsibilities because they are perceived as more “available” than married colleagues. While these expectations rarely appear in formal policy, they accumulate over time in ways that directly affect research productivity, publication output, networking opportunities, and long-term leadership progression. To address this, Dr. Joshi proposed institutional workload transparency systems that would formally audit and track teaching loads, committee responsibilities, mentorship expectations, and administrative labour across departments. She also highlighted the growing precarity of contractual employment in Indian academia, where many women researchers remain excluded from long-term career pathways despite contributing substantially to institutional research output. Her proposed “contract-to-career-track” pathways aimed to create more stable leadership trajectories for high-performing contractual researchers through multi-year appointments, grant eligibility, and structured leadership development opportunities. From Individual Resilience to Institutional Design What made these presentations particularly compelling was their grounding in everyday institutional realities. Rather than framing gender inequity solely through individual experience, the fellows focused attention on how systems distribute opportunity, visibility, labour, and stability across academic life. The proposals also shared an important characteristic: practicality. None relied on abstract commitments to empowerment or representation. Instead, they centred on reforms institutions could realistically pilot within the next 12–24 months, from workload audits and sponsorship structures to re-entry pathways and expanded evaluation frameworks. At a moment when India is investing heavily in AI, biotechnology, public health, and advanced research ecosystems, the discussion reinforced a broader point emerging globally: scientific leadership pipelines are shaped as much by institutional design as by individual talent. The India RISE Fellowship hopes these conversations continue beyond a single convening and contribute to a growing ecosystem of institutions willing to experiment with measurable, accountable reforms that strengthen women’s leadership in STEMM research.

This article was originally published by IndiaBioscience as part of its Journey of a Young Investigator (JOYI) 2026 series and has been cross-posted on the India RISE platform with permission. The original article can be accessed on the IndiaBioscience website. In this Journey of a Young Investigator (JOYI) 2026 article, Ashitha S N M, Assistant Professor, DST INSPIRE Faculty Fellow, Department of Psychiatry, NIMHANS, reflects on the uncertain decisions, quiet resilience, and unexpected mentorship that shaped her journey through academia. From navigating a lonely PhD and motherhood to building a research career, she shares honest lessons about persistence, imperfect choices, and finding strength in community while balancing personal life and scientific ambition. Decisions How can a twenty-year-old aspiring scientist be sure that ​‘this’ is the right decision and that it will ensure future success? I was naïve too. My journey as a researcher has been shaped as much by uncertainty as by perseverance.  With limited academic mentorship, many of my early decisions were instinctive rather than strategic. I chose courses out of curiosity, and when the ​“PhD bug” bit me, I accepted the first offer that came my way, without fully understanding what a PhD entailed. Nearly a year later, the weight of that decision set in. At 24, I felt intellectually isolated and unsure of an exit route, even though my guide was kind-hearted.  What followed became the most defining phase of my life. With minimal guidance, I learned to rely on myself. I immersed myself in my research topic, framed my own questions, designed experiments, and wrote manuscripts, all of which were accepted on first submission. That period shaped me. The loneliness of my doctoral years instilled self-reliance, resilience, and a quiet belief in myself and my work. Retrospectively, I realise that it was this experience that enabled me to design and defend my DST-INSPIRE Faculty Fellowship proposal with conviction and confidence and within a year of completing my PhD, I was awarded this highly competitive grant.  Although my doctoral journey was lonely, it instilled a deep belief that ​‘hard work pays’. Over time, one principle has stayed with me- take a decision and make it work. Those early lessons continue to anchor me. Find your clan A PhD is a hard-won battle, and no one can reach the top without support. I was fortunate. When I made choices that, in hindsight, were not ideal, mentorship arrived in unexpected ways. My senior, Raviraj VS, became the wind under my wings. Having faced similar challenges, he helped me navigate the difficult situation I found myself stuck in. It was all I needed to stay afloat, gather my strength and refocus on academic excellence.  The second such instance was when I found my ​‘girl gang’, not when younger, but in my thirties. These were women who consistently showed up for me, without agenda. Through them, I experienced the strength of sisterhood rooted in pure intentions, a genuine desire to support one another through thick and thin with mutual respect and genuine support. The bane and boon of the thirties The thirties can be a very demanding decade. It is when the safety-net of being ​‘young’ begins to fade and responsibilities intensify. Irrespective of gender, this is often the stage when personal commitments pile up, demanding attention just as professional expectations peak.  In Indian academia, this pressure is particularly acute. Age limits for fellowships, faculty positions, and travel grants begin to narrow options. The academic clock for finding a regular position ticks alongside personal milestones of finding a partner, getting married, followed by the responsibility of making the house a home. Uncertainty on both fronts takes away one’s focus and tests one’s composure.  Yet, I have to admit there is a certain charm in being in our thirties. Emotional maturity begins to ground ambition in realism.  This decade brings in the much-needed clarity that helps us declutter thoughts, identify and filter out distractions and judge better. The thirties become a period of introspection and re-assessment, one that equips us to navigate life’s curveballs with steadier resolve and prepares us for the tougher challenges of middle age. Homegrown academic by circumstance It was not only personal, but also professional realities that shaped my decision to forego a postdoctoral fellowship abroad. When one completes a PhD in one’s thirties and marries soon after, career decisions become collective rather than individual. Ageing parents, the need for job stability for both partners, and questions about how, when and where to raise a child all enter the equation. No amount of conversations prior to marriage and future planning can resolve these uncertainties. For me, prioritising family stability became the guiding choice. The timing of my PhD completion compounded this situation, as it coincided with the onset of the COVID-19 pandemic. For nearly two years, conferences were inaccessible, limiting opportunities to present my work, build networks, and engage with potential postdoctoral mentors. Cold emails became my primary mode of outreach, often with limited response. In retrospect, several factors were at play: the global crisis, laboratories focused on continuity, and my keen interest in transitioning from genetics to patient-derived stem-cell models of psychiatric disorders, an area in which I lacked hands-on experience. Now, as a principal investigator (PI) myself, I understand why such a major pivot may not always align with a hiring PI’s expectation from a postdoctoral candidate, who is required to be independent and take on mentorship responsibilities. Do I regret staying back? Absolutely not. I learned a lot more that extends well beyond what a conventional postdoctoral trajectory might have offered. I learned adaptability, persistence, and perseverance. More importantly, I gained a better understanding of Indian academia. I remain intentional about staying current and competitive ‑presenting my work at conferences and building meaningful international collaborations.  The journey reassures me that there is no single path to scientific growth, only paths shaped by commitment, adaptability, and purpose. Lessons from motherhood My parents and extended family — my greatest cheerleaders — patiently supported my decision to complete my PhD before marriage. I was in my early thirties when my baby was born, and to say that life changed would be an understatement. My brain changed. When I confidently told my very supportive mentor Meera Purushottam, that I would return from maternity leave and complete X, Y, and Z, she gently warned me, ​“your brain will split into two, and you will function at half capacity”. Only in hindsight do I understand the