Souvik Mandal

I'm Souvik Mandal.

I dream of a world where all life forms are dignified and free from exploitation, where every human has equal access to freedom, justice, opportunities, and knowledge, where growth harmonizes with sustainability.

I believe making high-quality and relevant education accessible to all can sustainably achieve this future, and I am dedicated to pursuing this vision.

After over 14 years working as an academic researcher, I transitioned to ed-tech in 2023. Currently, I work at LabXchange, a free, web-based educational platform by Harvard University, where I contribute as a data professional, learning expert, and AI specialist. I am also actively engaged in upholding human rights, educational outreach, policy-making, and creating tech startup initiatives.

Besides, I find joy in exploring nature, studying history, observing and training animals, listening to and playing music, painting, photography, and filmmaking. Please click the buttons below to explore my work, ideas, and interests.

Education
Research & Teaching
Data, Tech & AI
Art Corner

Education: My Vision for the Future

While the world accelerates into the future at an unprecedented pace, one crucial aspect of human progress has remained largely unchanged for centuries for a vast part of the global population – our approach to delivering formal education.

Globally, the quality of learning is alarmingly declining for a significant portion of the population¹. Persistent socio-economic factors aside, a major factor in this decline is the non-alignment between what students are taught through formal education and what they aspire to learn. Moreover, the feeling that their education is neither sufficiently enabling them to have a financially secure, dignified, and successful life, nor solving any overarching problem, or contributing to broader social progress is on the rise.

I am working towards transforming the education system in which every student can live up to their dreams, dreams that are small or big, common or wild, unleashing their true potential and the explorer within. This vision involves fluid exchange of knowledge transcending traditional subject boundaries, igniting curiosity, creativity, humility, and courage to think the unthinkable, discuss the unmentionable, and challange the unchallangable. ostering cooperation, problem-solving, and scientific thinking, as well as development of skills for tomorrow's job market and solving real-world problems. Achieving this will require empowering educators with up-to-date educational resources and comprehensive training, backed by the ever-evolving understanding of learning and pedagogy from scientific research.

LabXchange offers me to work towards transforming this vision into reality. Here at LabXchange, we have been developing a learning ecosystem for learners and educators that is interest-based and holistic, supports both self-learning and traditional classroom settings, and is accessible to everyone for free. The learning materials at LabXchange are carefully curated by trained scientists and expert educators, and aligned with curricula from various parts of the globe. We strive to ensure that every student can engage with content that resonates with their personal interests and professional ambitions.

Research & Teaching

My career as an academic researcher spanned over 14 years, during which I focused on cognition, learning, memory, cooperation, and searching strategies in social animals, particularly social insects. Throughout my research, I blended classical behavioral science and ecology with cutting-edge computational tools, including computer vision, data science, and artificial intelligence. Please click here to check my academic publications.

Before joining LabXchange, I worked as a post-doctoral scientist at Harvard University from 2018 to 2023. There, I worked on deciphering navigational decision-making in ants with Venki Murthy and on cooperative behavior with L. Mahadevan. A substantial focus of my research here was on creating tools to automate behavioral data collection from videos using computer vision and AI, supported by the Harvard Brain Science Initiative Pioneer Grant, given to scientists who take on "risky" pioneering projects, often involving developing new technologies. You can have a quick glimpse of my work in this article.

Before that, I explored the neurobiology of collective defense behavior in honeybees with Martin Giurfa in Toulouse, France as a visiting scientist. Before that, I obtained my PhD in Behavior Science/ Behavioral Ecology from the Centre for Ecological Science at the Indian Institute of Science, under the guidence of Raghavendra Gadagkar.

At Harvard, I created and taught a course "Computational Ethology" for three years (check below to access the course materials), and collaborated with Harvard Natural History Museum as an outreach scientist; here is a video produced by the museum explaining my work for non-experts. I have also taught Introductory Biology, Animal Behavior, Ecology, and Science communication at the undergraduate level.

COURSE WEBPAGE

DATA, TECH, & AI

Transitioning from Academia to Tech

Starting Off: My first brush with programming came around 2009-10, when I started wrangling and analyzing the data I collected for my PhD research. By the end of my PhD, I acquired quite a handsome set of skills required for data scientist roles in the industry.

Diving Deeper: But I decided to continue my research on behavior science and joined Venki Murthy’s lab at Harvard for my postdoc in 2018. It quickly became clear that mastering Python and automation was essential to streamline my workflows and scope of my research. Thanks to the supportive learning environment at Venki’s lab, this period was pivotal as I honed my skills in data collaboration, environment management, and version control, which are crucial for ensuring reproducibility and efficiency in research. In a short time, I started venturing into the realms of computer vision and artificial intelligence, fascinated by their potential to transform conventional research methodologies.

Teaching to Master It: Drawing inspiration from Richard Feynman, once I felt confident in my grasp of computer vision and AI, I decided to deepen my understanding through teaching. In 2020, I developed and began teaching a course titled "Computational Ethology." Teaching this course proved to be a dual learning journey—it not only refined my technical skills but also enhanced my capabilities in team management and educational delivery.

Moving Further: Curious about how the internet stitches together data and interfaces, I started learning about website data architectures, then progressed to big data, and gradually to data engineering. Each step was like a new door opening, broadening my understanding of the vast potential of data.

Generative AI – The Frontier: Since early 2023, I’ve been immersed in the intriguing world of Generative AI. This thrilling field is ripe with potential, poised to revolutionize our interactions with technology and how we harness its capabilities.

From my PhD days to now, every step has fueled my desire to harness technology not just as a tool, but as a cornerstone for building a smarter, better-connected world. As we continue to expand our horizons, let's commit to forging pathways that promise a better world for all. Here's to the relentless pursuit of knowledge, innovation, and meaningful impact!