Minakshi Boruah – Computational Biology – Best Researcher Award

Minakshi Boruah - Computational Biology - Best Researcher Award

DR. B R AMBEDKAR NATIONAL INSTITUTE OF TECHNOLOGY - INDIA

EARLY ACADEMIC PURSUITS

Minakshi Boruah's academic journey reflects a commitment to excellence, evident from her academic achievements since school. With accolades like standing II in AISSE and winning academic prizes during her undergraduate years, she demonstrated a passion for learning and excelling in her studies.

PROFESSIONAL ENDEAVORS

Transitioning into her professional career, Minakshi Boruah continued to excel, qualifying competitive exams like GATE and NET UGC in Computer Science and Applications. Her work experience at Wipro further honed her skills, where she undertook certifications in AWS cloud and actively participated in various training programs and workshops.

CONTRIBUTIONS AND RESEARCH FOCUS

Minakshi Boruah's dedication to pursuing higher research-based studies in Computer Science and Engineering is evident from her participation in numerous workshops, training programs, and conferences. Her research interests extend to Computational Biology, as seen in her paper presentations and attendance at events like the SERB-INAE workshop.

IMPACT AND INFLUENCE

Through her active involvement in academic and research activities, Minakshi Boruah has made a significant impact on her peers and colleagues. Her paper presentations at prestigious conferences and receipt of the Best Paper Award highlight her contributions to the field of Computational Biology.

ACADEMIC CITES

Minakshi Boruah's research contributions have been recognized through her paper presentations at IEEE conferences and the receipt of the Best Paper Award. These achievements underscore her growing influence in the academic community and her potential for future scholarly contributions.

LEGACY AND FUTURE CONTRIBUTIONS

As Minakshi Boruah continues her journey in academia and research, her legacy is shaped by her dedication to excellence, passion for learning, and commitment to making meaningful contributions to the field of Computational Biology. Her future endeavors hold promise for further advancements in research and innovation.

NOTABLE PUBLICATION

CaDenseNet: a novel deep learning approach using capsule network with attention for the identification of HIV-1 integration site  2023

Identification of DNA motif using likelihood and attention based pooling method in the GRU framework  2022